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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1704.01478
|
Vladimir Belov
|
D. Yu. Akimov, V. A. Belov, O. V. Borshchev, A. A. Burenkov, Yu. L.
Grishkin, A. K. Karelin, A. V. Kuchenkov, A. N. Martemiyanov, S. A.
Ponomarenko, G. E. Simakov, V. N. Stekhanov, N. M. Surin, V. S. Timoshin, O.
Ya. Zeldovich
|
Test of SensL SiPM coated with NOL-1 wavelength shifter in liquid xenon
|
8 pages, 4 figures
| null |
10.1088/1748-0221/12/05/P05014
| null |
physics.ins-det
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
A SensL MicroFC-SMT-60035 6x6 mm$^2$ silicon photo-multiplier coated with a
NOL-1 wavelength shifter have been tested in the liquid xenon to detect the
175-nm scintillation light. For comparison, a Hamamatsu vacuum ultraviolet
sensitive MPPC VUV3 3x3 mm$^2$ was tested under the same conditions. The
photodetection efficiency of $13.1 \pm 2.5$% and $6.0 \pm 1.0$%,
correspondingly, is obtained.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.704292
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1704.02637
|
Peter Ma
|
Peter C. Ma, Yu Lv, Matthias Ihme
|
Numerical methods to prevent pressure oscillations in transcritical
flows
|
Annual Research Briefs 2016, Center for Turbulence Research, Stanford
University
| null | null | null |
physics.flu-dyn physics.comp-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The accurate and robust simulation of transcritical real-fluid effects is
crucial for many engineering applications, such as fuel injection in internal
combustion engines, rocket engines and gas turbines. For example, in diesel
engines, the liquid fuel is injected into the ambient gas at a pressure that
exceeds its critical value, and the fuel jet will be heated to a supercritical
temperature before combustion takes place. This process is often referred to as
transcritical injection. The largest thermodynamic gradient in the
transcritical regime occurs as the fluid undergoes a liquid-like to a gas-like
transition when crossing the pseudo-boiling line (Yang 2000, Oschwald et al.
2006, Banuti 2015). The complex processes during transcritical injection are
still not well understood. Therefore, to provide insights into high-pressure
combustion systems, accurate and robust numerical simulation tools are required
for the characterization of supercritical and transcritical flows.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709875
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1704.04091
|
Chao Zuo
|
Chao Zuo, Jiasong Sun, Jiaji Li, Jialin Zhang, Anand Asundi, Qian Chen
|
High-resolution transport-of-intensity quantitative phase microscopy
with annular illumination
|
This manuscript was originally submitted on 20 Feb. 2017
| null | null | null |
physics.optics physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
For quantitative phase imaging (QPI) based on transport-of-intensity equation
(TIE), partially coherent illumination provides speckle-free imaging,
compatibility with brightfield microscopy, and transverse resolution beyond
coherent diffraction limit. Unfortunately, in a conventional microscope with
circular illumination aperture, partial coherence tends to diminish the phase
contrast, exacerbating the inherent noise-to-resolution tradeoff in TIE
imaging, resulting in strong low-frequency artifacts and compromised imaging
resolution. Here, we demonstrate how these issues can be effectively addressed
by replacing the conventional circular illumination aperture with an annular
one. The matched annular illumination not only strongly boosts the phase
contrast for low spatial frequencies, but significantly improves the practical
imaging resolution to near the incoherent diffraction limit. By incorporating
high-numerical aperture (NA) illumination as well as high-NA objective, it is
shown, for the first time, that TIE phase imaging can achieve a transverse
resolution up to 208 nm, corresponding to an effective NA of 2.66. Time-lapse
imaging of in vitro Hela cells revealing cellular morphology and subcellular
dynamics during cells mitosis and apoptosis is exemplified. Given its
capability for high-resolution QPI as well as the compatibility with widely
available brightfield microscopy hardware, the proposed approach is expected to
be adopted by the wider biology and medicine community.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.713297
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1704.04613
|
Yang Mingkun
|
Xiang Bai, Mingkun Yang, Pengyuan Lyu, Yongchao Xu and Jiebo Luo
|
Integrating Scene Text and Visual Appearance for Fine-Grained Image
Classification
| null | null | null | null |
cs.CV
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Text in natural images contains rich semantics that are often highly relevant
to objects or scene. In this paper, we focus on the problem of fully exploiting
scene text for visual understanding. The main idea is combining word
representations and deep visual features into a globally trainable deep
convolutional neural network. First, the recognized words are obtained by a
scene text reading system. Then, we combine the word embedding of the
recognized words and the deep visual features into a single representation,
which is optimized by a convolutional neural network for fine-grained image
classification. In our framework, the attention mechanism is adopted to reveal
the relevance between each recognized word and the given image, which further
enhances the recognition performance. We have performed experiments on two
datasets: Con-Text dataset and Drink Bottle dataset, that are proposed for
fine-grained classification of business places and drink bottles, respectively.
The experimental results consistently demonstrate that the proposed method
combining textual and visual cues significantly outperforms classification with
only visual representations. Moreover, we have shown that the learned
representation improves the retrieval performance on the drink bottle images by
a large margin, making it potentially useful in product search.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.65683
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1704.04648
|
Gerd Christian Krizek
|
Gerd Christian Krizek
|
Einstein's 1935 papers: EPR=ER?
|
43 pages, typos corrected
| null | null | null |
physics.hist-ph quant-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In May of 1935, Einstein published with two co-authors the famous EPR-paper
about entangled particles, which questioned the completeness of Quantum
Mechanics by means of a gedankenexperiment. Only one month later, he published
a work that seems unconnected to the EPR-paper at first, the so called
Einstein-Rosen-paper, that presented a solution of the field equations for
particles in the framework of general relativity. Both papers ask for the
conception of completeness in a theory and, from a modern perspective, it is
easy to believe that there is a connection between these topics. We question
whether Einstein might have considered that a correlation between nonlocal
features of Quantum Mechanics and the Einstein-Rosen bridge can be used to
explain entanglement. We analyse this question by discussing the used
conceptions of "completeness," "atomistic structure of matter," and "quantum
phenomena." We discuss the historical embedding of the two works and the
context to modern research. Recent approaches are presented that formulate an
EPR=ER principle and claim an equivalence of the basic principles of these two
papers.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.710339
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1704.05825
|
Thomas K\"ollner
|
Thomas K\"ollner and Thomas Boeck and J\"org Schumacher
|
Thermal Rayleigh-Marangoni convection in a three-layer
liquid-metal-battery model
| null |
Phys. Rev. E 95, 053114 (2017)
|
10.1103/PhysRevE.95.053114
| null |
physics.flu-dyn
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The combined effects of buoyancy-driven Rayleigh-B\'{e}nard convection (RC)
and surface tension-driven Marangoni convection (MC) are studied in a
triple-layer configuration which serves as a simplified model for a liquid
metal battery (LMB). The three-layer model consists of a liquid metal alloy
cathode, a molten salt separation layer, and a liquid metal anode at the top.
Convection is triggered by the temperature gradient between the hot electrolyte
and the colder electrodes, which is a consequence of the release of resistive
heat during operation. We present a linear stability analysis of the state of
pure thermal conduction in combination with three-dimensional direct numerical
simulations of the nonlinear turbulent evolution on the basis of a
pseudospectral method. Five different modes of convection are identified in the
configuration, which are partly coupled to each other: RC in the upper
electrode, RC with internal heating in the molten salt layer, MC at both
interfaces between molten salt and electrode as well as anti-convectionin the
middle layer and lower electrode. The linear stability analysis confirms that
the additional Marangoni effect in the present setup increases the growth rates
of the linearly unstable modes, i.e. Marangoni and Rayleigh-B\'{e}nard
instability act together in the molten salt layer. The critical Grashof and
Marangoni numbers decrease with increasing middle layer thickness. The
calculated thresholds for the onset of convection are found for realistic
current densities of laboratory-sized LMBs. The global turbulent heat transfer
follows scaling predictions for internally heated RC. The global turbulent
momentum transfer is comparable with turbulent convection in the classical
Rayleigh-B\'{e}nard case.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709275
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1704.06512
|
Suyong Choi
|
Suyong Choi, Yunjun Kim, Youn Roh
|
Detection of Dark Photon Decaying into $e^+e^-$ using Cherenkov
Radiation
| null | null | null | null |
physics.ins-det hep-ex
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In dark photon search experiments with electron beam-dumps, it is difficult
to access the smaller dark photon life-time region of phase space due to
enormous backgrounds from low-energy particles emerging from the target. In
order to reduce the background, a thick beam-dump target is usually necessary.
We propose to detect the Cherenkov radiation in gas due to ultra-relativistic
electron and positron from dark photon decay. The secondary particles emerging
from the beam dump have very little chance to produce such Cherenkov radiation
in gas. Making use of the direction of the Cherenkov radiation, low background
dark photon search with thinner target is possible. This would allow one to
access challenging regions of the dark photon parameter space with low power
electron beams and low-cost experimental setup.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709517
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1704.07153
|
Mariusz Puchalski
|
Mariusz Puchalski, Jacek Komasa and Krzysztof Pachucki
|
Relativistic corrections for the ground electronic state of molecular
hydrogen
| null |
Phys. Rev. A 95, 052506 (2017)
|
10.1103/PhysRevA.95.052506
| null |
physics.chem-ph physics.atom-ph physics.comp-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We recalculate the leading relativistic corrections for the ground electronic
state of the hydrogen molecule using variational method with explicitly
correlated functions which satisfy the interelectronic cusp condition. The new
computational approach allowed for the control of the numerical precision which
reached about 8 significant digits. More importantly, the updated theoretical
energies became discrepant with the known experimental values and we conclude
that the yet unknown relativistic recoil corrections might be larger than
previously anticipated.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709358
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1704.08626
|
Jason Hindes
|
Jason Hindes and Ira B. Schwartz
|
Epidemic Extinction Paths in Complex Networks
| null |
Phys. Rev. E 95, 052317 (2017)
|
10.1103/PhysRevE.95.052317
| null |
physics.soc-ph cond-mat.dis-nn
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We study the extinction of long-lived epidemics on finite complex networks
induced by intrinsic noise. Applying analytical techniques to the stochastic
Susceptible-Infected-Susceptible model, we predict the distribution of large
fluctuations, the most probable, or optimal path through a network that leads
to a disease-free state from an endemic state, and the average extinction time
in general configurations. Our predictions agree with Monte-Carlo simulations
on several networks, including synthetic weighted and degree-distributed
networks with degree correlations, and an empirical high school contact
network. In addition, our approach quantifies characteristic scaling patterns
for the optimal path and distribution of large fluctuations, both near and away
from the epidemic threshold, in networks with heterogeneous eigenvector
centrality and degree distributions.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711104
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.00664
|
Ryutaro Tanno
|
Ryutaro Tanno, Daniel E. Worrall, Aurobrata Ghosh, Enrico Kaden,
Stamatios N. Sotiropoulos, Antonio Criminisi, Daniel C. Alexander
|
Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI
Super-Resolution
|
Accepted paper at MICCAI 2017
| null | null | null |
cs.CV
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In this work, we investigate the value of uncertainty modeling in 3D
super-resolution with convolutional neural networks (CNNs). Deep learning has
shown success in a plethora of medical image transformation problems, such as
super-resolution (SR) and image synthesis. However, the highly ill-posed nature
of such problems results in inevitable ambiguity in the learning of networks.
We propose to account for intrinsic uncertainty through a per-patch
heteroscedastic noise model and for parameter uncertainty through approximate
Bayesian inference in the form of variational dropout. We show that the
combined benefits of both lead to the state-of-the-art performance SR of
diffusion MR brain images in terms of errors compared to ground truth. We
further show that the reduced error scores produce tangible benefits in
downstream tractography. In addition, the probabilistic nature of the methods
naturally confers a mechanism to quantify uncertainty over the super-resolved
output. We demonstrate through experiments on both healthy and pathological
brains the potential utility of such an uncertainty measure in the risk
assessment of the super-resolved images for subsequent clinical use.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711017
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.01462
|
Naveen Mellempudi
|
Naveen Mellempudi, Abhisek Kundu, Dheevatsa Mudigere, Dipankar Das,
Bharat Kaul, Pradeep Dubey
|
Ternary Neural Networks with Fine-Grained Quantization
| null | null | null | null |
cs.LG cs.NE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We propose a novel fine-grained quantization (FGQ) method to ternarize
pre-trained full precision models, while also constraining activations to 8 and
4-bits. Using this method, we demonstrate a minimal loss in classification
accuracy on state-of-the-art topologies without additional training. We provide
an improved theoretical formulation that forms the basis for a higher quality
solution using FGQ. Our method involves ternarizing the original weight tensor
in groups of $N$ weights. Using $N=4$, we achieve Top-1 accuracy within $3.7\%$
and $4.2\%$ of the baseline full precision result for Resnet-101 and Resnet-50
respectively, while eliminating $75\%$ of all multiplications. These results
enable a full 8/4-bit inference pipeline, with best-reported accuracy using
ternary weights on ImageNet dataset, with a potential of $9\times$ improvement
in performance. Also, for smaller networks like AlexNet, FGQ achieves
state-of-the-art results. We further study the impact of group size on both
performance and accuracy. With a group size of $N=64$, we eliminate
$\approx99\%$ of the multiplications; however, this introduces a noticeable
drop in accuracy, which necessitates fine tuning the parameters at lower
precision. We address this by fine-tuning Resnet-50 with 8-bit activations and
ternary weights at $N=64$, improving the Top-1 accuracy to within $4\%$ of the
full precision result with $<30\%$ additional training overhead. Our final
quantized model can run on a full 8-bit compute pipeline using 2-bit weights
and has the potential of up to $15\times$ improvement in performance compared
to baseline full-precision models.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.710705
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.05914
|
Stefano De Leo
|
Stefano De Leo, Manoel P. Ara\'ujo, Gabriel G. Maia
|
The oscillatory behavior of light in the composite Goos-Haenchen shift
|
12 pages, 4 figures
|
Phys. Rev. A 95, 053836 (2017)
|
10.1103/PhysRevA.95.053836
| null |
physics.optics
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
For incidence in the critical region, the propagation of gaussian lasers
through triangular dielectric blocks is characterized by the joint action of
angular deviations and lateral displacements. This mixed effect, known as
composite Goos-Haenchen shift, produces a lateral displacement dependent on the
axial coordinate, recently confirmed by a weak measurement experiment. We
discuss under which conditions this axial lateral displacement, which only
exists for the composite Goos-Haenchen shift, presents an oscillatory behavior.
This oscillation phenomenon shows a peculiar behavior of light for critical
incidence and, if experimentally tested, could stimulate further theoretical
studies and lead to interesting optical applications.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.713234
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.06839
|
Chaoyang Wang
|
Chaoyang Wang, Hamed Kiani Galoogahi, Chen-Hsuan Lin, and Simon Lucey
|
Deep-LK for Efficient Adaptive Object Tracking
| null | null | null | null |
cs.CV
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In this paper we present a new approach for efficient regression based object
tracking which we refer to as Deep- LK. Our approach is closely related to the
Generic Object Tracking Using Regression Networks (GOTURN) framework of Held et
al. We make the following contributions. First, we demonstrate that there is a
theoretical relationship between siamese regression networks like GOTURN and
the classical Inverse-Compositional Lucas & Kanade (IC-LK) algorithm. Further,
we demonstrate that unlike GOTURN IC-LK adapts its regressor to the appearance
of the currently tracked frame. We argue that this missing property in GOTURN
can be attributed to its poor performance on unseen objects and/or viewpoints.
Second, we propose a novel framework for object tracking - which we refer to as
Deep-LK - that is inspired by the IC-LK framework. Finally, we show impressive
results demonstrating that Deep-LK substantially outperforms GOTURN.
Additionally, we demonstrate comparable tracking performance to current state
of the art deep-trackers whilst being an order of magnitude (i.e. 100 FPS)
computationally efficient.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.712148
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.07954
|
Alessandro Salandrino
|
Susobhan Das, Shima Fardad, Inki Kim, Junsuk Rho, Rongqing Hui,
Alessandro Salandrino
|
Nanophotonic modal dichroism: mode-multiplexed modulators
| null |
Opt. Lett. 41, 4394-4397 (2016)
|
10.1364/OL.41.004394
| null |
physics.app-ph physics.optics
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
As the diffraction limit is approached, device miniaturization to integrate
more functionality per area becomes more and more challenging. Here we propose
a novel strategy to increase the functionality-per-area by exploiting the modal
properties of a waveguide system. With such approach the design of a
mode-multiplexed nanophotonic modulator relying on the mode-selective
absorption of a patterned Indium-Tin-Oxide is proposed. Full-wave simulations
of a device operating at the telecom wavelength of 1550nm show that two modes
can be independently modulated, while maintaining performances in line with
conventional single-mode ITO modulators reported in the recent literature. The
proposed design principles can pave the way to a novel class of
mode-multiplexed compact photonic devices able to effectively multiply the
functionality-per-area in integrated photonic systems.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711717
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.08144
|
Regine Schuppe
|
Peter Fulde
|
Wavefunctions for large electronic systems
|
9 pages, 2 figures
| null | null | null |
physics.chem-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Wavefunctions for large electron numbers suffer from an exponential growth of
the Hilbert space which is required for their description. In fact, as pointed
out by W. Kohn, for electron numbers $N > N_0$ where $N_0 \approx 10^3$ they
become meaningless (exponential wall problem). Nevertheless, despite of the
enormous successes of density functional theory, one would also like to develop
electronic structure calculations for large systems based on wavefunctions.
This is possible if one defines the latter in Liouville space with a cumulant
metric rather than in Hilbert space. The cluster expansion of the free energy
of a classical monoatomic gas makes it plausible that cumulants are a proper
tool for electronic structure calculations.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709875
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.08226
|
Vladimir Burdyuzha
|
Vladimir Burdyuzha
|
The Dark Components of the Universe Are Slowly Clarified
|
34 pages, 0 figures
|
JETP 124 (2017) 358-368 pp
|
10.1134/S1063776117020029
| null |
physics.gen-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The dark sector of the Universe is beginning to be clarified step by step. If
the dark energy is vacuum energy, then 123 orders are exactly reduced by
ordinary physical processes. For many years these unexplained orders were
called a crisis in physics. There was indeed a "crisis" before the introduction
of the holographic principle and entropic force in physics. The vacuum energy
was spent for the organization of new microstates during the entire life of the
Universe, but in the initial period of its evolution the vacuum energy (78
orders) were reduced more effectively by the vacuum condensates produced by
phase transitions, because the Universe lost the high symmetry during its
expansion. Important problems of physics and cosmology can be solved if the
quarks, leptons, and gauge bosons are composite particles. The dark matter,
partially or all consisting of familon-type pseudo-Goldstone bosons with a mass
of 10^{-5} - 10^{-3} eV, can be explained in the composite model. Three
generations of elementary particles are absolutely necessary in this model. In
addition, this model realizes three relativistic phase transitions in a medium
of familons at different red shifts, forming a large-scale structure of dark
matter that was "repeated" by baryons. We predict the detection of dark matter
dynamics, the detection of familons as dark matter particles, and the
development of spectroscopy for dark medium due to the probable presence of
dark atoms in it. Other viewpoints on the dark components of the Universe are
also discussed briefly.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711761
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.08286
|
Qibin Zhao Dr
|
Qibin Zhao, Masashi Sugiyama, Andrzej Cichocki
|
Learning Efficient Tensor Representations with Ring Structure Networks
|
arXiv admin note: substantial text overlap with arXiv:1606.05535
| null | null | null |
cs.NA
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Tensor train (TT) decomposition is a powerful representation for high-order
tensors, which has been successfully applied to various machine learning tasks
in recent years. However, since the tensor product is not commutative,
permutation of data dimensions makes solutions and TT-ranks of TT decomposition
inconsistent. To alleviate this problem, we propose a permutation symmetric
network structure by employing circular multilinear products over a sequence of
low-order core tensors. This network structure can be graphically interpreted
as a cyclic interconnection of tensors, and thus we call it tensor ring (TR)
representation. We develop several efficient algorithms to learn TR
representation with adaptive TR-ranks by employing low-rank approximations.
Furthermore, mathematical properties are investigated, which enables us to
perform basic operations in a computationally efficiently way by using TR
representations. Experimental results on synthetic signals and real-world
datasets demonstrate that the proposed TR network is more expressive and
consistently informative than existing TT networks.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711066
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.08715
|
Harsh Beohar
|
Harsh Beohar and Sebastian K\"upper
|
On path-based coalgebras and weak notions of bisimulation
|
A long version (with proofs) of CALCO'17 paper
| null | null | null |
cs.LO
|
http://creativecommons.org/licenses/by/4.0/
|
It is well known that the theory of coalgebras provides an abstract
definition of behavioural equivalence that coincides with strong bisimulation
across a wide variety of state-based systems. Unfortunately, the theory in the
presence of so-called silent actions is not yet fully developed. In this paper,
we give a coalgebraic characterisation of branching bisimulation in the context
of labelled transition systems and fully probabilistic systems. It is shown
that recording executions (up to a notion of stuttering), rather than the set
of successor states, from a state is sufficient to characterise branching
bisimulation in both cases.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.708741
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.09276
|
Yue Wang
|
Yue Wang and Yeye He
|
Synthesizing Mapping Relationships Using Table Corpus
|
The long version of a paper published at SIGMOD 2017
| null | null | null |
cs.DB
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Mapping relationships, such as (country, country-code) or (company,
stock-ticker), are versatile data assets for an array of applications in data
cleaning and data integration like auto-correction and auto-join. However,
today there are no good repositories of mapping tables that can enable these
intelligent applications.
Given a corpus of tables such as web tables or spreadsheet tables, we observe
that values of these mappings often exist in pairs of columns in same tables.
Motivated by their broad applicability, we study the problem of synthesizing
mapping relationships using a large table corpus. Our synthesis process
leverages compatibility of tables based on co-occurrence statistics, as well as
constraints such as functional dependency. Experiment results using web tables
and enterprise spreadsheets suggest that the proposed approach can produce high
quality mappings.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.708769
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.09499
|
Scientific Information Service CERN
|
V. Baglin, P. Chiggiato, P. Cruikshank, M. Gallilee, C. Garion and R.
Kersevan
|
Vacuum System
|
11 pages, chapter 12 in High-Luminosity Large Hadron Collider
(HL-LHC) : Preliminary Design Report
|
CERN Yellow Report CERN 2015-005, pp.195-205
|
10.5170/CERN-2015-005.195
| null |
physics.acc-ph
|
http://creativecommons.org/licenses/by/4.0/
|
Chapter 12 in High-Luminosity Large Hadron Collider (HL-LHC) : Preliminary
Design Report. The Large Hadron Collider (LHC) is one of the largest scientific
instruments ever built. Since opening up a new energy frontier for exploration
in 2010, it has gathered a global user community of about 7,000 scientists
working in fundamental particle physics and the physics of hadronic matter at
extreme temperature and density. To sustain and extend its discovery potential,
the LHC will need a major upgrade in the 2020s. This will increase its
luminosity (rate of collisions) by a factor of five beyond the original design
value and the integrated luminosity (total collisions created) by a factor ten.
The LHC is already a highly complex and exquisitely optimised machine so this
upgrade must be carefully conceived and will require about ten years to
implement. The new configuration, known as High Luminosity LHC (HL-LHC), will
rely on a number of key innovations that push accelerator technology beyond its
present limits. Among these are cutting-edge 11-12 tesla superconducting
magnets, compact superconducting cavities for beam rotation with ultra-precise
phase control, new technology and physical processes for beam collimation and
300 metre-long high-power superconducting links with negligible energy
dissipation. The present document describes the technologies and components
that will be used to realise the project and is intended to serve as the basis
for the detailed engineering design of HL-LHC.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.710946
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.09501
|
Scientific Information Service CERN
|
E. Bravin, B. Dehning, R. Jones, T. Lefevre and H. Schmickler
|
Beam Instrumentation and Long-Range Beam-Beam Compensation
|
14 pages, chapter 13 in High-Luminosity Large Hadron Collider
(HL-LHC) : Preliminary Design Report
|
CERN Yellow Report CERN 2015-005, pp. 207-220
|
10.5170/CERN-2015-005.207
| null |
physics.acc-ph
|
http://creativecommons.org/licenses/by/4.0/
|
Chapter 13 in High-Luminosity Large Hadron Collider (HL-LHC) : Preliminary
Design Report. The Large Hadron Collider (LHC) is one of the largest scientific
instruments ever built. Since opening up a new energy frontier for exploration
in 2010, it has gathered a global user community of about 7,000 scientists
working in fundamental particle physics and the physics of hadronic matter at
extreme temperature and density. To sustain and extend its discovery potential,
the LHC will need a major upgrade in the 2020s. This will increase its
luminosity (rate of collisions) by a factor of five beyond the original design
value and the integrated luminosity (total collisions created) by a factor ten.
The LHC is already a highly complex and exquisitely optimised machine so this
upgrade must be carefully conceived and will require about ten years to
implement. The new configuration, known as High Luminosity LHC (HL-LHC), will
rely on a number of key innovations that push accelerator technology beyond its
present limits. Among these are cutting-edge 11-12 tesla superconducting
magnets, compact superconducting cavities for beam rotation with ultra-precise
phase control, new technology and physical processes for beam collimation and
300 metre-long high-power superconducting links with negligible energy
dissipation. The present document describes the technologies and components
that will be used to realise the project and is intended to serve as the basis
for the detailed engineering design of HL-LHC.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.710534
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.09584
|
Scientific Information Service CERN
|
V. Malka
|
Plasma Wake Accelerators: Introduction and Historical Overview
|
28 pages, CAS - CERN Accelerator School: Plasma Wake Acceleration,
CERN, Geneva, Switzerland, 23 - 29 Nov 2014
|
CERN Yellow Report CERN-2016-001, pp.1-28
|
10.5170/CERN-2016-001.1
| null |
physics.acc-ph
|
http://creativecommons.org/licenses/by/4.0/
|
Fundamental questions on the nature of matter and energy have found answers
thanks to the use of particle accelerators. Societal applications, such as
cancer treatment or cancer imaging, illustrate the impact of accelerators in
our current life. Today, accelerators use metallic cavities that sustain
electricfields with values limited to about 100 MV/m. Because of their ability
to support extreme accelerating gradients, the plasma medium has recently been
proposed for future cavity-like accelerating structures. This contribution
highlights the tremendous evolution of plasma accelerators driven by either
laser or particle beams that allow the production of high quality particle
beams with a degree of tunability and a set of parameters that make them very
pertinent for many applications.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709778
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.09696
|
Domingos Soares
|
Domingos S. L. Soares, Marcos C. D. Neves, Andre K. T. Assis
|
Arp's Indomitable Universe
|
9 pages, 4 figures, pp. 185-197 of the book "The Galileo of Palomar:
Essays in Memory of Halton Arp" (Apeiron, Montreal, 2017)
| null | null | null |
physics.hist-ph astro-ph.CO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We present some aspects of the work and personality of Halton Christian Arp
(1927-2013).
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.70782
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.09864
|
Haojin Yang
|
Haojin Yang, Martin Fritzsche, Christian Bartz, Christoph Meinel
|
BMXNet: An Open-Source Binary Neural Network Implementation Based on
MXNet
|
4 pages
| null | null | null |
cs.LG cs.CV cs.NE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Binary Neural Networks (BNNs) can drastically reduce memory size and accesses
by applying bit-wise operations instead of standard arithmetic operations.
Therefore it could significantly improve the efficiency and lower the energy
consumption at runtime, which enables the application of state-of-the-art deep
learning models on low power devices. BMXNet is an open-source BNN library
based on MXNet, which supports both XNOR-Networks and Quantized Neural
Networks. The developed BNN layers can be seamlessly applied with other
standard library components and work in both GPU and CPU mode. BMXNet is
maintained and developed by the multimedia research group at Hasso Plattner
Institute and released under Apache license. Extensive experiments validate the
efficiency and effectiveness of our implementation. The BMXNet library, several
sample projects, and a collection of pre-trained binary deep models are
available for download at https://github.com/hpi-xnor
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.7108
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.09899
|
Zeerak Butt
|
Zeerak Waseem, Thomas Davidson, Dana Warmsley, Ingmar Weber
|
Understanding Abuse: A Typology of Abusive Language Detection Subtasks
|
To appear in the proceedings of the 1st Workshop on Abusive Language
Online. Please cite that version
| null | null | null |
cs.CL
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
As the body of research on abusive language detection and analysis grows,
there is a need for critical consideration of the relationships between
different subtasks that have been grouped under this label. Based on work on
hate speech, cyberbullying, and online abuse we propose a typology that
captures central similarities and differences between subtasks and we discuss
its implications for data annotation and feature construction. We emphasize the
practical actions that can be taken by researchers to best approach their
abusive language detection subtask of interest.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709994
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.09929
|
Suraiya Jabin
|
Mudasir Ahmad Wani, Suraiya Jabin
|
A sneak into the Devil's Colony - Fake Profiles in Online Social
Networks
|
31 pages, 8 figures
| null | null | null |
cs.SI
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Online Social Networks (OSNs) play an important role for internet users to
carry out their daily activities like content sharing, news reading, posting
messages, product reviews and discussing events etc. At the same time, various
kinds of spammers are also equally attracted towards these OSNs. These cyber
criminals including sexual predators, online fraudsters, advertising
campaigners, catfishes, and social bots etc. exploit the network of trust by
various means especially by creating fake profiles to spread their content and
carry out scams. All these malicious identities are very harmful for both the
users as well as the service providers. From the OSN service provider point of
view, fake profiles affect the overall reputation of the network in addition to
the loss of bandwidth. To spot out these malicious users, huge manpower effort
and more sophisticated automated methods are needed. In this paper, various
types of OSN threat generators like compromised profiles, cloned profiles and
online bots (spam bots, social bots, like bots and influential bots) have been
classified. An attempt is made to present several categories of features that
have been used to train classifiers in order to identify a fake profile.
Different data crawling approaches along with some existing data sources for
fake profile detection have been identified. A refresher on existing cyber laws
to curb social media based cyber crimes with their limitations is also
presented.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.714977
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10129
|
Tobias Wenger
|
Tobias Wenger, Giovanni Viola, Jari Kinaret, Mikael Fogelstr\"om, and
Philippe Tassin
|
High-sensitivity plasmonic refractive index sensing using graphene
|
This is an author-created, un-copyedited version of an article
accepted for publication/published in 2DMaterials. IOP Publishing Ltd is not
responsible for any errors or omissions in this version of the manuscript or
any version derived from it. The Version of Record is available online at
https://doi.org/10.1088/2053-1583/aa70ff
|
2DMaterials, 4, 025103 (2017)
|
10.1088/2053-1583/aa70ff
| null |
cond-mat.mes-hall physics.optics
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We theoretically demonstrate a high-sensitivity, graphene-plasmon based
refractive index sensor working in the mid-infrared at room temperature. The
bulk figure of merit of our sensor reaches values above $10$, but the key
aspect of our proposed plasmonic sensor is its surface sensitivity which we
examine in detail. We have used realistic values regarding doping level and
electron relaxation time, which is the limiting factor for the sensor
performance. Our results show quantitatively the high performance of
graphene-plasmon based refractive index sensors working in the mid-infrared.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.712398
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10134
|
Egor Malykh
|
Egor Malykh, Sergey Novoselov, Oleg Kudashev
|
On Residual CNN in text-dependent speaker verification task
|
Accepted for Specom 2017
| null | null | null |
cs.SD cs.LG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Deep learning approaches are still not very common in the speaker
verification field. We investigate the possibility of using deep residual
convolutional neural network with spectrograms as an input features in the
text-dependent speaker verification task. Despite the fact that we were not
able to surpass the baseline system in quality, we achieved a quite good
results for such a new approach getting an 5.23% ERR on the RSR2015 evaluation
part. Fusion of the baseline and proposed systems outperformed the best
individual system by 18% relatively.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711432
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10182
|
Taiji Suzuki
|
Taiji Suzuki
|
Fast learning rate of deep learning via a kernel perspective
|
36 pages
| null | null | null |
math.ST cs.LG stat.ML stat.TH
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We develop a new theoretical framework to analyze the generalization error of
deep learning, and derive a new fast learning rate for two representative
algorithms: empirical risk minimization and Bayesian deep learning. The series
of theoretical analyses of deep learning has revealed its high expressive power
and universal approximation capability. Although these analyses are highly
nonparametric, existing generalization error analyses have been developed
mainly in a fixed dimensional parametric model. To compensate this gap, we
develop an infinite dimensional model that is based on an integral form as
performed in the analysis of the universal approximation capability. This
allows us to define a reproducing kernel Hilbert space corresponding to each
layer. Our point of view is to deal with the ordinary finite dimensional deep
neural network as a finite approximation of the infinite dimensional one. The
approximation error is evaluated by the degree of freedom of the reproducing
kernel Hilbert space in each layer. To estimate a good finite dimensional
model, we consider both of empirical risk minimization and Bayesian deep
learning. We derive its generalization error bound and it is shown that there
appears bias-variance trade-off in terms of the number of parameters of the
finite dimensional approximation. We show that the optimal width of the
internal layers can be determined through the degree of freedom and the
convergence rate can be faster than $O(1/\sqrt{n})$ rate which has been shown
in the existing studies.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709278
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10286
|
Debashish Chowdhury
|
Colin D. Kinz-Thompson, Ajeet K. Sharma, Joachim Frank, Ruben L.
Gonzalez, Jr., Debashish Chowdhury
|
Quantitative Connection Between Ensemble Thermodynamics and
Single-Molecule Kinetics: A Case Study Using Cryogenic Electron Microscopy
and Single-Molecule Fluorescence Resonance Energy Transfer Investigations of
the Ribosome
|
43 pages, including 6 figures
|
Journal of Physical Chemistry B (ACS, USA, 2015), vol. 119, 10888
(2015)
|
10.1021/jp5128805
| null |
physics.bio-ph cond-mat.stat-mech physics.chem-ph q-bio.SC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
At equilibrium, thermodynamic and kinetic information can be extracted from
biomolecular energy landscapes by many techniques. However, while static,
ensemble techniques yield thermodynamic data, often only dynamic,
single-molecule techniques can yield the kinetic data that describes
transition-state energy barriers. Here we present a generalized framework based
upon dwell-time distributions that can be used to connect such static, ensemble
techniques with dynamic, single-molecule techniques, and thus characterize
energy landscapes to greater resolutions. We demonstrate the utility of this
framework by applying it to cryogenic electron microscopy (cryo-EM) and
single-molecule fluorescence resonance energy transfer (smFRET) studies of the
bacterial ribosomal pre-translocation complex. Among other benefits,
application of this framework to these data explains why two transient,
intermediate conformations of the pre-translocation complex, which are observed
in a cryo-EM study, may not be observed in several smFRET studies.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.70788
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10311
|
Abhay Shah
|
Junjie Bai, Abhay Shah and Xiaodong Wu
|
Optimal Multi-Object Segmentation with Novel Gradient Vector Flow Based
Shape Priors
|
Paper in review
| null | null | null |
cs.CV
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Shape priors have been widely utilized in medical image segmentation to
improve segmentation accuracy and robustness. A major way to encode such a
prior shape model is to use a mesh representation, which is prone to causing
self-intersection or mesh folding. Those problems require complex and expensive
algorithms to mitigate. In this paper, we propose a novel shape prior directly
embedded in the voxel grid space, based on gradient vector flows of a
pre-segmentation. The flexible and powerful prior shape representation is ready
to be extended to simultaneously segmenting multiple interacting objects with
minimum separation distance constraint. The problem is formulated as a Markov
random field problem whose exact solution can be efficiently computed with a
single minimum s-t cut in an appropriately constructed graph. The proposed
algorithm is validated on two multi-object segmentation applications: the brain
tissue segmentation in MRI images, and the bladder/prostate segmentation in CT
images. Both sets of experiments show superior or competitive performance of
the proposed method to other state-of-the-art methods.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.710734
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10313
|
Alexander W. Winkler
|
Alexander W Winkler, Farbod Farshidian, Diego Pardo, Michael Neunert
and Jonas Buchli
|
Fast Trajectory Optimization for Legged Robots using Vertex-based ZMP
Constraints
|
currently under review for IEEE RA-L
| null | null | null |
cs.RO math.OC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
This paper combines the fast Zero-Moment-Point (ZMP) approaches that work
well in practice with the broader range of capabilities of a Trajectory
Optimization formulation, by optimizing over body motion, footholds and Center
of Pressure simultaneously. We introduce a vertex-based representation of the
support-area constraint, which can treat arbitrarily oriented point-, line-,
and area-contacts uniformly. This generalization allows us to create motions
such quadrupedal walking, trotting, bounding, pacing, combinations and
transitions between these, limping, bipedal walking and push-recovery all with
the same approach. This formulation constitutes a minimal representation of the
physical laws (unilateral contact forces) and kinematic restrictions (range of
motion) in legged locomotion, which allows us to generate various motion in
less than a second. We demonstrate the feasibility of the generated motions on
a real quadruped robot.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709221
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10342
|
Thomas Lukasiewicz
|
Patrick Hohenecker and Thomas Lukasiewicz
|
Deep Learning for Ontology Reasoning
|
9 pages
| null | null | null |
cs.AI cs.LG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In this work, we present a novel approach to ontology reasoning that is based
on deep learning rather than logic-based formal reasoning. To this end, we
introduce a new model for statistical relational learning that is built upon
deep recursive neural networks, and give experimental evidence that it can
easily compete with, or even outperform, existing logic-based reasoners on the
task of ontology reasoning. More precisely, we compared our implemented system
with one of the best logic-based ontology reasoners at present, RDFox, on a
number of large standard benchmark datasets, and found that our system attained
high reasoning quality, while being up to two orders of magnitude faster.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711578
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10368
|
Jose Eduardo Novoa Ilic
|
Jos\'e Novoa, Josu\'e Fredes and N\'estor Becerra Yoma
|
DNN-based uncertainty estimation for weighted DNN-HMM ASR
| null | null | null | null |
cs.SD cs.NE
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
In this paper, the uncertainty is defined as the mean square error between a
given enhanced noisy observation vector and the corresponding clean one. Then,
a DNN is trained by using enhanced noisy observation vectors as input and the
uncertainty as output with a training database. In testing, the DNN receives an
enhanced noisy observation vector and delivers the estimated uncertainty. This
uncertainty in employed in combination with a weighted DNN-HMM based speech
recognition system and compared with an existing estimation of the noise
cancelling uncertainty variance based on an additive noise model. Experiments
were carried out with Aurora-4 task. Results with clean, multi-noise and
multi-condition training are presented.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709549
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10375
|
Bekir Sait Ciftler
|
Bekir Sait Ciftler and Adem Tuncer and Ismail Guvenc
|
Indoor UAV Navigation to a Rayleigh Fading Source Using Q-Learning
|
3 pages, 4 figures, in review for IEEE IoTJ
| null | null | null |
cs.NI
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Unmanned aerial vehicles (UAVs) can be used to localize victims, deliver
first-aid, and maintain wireless connectivity to victims and first responders
during search/rescue and public safety scenarios. In this letter, we consider
the problem of navigating a UAV to a Rayleigh fading wireless signal source,
e.g. the Internet-of-Things (IoT) devices such as smart watches and other
wearables owned by the victim in an indoor environment. The source is assumed
to transmit RF signals, and a Q-learning algorithm is used to navigate the UAV
to the vicinity of the source. Our results show that the time averaging window
and the exploration rate for the Q-learning algorithm can be optimized for
fastest navigation of the UAV to the IoT device. As a result, Q-learning
achieves the best performance with smaller convergence time overall.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.712005
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10385
|
Minje Kim
|
Minje Kim
|
Collaborative Deep Learning for Speech Enhancement: A Run-Time Model
Selection Method Using Autoencoders
| null |
Proc. of the IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP), pp 76-80, March 2017
| null | null |
cs.SD cs.LG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We show that a Modular Neural Network (MNN) can combine various speech
enhancement modules, each of which is a Deep Neural Network (DNN) specialized
on a particular enhancement job. Differently from an ordinary ensemble
technique that averages variations in models, the propose MNN selects the best
module for the unseen test signal to produce a greedy ensemble. We see this as
Collaborative Deep Learning (CDL), because it can reuse various already-trained
DNN models without any further refining. In the proposed MNN selecting the best
module during run time is challenging. To this end, we employ a speech
AutoEncoder (AE) as an arbitrator, whose input and output are trained to be as
similar as possible if its input is clean speech. Therefore, the AE can gauge
the quality of the module-specific denoised result by seeing its AE
reconstruction error, e.g. low error means that the module output is similar to
clean speech. We propose an MNN structure with various modules that are
specialized on dealing with a specific noise type, gender, and input
Signal-to-Noise Ratio (SNR) value, and empirically prove that it almost always
works better than an arbitrarily chosen DNN module and sometimes as good as an
oracle result.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.708639
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10394
|
Giuliano Gadioli La Guardia
|
Pedro J. Miranda and Giuliano La Guardia
|
On a relational theory of biological systems: a natural model for
complex biological behavior
| null | null | null | null |
nlin.AO physics.soc-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In this paper, we develop a natural (empirical) relational theory for
describing and modeling complex biological phenomena. We have as stepping stone
the assertion: function implies structure. The theory is built upon a graph's
theory structure in which a diffusion model of information takes place, and
where dynamics can be investigated in order to generate steady quantifiers. In
this context, we improve a seminal work by adding a free context biological
importance measure given by the Shannon's Entropy. We also introduce the
concept of biological loci. Such concept stands for closely related biological
agents which plays a role as an agent by itself. Our results allow us to
synthesize a natural model for complex biological behavior that takes into
account: system's update, irreducibility, and exploit of the dynamical behavior
mounted over a diffusion model. The model deals in final terms to its natural
capacity to model plasticity and environmental changes, which has an intrinsic
relationship with Shannon's Entropy and the sort of dynamics that biological
systems can display.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.70985
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10396
|
Zachary Friggstad
|
Sara Ahmadian and Zachary Friggstad
|
Further Approximations for Demand Matching: Matroid Constraints and
Minor-Closed Graphs
| null | null | null | null |
cs.DS
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We pursue a study of the Generalized Demand Matching problem, a common
generalization of the $b$-Matching and Knapsack problems. Here, we are given a
graph with vertex capacities, edge profits, and asymmetric demands on the
edges. The goal is to find a maximum-profit subset of edges so the demands of
chosen edges do not violate vertex capacities. This problem is APX-hard and
constant-factor approximations are known.
Our results fall into two categories. First, using iterated relaxation and
various filtering strategies, we show with an efficient rounding algorithm if
an additional matroid structure $\mathcal M$ is given and we further only allow
sets $F \subseteq E$ that are independent in $\mathcal M$, the natural LP
relaxation has an integrality gap of at most $\frac{25}{3} \approx 8.333$. This
can be improved in various special cases, for example we improve over the
15-approximation for the previously-studied Coupled Placement problem [Korupolu
et al. 2014] by giving a $7$-approximation.
Using similar techniques, we show the problem of computing a minimum-cost
base in $\mathcal M$ satisfying vertex capacities admits a $(1,3)$-bicriteria
approximation. This improves over the previous $(1,4)$-approximation in the
special case that $\mathcal M$ is the graphic matroid over the given graph
[Fukanaga and Nagamochi, 2009].
Second, we show Demand Matching admits a polynomial-time approximation scheme
in graphs that exclude a fixed minor. If all demands are polynomially-bounded
integers, this is somewhat easy using dynamic programming in bounded-treewidth
graphs. Our main technical contribution is a sparsification lemma allowing us
to scale the demands to be used in a more intricate dynamic programming
algorithm, followed by randomized rounding to filter our scaled-demand solution
to a feasible solution.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.707546
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10404
|
Cun Mu
|
Cun Mu, Daniel Hsu, Donald Goldfarb
|
Successive Rank-One Approximations for Nearly Orthogonally Decomposable
Symmetric Tensors
| null |
SIAM Journal on Matrix Analysis and Applications 36.4 (2015):
1638-1659
|
10.1137/15M1010890
| null |
cs.NA
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Many idealized problems in signal processing, machine learning and statistics
can be reduced to the problem of finding the symmetric canonical decomposition
of an underlying symmetric and orthogonally decomposable (SOD) tensor. Drawing
inspiration from the matrix case, the successive rank-one approximations (SROA)
scheme has been proposed and shown to yield this tensor decomposition exactly,
and a plethora of numerical methods have thus been developed for the tensor
rank-one approximation problem. In practice, however, the inevitable errors
(say) from estimation, computation, and modeling necessitate that the input
tensor can only be assumed to be a nearly SOD tensor---i.e., a symmetric tensor
slightly perturbed from the underlying SOD tensor. This article shows that even
in the presence of perturbation, SROA can still robustly recover the symmetric
canonical decomposition of the underlying tensor. It is shown that when the
perturbation error is small enough, the approximation errors do not accumulate
with the iteration number. Numerical results are presented to support the
theoretical findings.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709825
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10405
|
Nicolas Le Roux
|
Cl\'ement Calauz\`enes and Nicolas Le Roux
|
Distributed SAGA: Maintaining linear convergence rate with limited
communication
| null | null | null | null |
math.OC cs.LG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In recent years, variance-reducing stochastic methods have shown great
practical performance, exhibiting linear convergence rate when other stochastic
methods offered a sub-linear rate. However, as datasets grow ever bigger and
clusters become widespread, the need for fast distribution methods is pressing.
We propose here a distribution scheme for SAGA which maintains a linear
convergence rate, even when communication between nodes is limited.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709982
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10407
|
Gang Wang
|
Gang Wang and Georgios B. Giannakis and Yousef Saad and Jie Chen
|
Solving Almost all Systems of Random Quadratic Equations
|
27 pages, 8 figures
| null | null | null |
math.OC cs.IT math.IT stat.ML
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
This paper deals with finding an $n$-dimensional solution $x$ to a system of
quadratic equations of the form $y_i=|\langle{a}_i,x\rangle|^2$ for $1\le i \le
m$, which is also known as phase retrieval and is NP-hard in general. We put
forth a novel procedure for minimizing the amplitude-based least-squares
empirical loss, that starts with a weighted maximal correlation initialization
obtainable with a few power or Lanczos iterations, followed by successive
refinements based upon a sequence of iteratively reweighted (generalized)
gradient iterations. The two (both the initialization and gradient flow) stages
distinguish themselves from prior contributions by the inclusion of a fresh
(re)weighting regularization technique. The overall algorithm is conceptually
simple, numerically scalable, and easy-to-implement. For certain random
measurement models, the novel procedure is shown capable of finding the true
solution $x$ in time proportional to reading the data $\{(a_i;y_i)\}_{1\le i
\le m}$. This holds with high probability and without extra assumption on the
signal $x$ to be recovered, provided that the number $m$ of equations is some
constant $c>0$ times the number $n$ of unknowns in the signal vector, namely,
$m>cn$. Empirically, the upshots of this contribution are: i) (almost) $100\%$
perfect signal recovery in the high-dimensional (say e.g., $n\ge 2,000$) regime
given only an information-theoretic limit number of noiseless equations,
namely, $m=2n-1$ in the real-valued Gaussian case; and, ii) (nearly) optimal
statistical accuracy in the presence of additive noise of bounded support.
Finally, substantial numerical tests using both synthetic data and real images
corroborate markedly improved signal recovery performance and computational
efficiency of our novel procedure relative to state-of-the-art approaches.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709216
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10411
|
Thomas Chaigne
|
Thomas Chaigne, Bastien Arnal, Sergey Vilov, Emmanuel Bossy, Ori Katz
|
Super-resolution photoacoustic imaging via flow induced absorption
fluctuations
| null | null | null | null |
physics.optics
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In deep tissue photoacoustic imaging the spatial resolution is inherently
limited by the acoustic wavelength. We present an approach for surpassing the
acoustic diffraction limit by exploiting temporal fluctuations in the sample
absorption distribution, such as those induced by flowing particles. In
addition to enhanced resolution, our approach inherently provides background
reduction, and can be implemented with any conventional photoacoustic imaging
system. The considerable resolution increase is made possible by adapting
notions from super-resolution optical fluctuations imaging (SOFI) developed for
blinking fluorescent molecules, to flowing acoustic emitters. By generalizing
SOFI mathematical analysis to complex valued signals, we demonstrate
super-resolved photoacoustic images that are free from oscillations caused by
band-limited detection. The presented technique holds potential for
contrast-agent free micro-vessels imaging, as red blood cells provide a strong
endogenous source of naturally fluctuating absorption.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.712335
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10413
|
Evgeny Zamyatin I
|
Evgeny Zamyatin, Andrey Filchenkov
|
Learning to Generate Chairs with Generative Adversarial Nets
|
Submitted to NIPS 2017
| null | null | null |
cs.CV
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Generative adversarial networks (GANs) has gained tremendous popularity
lately due to an ability to reinforce quality of its predictive model with
generated objects and the quality of the generative model with and supervised
feedback. GANs allow to synthesize images with a high degree of realism.
However, the learning process of such models is a very complicated optimization
problem and certain limitation for such models were found. It affects the
choice of certain layers and nonlinearities when designing architectures. In
particular, it does not allow to train convolutional GAN models with
fully-connected hidden layers. In our work, we propose a modification of the
previously described set of rules, as well as new approaches to designing
architectures that will allow us to train more powerful GAN models. We show the
effectiveness of our methods on the problem of synthesizing projections of 3D
objects with the possibility of interpolation by class and view point.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.710546
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10420
|
Basura Fernando
|
Basura Fernando and Stephen Gould
|
Discriminatively Learned Hierarchical Rank Pooling Networks
|
International Journal of Computer Vision
| null | null | null |
cs.CV
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In this work, we present novel temporal encoding methods for action and
activity classification by extending the unsupervised rank pooling temporal
encoding method in two ways. First, we present "discriminative rank pooling" in
which the shared weights of our video representation and the parameters of the
action classifiers are estimated jointly for a given training dataset of
labelled vector sequences using a bilevel optimization formulation of the
learning problem. When the frame level features vectors are obtained from a
convolutional neural network (CNN), we rank pool the network activations and
jointly estimate all parameters of the model, including CNN filters and
fully-connected weights, in an end-to-end manner which we coined as "end-to-end
trainable rank pooled CNN". Importantly, this model can make use of any
existing convolutional neural network architecture (e.g., AlexNet or VGG)
without modification or introduction of additional parameters. Then, we extend
rank pooling to a high capacity video representation, called "hierarchical rank
pooling". Hierarchical rank pooling consists of a network of rank pooling
functions, which encode temporal semantics over arbitrary long video clips
based on rich frame level features. By stacking non-linear feature functions
and temporal sub-sequence encoders one on top of the other, we build a high
capacity encoding network of the dynamic behaviour of the video. The resulting
video representation is a fixed-length feature vector describing the entire
video clip that can be used as input to standard machine learning classifiers.
We demonstrate our approach on the task of action and activity recognition.
Obtained results are comparable to state-of-the-art methods on three important
activity recognition benchmarks with classification performance of 76.7% mAP on
Hollywood2, 69.4% on HMDB51, and 93.6% on UCF101.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.712987
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10421
|
David Moss
|
Marcello Ferrera, Yongwoo Park, Luca Razzari, Brent E. Little, Sai T.
Chu, Roberto Morandotti, David J. Moss, and Jose Azana
|
First and second order all-optical integrating functions in a photonic
integrated circuit
|
9 pages, 5 figures, 27 references
|
optics express volume 19, issue (23) pages 23153-23161 (2011)
|
10.1364/OE.19.023153
| null |
physics.optics
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We demonstrate all-optical temporal integration of arbitrary optical
waveforms with temporal features as short as ~1.9ps. By using a four-port
micro-ring resonator based on CMOS compatible doped glass technology we perform
the 1st- and 2nd-order cumulative time integral of optical signals over a
bandwidth that exceeds 400GHz. This device has applications for a wide range of
ultra-fast data processing and pulse shaping functions as well as in the field
of optical computing for the real-time analysis of differential equations.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709621
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10423
|
David Moss
|
A.Pasquazi, M.Peccianti, M.Lamont, R.Morandotti, B.E Little, S.Chu and
D.J Moss
|
Parametric gain and wavelength conversion via third order nonlinear
optics a CMOS compatible waveguide
|
8 pages, 4 figures, 30 references
|
Optics Express volume 18, issue (8) pages 7634-7641 (2010)
|
10.1364/OE.18.007634
| null |
physics.optics
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We demonstrate sub-picosecond wavelength conversion in the C-band via four
wave mixing in a 45cm long high index doped silica spiral waveguide. We achieve
an on/off conversion efficiency (signal to idler) of +16.5dB as well as a
parametric gain of +15dB for a peak pump power of 38W over a wavelength range
of 100nm. Furthermore, we demonstrated a minimum gain of +5dB over a wavelength
range as large as 200nm.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709549
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10432
|
Hamid Mirzaei Buini
|
Hamid Mirzaei, Tony Givargis
|
Fine-grained acceleration control for autonomous intersection management
using deep reinforcement learning
|
Accepted in IEEE Smart World Congress 2017
| null | null | null |
cs.AI cs.RO cs.SY
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Recent advances in combining deep learning and Reinforcement Learning have
shown a promising path for designing new control agents that can learn optimal
policies for challenging control tasks. These new methods address the main
limitations of conventional Reinforcement Learning methods such as customized
feature engineering and small action/state space dimension requirements. In
this paper, we leverage one of the state-of-the-art Reinforcement Learning
methods, known as Trust Region Policy Optimization, to tackle intersection
management for autonomous vehicles. We show that using this method, we can
perform fine-grained acceleration control of autonomous vehicles in a grid
street plan to achieve a global design objective.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.707934
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10437
|
Nikolaos Sahinidis
|
Nikolaos Ploskas, Christopher Laughman, Arvind U. Raghunathan,
Nikolaos V. Sahinidis
|
Optimization of circuitry arrangements for heat exchangers using
derivative-free optimization
| null | null |
10.1016/j.cherd.2017.05.015
| null |
cs.CE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Optimization of the refrigerant circuitry can improve a heat exchanger's
performance. Design engineers currently choose the refrigerant circuitry
according to their experience and heat exchanger simulations. However, the
design of an optimized refrigerant circuitry is difficult. The number of
refrigerant circuitry candidates is enormous. Therefore, exhaustive search
algorithms cannot be used and intelligent techniques must be developed to
explore the solution space efficiently. In this paper, we formulate refrigerant
circuitry design as a binary constrained optimization problem. We use
CoilDesigner, a simulation and design tool of air to refrigerant heat
exchangers, in order to simulate the performance of different refrigerant
circuitry designs. We treat CoilDesigner as a black-box system since the exact
relationship of the objective function with the decision variables is not
explicit. Derivative-free optimization (DFO) algorithms are suitable for
solving this black-box model since they do not require explicit functional
representations of the objective function and the constraints. The aim of this
paper is twofold. First, we compare four mixed-integer constrained DFO solvers
and one box-bounded DFO solver and evaluate their ability to solve a difficult
industrially relevant problem. Second, we demonstrate that the proposed
formulation is suitable for optimizing the circuitry configuration of heat
exchangers. We apply the DFO solvers to 17 heat exchanger design problems.
Results show that TOMLAB/glcDirect and TOMLAB/glcSolve can find optimal or
near-optimal refrigerant circuitry designs after a relatively small number of
circuit simulations.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.708629
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10439
|
Oliver Knill
|
Oliver Knill
|
On a Dehn-Sommerville functional for simplicial complexes
|
24 pages, 10 figures
| null | null | null |
math.CO cs.CG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Assume G is a finite abstract simplicial complex with f-vector (v0,v1, ...),
and generating function f(x) = sum(k=1 v(k-1) x^k = v0 x + v1 x^2+ v2 x^3 +
..., the Euler characteristic of G can be written as chi(G)=f(0)-f(-1). We
study here the functional f1'(0)-f1'(-1), where f1' is the derivative of the
generating function f1 of G1. The Barycentric refinement G1 of G is the Whitney
complex of the finite simple graph for which the faces of G are the vertices
and where two faces are connected if one is a subset of the other. Let L is the
connection Laplacian of G, which is L=1+A, where A is the adjacency matrix of
the connection graph G', which has the same vertex set than G1 but where two
faces are connected they intersect. We have f1'(0)=tr(L) and for the Green
function g L^(-1) also f1'(-1)=tr(g) so that eta1(G) = f1'(0)-f1'(-1) is equal
to eta(G)=tr(L-L^(-1). The established formula tr(g)=f1'(-1) for the generating
function of G1 complements the determinant expression det(L)=det(g)=zeta(-1)
for the Bowen-Lanford zeta function zeta(z)=1/det(1-z A) of the connection
graph G' of G. We also establish a Gauss-Bonnet formula eta1(G) = sum(x in
V(G1) chi(S(x)), where S(x) is the unit sphere of x the graph generated by all
vertices in G1 directly connected to x. Finally, we point out that the
functional eta0(G) = sum(x in V(G) chi(S(x)) on graphs takes arbitrary small
and arbitrary large values on every homotopy type of graphs.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709959
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10443
|
Victor Silva
|
Victor do Nascimento Silva and Luiz Chaimowicz
|
MOBA: a New Arena for Game AI
| null | null | null | null |
cs.AI
|
http://creativecommons.org/licenses/by/4.0/
|
Games have always been popular testbeds for Artificial Intelligence (AI). In
the last decade, we have seen the rise of the Multiple Online Battle Arena
(MOBA) games, which are the most played games nowadays. In spite of this, there
are few works that explore MOBA as a testbed for AI Research. In this paper we
present and discuss the main features and opportunities offered by MOBA games
to Game AI Research. We describe the various challenges faced along the game
and also propose a discrete model that can be used to better understand and
explore the game. With this, we aim to encourage the use of MOBA as a novel
research platform for Game AI.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.713548
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10447
|
Jimmy Ren
|
Jimmy Ren, Zhiyang Yu, Jianbo Liu, Rui Zhang, Wenxiu Sun, Jiahao Pang,
Xiaohao Chen, Qiong Yan
|
Robust Tracking Using Region Proposal Networks
| null | null | null | null |
cs.CV
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Recent advances in visual tracking showed that deep Convolutional Neural
Networks (CNN) trained for image classification can be strong feature
extractors for discriminative trackers. However, due to the drastic difference
between image classification and tracking, extra treatments such as model
ensemble and feature engineering must be carried out to bridge the two domains.
Such procedures are either time consuming or hard to generalize well across
datasets. In this paper we discovered that the internal structure of Region
Proposal Network (RPN)'s top layer feature can be utilized for robust visual
tracking. We showed that such property has to be unleashed by a novel loss
function which simultaneously considers classification accuracy and bounding
box quality. Without ensemble and any extra treatment on feature maps, our
proposed method achieved state-of-the-art results on several large scale
benchmarks including OTB50, OTB100 and VOT2016. We will make our code publicly
available.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709961
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10449
|
Yaohang Li
|
Hao Ji, Michael Mascagni, Yaohang Li
|
Gaussian Variant of Freivalds' Algorithm for Efficient and Reliable
Matrix Product Verification
| null | null | null | null |
cs.DS
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In this article, we consider the general problem of checking the correctness
of matrix multiplication. Given three $n \times n$ matrices $A$, $B$, and $C$,
the goal is to verify that $A \times B=C$ without carrying out the
computationally costly operations of matrix multiplication and comparing the
product $A \times B$ with $C$, term by term. This is especially important when
some or all of these matrices are very large, and when the computing
environment is prone to soft errors. Here we extend Freivalds' algorithm to a
Gaussian Variant of Freivalds' Algorithm (GVFA) by projecting the product $A
\times B$ as well as $C$ onto a Gaussian random vector and then comparing the
resulting vectors. The computational complexity of GVFA is consistent with that
of Freivalds' algorithm, which is $O(n^{2})$. However, unlike Freivalds'
algorithm, whose probability of a false positive is $2^{-k}$, where $k$ is the
number of iterations. Our theoretical analysis shows that when $A \times B \neq
C$, GVFA produces a false positive on set of inputs of measure zero with exact
arithmetic. When we introduce round-off error and floating point arithmetic
into our analysis, we can show that the larger this error, the higher the
probability that GVFA avoids false positives. Moreover, by iterating GVFA $k$
times, the probability of a false positive decreases as $p^k$, where $p$ is a
very small value depending on the nature of the fault on the result matrix and
the arithmetic system's floating-point precision. Unlike deterministic
algorithms, there do not exist any fault patterns that are completely
undetectable with GVFA. Thus GVFA can be used to provide efficient fault
tolerance in numerical linear algebra, and it can be efficiently implemented on
modern computing architectures. In particular, GVFA can be very efficiently
implemented on architectures with hardware support for fused multiply-add
operations.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.70723
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10453
|
Hamidreza Alvari
|
Hamidreza Alvari
|
Twitter Hashtag Recommendation using Matrix Factorization
| null | null | null | null |
cs.SI cs.IR
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Twitter, one of the biggest and most popular microblogging Websites, has
evolved into a powerful communication platform which allows millions of active
users to generate huge volume of microposts and queries on a daily basis. To
accommodate effective categorization and easy search, users are allowed to make
use of hashtags, keywords or phrases prefixed by hash character, to categorize
and summarize their posts. However, valid hashtags are not restricted and thus
are created in a free and heterogeneous style, increasing difficulty of the
task of tweet categorization. In this paper, we propose a low-rank weighted
matrix factorization based method to recommend hashtags to the users solely
based on their hashtag usage history and independent from their tweets'
contents. We confirm using two-sample t-test that users are more likely to
adopt new hashtags similar to the ones they have previously adopted. In
particular, we formulate the problem of hashtag recommendation into an
optimization problem and incorporate hashtag correlation weight matrix into it
to account for the similarity between different hashtags. We finally leverage
widely used matrix factorization from recommender systems to solve the
optimization problem by capturing the latent factors of users and hashtags.
Empirical experiments demonstrate that our method is capable to properly
recommend hashtags.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711839
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10455
|
Hamidreza Alvari
|
Hamidreza Alvari
|
Exploiting Consistency Theory for Modeling Twitter Hashtag Adoption
| null | null | null | null |
cs.SI
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Twitter, a microblogging service, has evolved into a powerful communication
platform with millions of active users who generate immense volume of
microposts on a daily basis. To facilitate effective categorization and easy
search, users adopt hashtags, keywords or phrases preceded by hash (#)
character. Successful prediction of the spread and propagation of information
in the form of trending topics or hashtags in Twitter, could help real time
identification of new trends and thus improve marketing efforts. Social
theories such as consistency theory suggest that people prefer harmony or
consistency in their thoughts. In Twitter, for example, users are more likely
to adopt the same trending hashtag multiple times before it eventually dies. In
this paper, we propose a low-rank weighted matrix factorization approach to
model trending hashtag adoption in Twitter based on consistency theory. In
particular, we first cast the problem of modeling trending hashtag adoption
into an optimization problem, then integrate consistency theory into it as a
regularization term and finally leverage widely used matrix factorization to
solve the optimization. Empirical experiments demonstrate that our method
outperforms other baselines in predicting whether a specific trending hashtag
will be used by users in future.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.712567
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10459
|
Itsik Bergel
|
Avi Zanko, Itsik Bergel and Amir Leshem
|
Deep-LMS for gigabit transmission over unshielded twisted pair cables
| null | null | null | null |
cs.IT math.IT
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In this paper we propose a rapidly converging LMS algorithm for crosstalk
cancellation. The architecture is similar to deep neural networks, where
multiple layers are adapted sequentially. The application motivating this
approach is gigabit rate transmission over unshielded twisted pairs using a
vectored system. The crosstalk cancellation algorithm uses an adaptive
non-diagonal preprocessing matrix prior to a conventional LMS crosstalk
canceler. The update of the preprocessing matrix is inspired by deep neural
networks. However, since most the operations in the Deep-LMS algorithm are
linear, we are capable of providing an exact convergence speed analysis. The
role of the preprocessing matrix is to speed up the convergence of the
conventional LMS crosstalk canceler and hence the convergence of the overall
system. The Deep-LMS is important for crosstalk cancellation in the novel
G.fast standard, where traditional LMS converges very slowly due to the
ill-conditioned covariance matrix of the received signal at the extended
bandwidth. Simulation results support our analysis and show significant
reduction in convergence time compared to existing LMS variants.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709225
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10475
|
Brynle Barrett
|
G. Lefevre, G. Condon, I. Riou, L. Chichet, M. Essayeh, M. Rabault, L.
Antoni-Micollier, N. Mielec, D. Holleville, L. Amand, R. Geiger, A.
Landragin, M. Prevedelli, B. Barrett, B. Battelier, A. Bertoldi, B. Canuel,
P. Bouyer
|
Studies of general relativity with quantum sensors
|
11 pages, 7 figures, to appear in "Proceedings of the 52nd Rencontres
de Moriond on Gravitation"
| null | null | null |
physics.atom-ph gr-qc quant-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We present two projects aiming to probe key aspects of the theory of General
Relativity with high-precision quantum sensors. These projects use cold-atom
interferometry with the aim of measuring gravitational waves and testing the
equivalence principle. To detect gravitational waves, a large multi-sensor
demonstrator is currently under construction that will exploit correlations
between three atom interferometers spread along a 200 m optical cavity.
Similarly, a test of the weak equivalence principle is currently underway using
a compact and mobile dual-species interferometer, which will serve as a
prototype for future high-precision tests onboard an orbiting satellite. We
present recent results and improvements related to both projects.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.699383
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10494
|
Baruch Epstein
|
Baruch Epstein. Ron Meir, Tomer Michaeli
|
Joint auto-encoders: a flexible multi-task learning framework
| null | null | null | null |
stat.ML cs.LG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The incorporation of prior knowledge into learning is essential in achieving
good performance based on small noisy samples. Such knowledge is often
incorporated through the availability of related data arising from domains and
tasks similar to the one of current interest. Ideally one would like to allow
both the data for the current task and for previous related tasks to
self-organize the learning system in such a way that commonalities and
differences between the tasks are learned in a data-driven fashion. We develop
a framework for learning multiple tasks simultaneously, based on sharing
features that are common to all tasks, achieved through the use of a modular
deep feedforward neural network consisting of shared branches, dealing with the
common features of all tasks, and private branches, learning the specific
unique aspects of each task. Once an appropriate weight sharing architecture
has been established, learning takes place through standard algorithms for
feedforward networks, e.g., stochastic gradient descent and its variations. The
method deals with domain adaptation and multi-task learning in a unified
fashion, and can easily deal with data arising from different types of sources.
Numerical experiments demonstrate the effectiveness of learning in domain
adaptation and transfer learning setups, and provide evidence for the flexible
and task-oriented representations arising in the network.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711007
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10496
|
Christian Schmidt
|
Christian Schmidt and Eleanor Dunn and Madeleine Lowery and Ursula van
Rienen
|
Uncertainty Quantification of Oscillation Suppression during DBS in a
Coupled Finite Element and Network Model
|
10 pages
| null |
10.1109/TNSRE.2016.2608925
| null |
q-bio.NC cs.CE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Models of the cortico-basal ganglia network and volume conductor models of
the brain can provide insight into the mechanisms of action of deep brain
stimulation (DBS). In this study, the coupling of a network model, under
parkinsonian conditions, to the extracellular field distribution obtained from
a three dimensional finite element model of a rodent's brain during DBS is
presented. This coupled model is used to investigate the influence of
uncertainty in the electrical properties of brain tissue and encapsulation
tissue, formed around the electrode after implantation, on the suppression of
oscillatory neural activity during DBS. The resulting uncertainty in this
effect of DBS on the network activity is quantified using a computationally
efficient and non-intrusive stochastic approach based on the generalized
Polynomial Chaos. The results suggest that variations in the electrical
properties of brain tissue may have a substantial influence on the level of
suppression of oscillatory activity during DBS. Applying a global sensitivity
analysis on the suppression of the simulated oscillatory activity showed that
the influence of uncertainty in the electrical properties of the encapsulation
tissue had only a minor influence, in agreement with previous experimental and
computational studies investigating the mechanisms of current-controlled DBS in
the literature.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.708052
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10503
|
Marko Jankovic
|
Marko V. Jankovic
|
Quantum Low Entropy based Associative Reasoning or QLEAR Learning
| null | null | null | null |
cs.LG cs.IT math.IT
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In this paper, we propose the classification method based on a learning
paradigm we are going to call Quantum Low Entropy based Associative Reasoning
or QLEAR learning. The approach is based on the idea that classification can be
understood as supervised clustering, where a quantum entropy in the context of
the quantum probabilistic model, will be used as a "capturer" (measure, or
external index), of the "natural structure" of the data. By using quantum
entropy we do not make any assumption about linear separability of the data
that are going to be classified. The basic idea is to find close neighbors to a
query sample and then use relative change in the quantum entropy as a measure
of similarity of the newly arrived sample with the representatives of interest.
In other words, method is based on calculation of quantum entropy of the
referent system and its relative change with the addition of the newly arrived
sample. Referent system consists of vectors that represent individual classes
and that are the most similar, in Euclidean distance sense, to the vector that
is analyzed. Here, we analyze the classification problem in the context of
measuring similarities to prototype examples of categories. While nearest
neighbor classifiers are natural in this setting, they suffer from the problem
of high variance (in bias-variance decomposition) in the case of limited
sampling. Alternatively, one could use machine learning techniques (like
support vector machines) but they involve time-consuming optimization. Here we
propose a hybrid of nearest neighbor and machine learning technique which deals
naturally with the multi-class setting, has reasonable computational complexity
both in training and at run time, and yields excellent results in practice.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.712552
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10504
|
Daniel Errandonea
|
A. Benmakhlouf, D. Errandonea, M. Bouchenafa, S. Maabed, A.
Bouhemadou, A. Bentabet
|
New Pressure-Induced Polymorphic Transitions of Anhydrous Magnesium
Sulfate
|
35 paginas, 9 figures, Table 9
|
Dalton Trans. 46, 5058 - 5068 (2017)
|
10.1039/c7dt00539c
| null |
cond-mat.mtrl-sci physics.chem-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The effects of pressure on the crystal structure of the three known
polymorphs of magnesium sulfate have been theoretically study by means of DFT
calculations up to 45 GPa. We determined that at ambient conditions gamma MgSO4
is an unstable polymorph, which decompose into MgO and SO3, and that the
response of the other two polymorphs to hydrostatic pressure is non isotropic.
Additionally we found that at all pressures beta MgSO4 has a largest enthalpy
than alpha MgSO4. This indicates that beta MgSO4 is thermodynamically unstable
versus alpha MgSO4 and predicts the occurrence of a beta alpha phase transition
under moderate compression. Our calculations also predict the existence under
pressure of additional phase transitions to two new polymorphs of MgSO4, which
we named as delta MgSO4 and epsilon MgSO4. The alpha delta transition is
predicted to occur at 17.5 GPa, and the delta epsilon transition at 35 GPa,
pressures that nowadays can be experimentally easily achieved. All the
predicted structural transforma ions are characterized as first order
transitions. This suggests that they can be non reversible, and therefore the
new polymorphs could be recovered as metastable polymorphs at ambient
conditions. The crystal structure of the two new polymorphs is reported. In
them, the coordination number of sulfur is four as in the previously known
polymorphs, but the coordination number of magnesium is eight instead of six.
In the article we will report the axial and bond compressibility for the four
polymorphs of MgSO4. The pressure volume equation of state of each phase is
also given. The values obtained for the bulk modulus are 62 GPa, 57 GPa, 102
GPa, and 119 GPa for alpha MgSO4, beta MgSO4, delta MgSO4, and epsilon MgSO4,
respectively. Finally, the electronic band structure of these four polymorphs
of MgSO4 has been calculated by the first time.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.712773
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10507
|
Daniel Errandonea
|
David Santamaria Perez, Tomas Marqueno, Simon MacLeod, Javier Ruiz
Fuertes, Dominik Daisenberger, Raquel Chulia Jordan, Daniel Errandonea, Jose
Luis Jorda, Fernando Rey, Chris McGuire, Adam Mahkluf, Abby Kavner, Catalin
Popescu
|
Structural evolution of CO2 filled pure silica LTA zeolite under
high-pressure high-temperature conditions
|
29 pages, 9 figures, 5 tables
|
Chem. Mater. 29, 4502 - 4510 (2017)
|
10.1021/acs.chemmater.7b01158
| null |
cond-mat.mtrl-sci physics.chem-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The crystal structure of CO2 filled pure SiO2 LTA zeolite has been studied at
high pressures and temperatures using synchrotron based x ray powder
diffraction. Its structure consists of 13 CO2 guest molecules, 12 of them
accommodated in the large alpha cages and 1 in the beta cages, giving a
SiO2:CO2 stoichiometric ratio smaller than 2. The structure remains stable
under pressure up to 20 GPa with a slight pressure dependent rhombohedral
distortion, indicating that pressure induced amorphization is prevented by the
insertion of guest species in this open framework. The ambient-temperature
lattice compressibility has been determined. In situ high pressure resistive
heating experiments up to 750 K allow us to estimate the thermal expansivity at
5 GPa. Our data confirm that the insertion of CO2 reverses the negative thermal
expansion of the empty zeolite structure. No evidence of any chemical reaction
was observed. The possibility of synthesizing a silicon carbonate at high
temperatures and higher pressures is discussed in terms of the evolution of C-O
and Si-O distances between molecular and framework atoms.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709018
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10520
|
Laszlo Csirmaz
|
Laszlo Csirmaz and Peter Ligeti
|
Secret sharing on large girth graphs
| null | null | null | null |
cs.IT math.CO math.IT
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We investigate graph based secret sharing schemes and its information ratio,
also called complexity, measuring the maximal amount of information the
vertices has to store. It was conjectured that in large girth graphs, where the
interaction between far away nodes is restricted to a single path, this ratio
is bounded. This conjecture was supported by several result, most notably by a
result of Csirmaz and Ligeti saying that the complexity of graphs with girth at
least six and no neighboring high degree vertices is strictly below 2. In this
paper we refute the above conjecture. First, a family of $d$-regular graphs is
defined iteratively such that the complexity of these graphs is the largest
possible $(d+1)/2$ allowed by Stinson's bound. This part extends earlier
results of van Dijk and Blundo et al, and uses the so-called entropy method.
Second, using combinatorial arguments, we show that this family contains graphs
with arbitrary large girth. In particular, we obtain the following purely
combinatorial result, which might be interesting on its own: there are
$d$-regular graphs with arbitrary large girth such that any fractional
edge-cover by stars (or by complete multipartite graphs) must cover some vertex
$(d+1)/2$ times.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711226
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10524
|
Zhanyu Ma
|
Zhanyu Ma, Jing-Hao Xue, Arne Leijon, Zheng-Hua Tan, Zhen Yang, and
Jun Guo
|
Decorrelation of Neutral Vector Variables: Theory and Applications
| null | null | null | null |
cs.CV stat.ML
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In this paper, we propose novel strategies for neutral vector variable
decorrelation. Two fundamental invertible transformations, namely serial
nonlinear transformation and parallel nonlinear transformation, are proposed to
carry out the decorrelation. For a neutral vector variable, which is not
multivariate Gaussian distributed, the conventional principal component
analysis (PCA) cannot yield mutually independent scalar variables. With the two
proposed transformations, a highly negatively correlated neutral vector can be
transformed to a set of mutually independent scalar variables with the same
degrees of freedom. We also evaluate the decorrelation performances for the
vectors generated from a single Dirichlet distribution and a mixture of
Dirichlet distributions. The mutual independence is verified with the distance
correlation measurement. The advantages of the proposed decorrelation
strategies are intensively studied and demonstrated with synthesized data and
practical application evaluations.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.71057
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10528
|
Joshua Achiam
|
Joshua Achiam, David Held, Aviv Tamar, Pieter Abbeel
|
Constrained Policy Optimization
|
Accepted to ICML 2017
| null | null | null |
cs.LG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
For many applications of reinforcement learning it can be more convenient to
specify both a reward function and constraints, rather than trying to design
behavior through the reward function. For example, systems that physically
interact with or around humans should satisfy safety constraints. Recent
advances in policy search algorithms (Mnih et al., 2016, Schulman et al., 2015,
Lillicrap et al., 2016, Levine et al., 2016) have enabled new capabilities in
high-dimensional control, but do not consider the constrained setting.
We propose Constrained Policy Optimization (CPO), the first general-purpose
policy search algorithm for constrained reinforcement learning with guarantees
for near-constraint satisfaction at each iteration. Our method allows us to
train neural network policies for high-dimensional control while making
guarantees about policy behavior all throughout training. Our guarantees are
based on a new theoretical result, which is of independent interest: we prove a
bound relating the expected returns of two policies to an average divergence
between them. We demonstrate the effectiveness of our approach on simulated
robot locomotion tasks where the agent must satisfy constraints motivated by
safety.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709488
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10529
|
Scientific Information Service CERN
|
P. Gibbon
|
Introduction to Plasma Physics
|
15 pages, contribution to the CAS - CERN Accelerator School: Plasma
Wake Acceleration, CERN, Geneva, Switzerland, 23 - 29 Nov 2014
|
CERN Yellow Report CERN-2016-001, pp. 51-65
|
10.5170/CERN-2016-001.51
| null |
physics.acc-ph
|
http://creativecommons.org/licenses/by/4.0/
|
These notes are intended to provide a brief primer in plasma physics,
introducing common definitions, basic properties, and typical processes found
in plasmas. These concepts are inherent in contemporary plasma-based
accelerator schemes, and thus provide a foundation for the more advanced
expositions that follow in this volume. No prior knowledge of plasma physics is
required, but the reader is assumed to be familiar with basic electrodynamics
and fluid mechanics.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.714236
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10534
|
Scientific Information Service CERN
|
Z. Najmudin
|
Laser Wakefield Accelerators
|
10 pages, contribution to the CAS - CERN Accelerator School: Plasma
Wake Acceleration, CERN, Geneva, Switzerland, 23 - 29 Nov 2014
|
CERN Yellow Report CERN 2016-001, pp.109-118
|
10.5170/CERN-2016-001.109
| null |
physics.acc-ph physics.plasm-ph
|
http://creativecommons.org/licenses/by/4.0/
|
The one-dimensional wakefield generation equations are solved for increasing
levels of non-linearity, to demonstrate how they contribute to the overall
behaviour of a non-linear wakefield in a plasma. The effect of laser guiding is
also studied as a way to increase the interaction length of a laser wakefield
accelerator.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.70964
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10535
|
Scientific Information Service CERN
|
R. Bingham and R. Trines
|
Introduction to Plasma Accelerators: the Basics
|
11 pages, Contribution to the CAS - CERN Accelerator School: Plasma
Wake Acceleration, CERN, Geneva, Switzerland, 23 - 29 Nov 2014
|
CERN Yellow Report CERN 2016-001, pp. 67-77
|
10.5170/CERN-2016-001.67
| null |
physics.acc-ph physics.plasm-ph
|
http://creativecommons.org/licenses/by/4.0/
|
In this article, we concentrate on the basic physics of relativistic plasma
wave accelerators. The generation of relativistic plasma waves by intense
lasers or electron beams in low-density plasmas is important in the quest for
producing ultra-high acceleration gradients for accelerators. A number of
methods are being pursued vigorously to achieve ultra-high acceleration
gradients using various plasma wave drivers; these include wakefield
accelerators driven by photon, electron, and ion beams. We describe the basic
equations and show how intense beams can generate a large-amplitude
relativistic plasma wave capable of accelerating particles to high energies. We
also demonstrate how these same relativistic electron waves can accelerate
photons in plasmas.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.71278
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10537
|
Scientific Information Service CERN
|
P. Muggli
|
Beam-driven, Plasma-based Particle Accelerators
|
24 pages, contribution to the CAS - CERN Accelerator School: Plasma
Wake Acceleration, CERN, Geneva, Switzerland, 23 - 29 Nov 2014
|
CERN Yellow Report CERN 2016-001, pp.119-142
|
10.5170/CERN-2016-001.119
| null |
physics.acc-ph physics.plasm-ph
|
http://creativecommons.org/licenses/by/4.0/
|
We briefly give some of the characteristics of the beam-driven, plasma-based
particle accelerator known as the plasma wakefield accelerator (PWFA). We also
mention some of the major results that have been obtained since the birth of
the concept. We focus on high-energy particle beams where possible.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.715012
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10542
|
Scientific Information Service CERN
|
J. Faure
|
Plasma Injection Schemes for Laser-Plasma Accelerators
|
15 pages, contribution to the CAS - CERN Accelerator School: Plasma
Wake Acceleration, CERN, Geneva, Switzerland, 23 - 29 Nov 2014
|
CERN Yellow Report CERN 2016-001, pp.143-157
|
10.5170/CERN-2016-001.143
| null |
physics.acc-ph physics.plasm-ph
|
http://creativecommons.org/licenses/by/4.0/
|
Plasma injection schemes are crucial for producing high-quality electron
beams in laser-plasma accelerators. This article introduces the general
concepts of plasma injection. First, a Hamiltonian model for particle trapping
and acceleration in plasma waves is introduced; ionization injection and
colliding-pulse injection are described in the framework of this Hamiltonian
model. We then proceed to consider injection in plasma density gradients.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.712835
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10546
|
Hamed R. Tavakoli
|
Hamed R. Tavakoli, Fawad Ahmed, Ali Borji, Jorma Laaksonen
|
Saliency Revisited: Analysis of Mouse Movements versus Fixations
| null | null | null | null |
cs.CV
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
This paper revisits visual saliency prediction by evaluating the recent
advancements in this field such as crowd-sourced mouse tracking-based databases
and contextual annotations. We pursue a critical and quantitative approach
towards some of the new challenges including the quality of mouse tracking
versus eye tracking for model training and evaluation. We extend quantitative
evaluation of models in order to incorporate contextual information by
proposing an evaluation methodology that allows accounting for contextual
factors such as text, faces, and object attributes. The proposed contextual
evaluation scheme facilitates detailed analysis of models and helps identify
their pros and cons. Through several experiments, we find that (1) mouse
tracking data has lower inter-participant visual congruency and higher
dispersion, compared to the eye tracking data, (2) mouse tracking data does not
totally agree with eye tracking in general and in terms of different contextual
regions in specific, and (3) mouse tracking data leads to acceptable results in
training current existing models, and (4) mouse tracking data is less reliable
for model selection and evaluation. The contextual evaluation also reveals
that, among the studied models, there is no single model that performs best on
all the tested annotations.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.710621
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10552
|
Longquan Dai
|
Longquan Dai
|
Interpreting and Extending The Guided Filter Via Cyclic Coordinate
Descent
| null | null | null | null |
cs.CV
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In this paper, we will disclose that the Guided Filter (GF) can be
interpreted as the Cyclic Coordinate Descent (CCD) solver of a Least Square
(LS) objective function. This discovery implies a possible way to extend GF
because we can alter the objective function of GF and define new filters as the
first pass iteration of the CCD solver of modified objective functions.
Moreover, referring to the iterative minimizing procedure of CCD, we can derive
new rolling filtering schemes. Hence, under the guidance of this discovery, we
not only propose new GF-like filters adapting to the specific requirements of
applications but also offer thoroughly explanations for two rolling filtering
schemes of GF as well as the way to extend them. Experiments show that our new
filters and extensions produce state-of-the-art results.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711905
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10557
|
John Aslanides
|
John Aslanides, Jan Leike, Marcus Hutter
|
Universal Reinforcement Learning Algorithms: Survey and Experiments
|
8 pages, 6 figures, Twenty-sixth International Joint Conference on
Artificial Intelligence (IJCAI-17)
| null | null | null |
cs.AI
|
http://creativecommons.org/licenses/by/4.0/
|
Many state-of-the-art reinforcement learning (RL) algorithms typically assume
that the environment is an ergodic Markov Decision Process (MDP). In contrast,
the field of universal reinforcement learning (URL) is concerned with
algorithms that make as few assumptions as possible about the environment. The
universal Bayesian agent AIXI and a family of related URL algorithms have been
developed in this setting. While numerous theoretical optimality results have
been proven for these agents, there has been no empirical investigation of
their behavior to date. We present a short and accessible survey of these URL
algorithms under a unified notation and framework, along with results of some
experiments that qualitatively illustrate some properties of the resulting
policies, and their relative performance on partially-observable gridworld
environments. We also present an open-source reference implementation of the
algorithms which we hope will facilitate further understanding of, and
experimentation with, these ideas.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711575
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10564
|
Scientific Information Service CERN
|
M. Ferrario
|
Injection, Extraction and Matching
|
21 pages, contribution to the CAS - CERN Accelerator School: Plasma
Wake Acceleration, CERN, Geneva, Switzerland, 23 - 29 Nov 2014
|
CERN Yellow Report CERN 2016-001, pp.159-179
|
10.5170/CERN-2016-001.159
| null |
physics.acc-ph
|
http://creativecommons.org/licenses/by/4.0/
|
In this lecture we introduce from basic principles the main concepts of beam
focusing and transport in modern accelerators using the beam envelope
equationas a convenient mathematical tool. Matching conditions suitable for
preserving beam quality are derived from the model for significant beam
dynamics regimes. An extension of the model to the case of plasma accelerators
is introduced. The understanding of similarities and differences with respect
to traditionalaccelerators is also emphasized.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711376
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10566
|
Scientific Information Service CERN
|
B. Cros
|
Laser-driven Plasma Wakefield: Propagation Effects
|
24 pages, contribution to the CAS - CERN Accelerator School: Plasma
Wake Acceleration, CERN, Geneva, Switzerland, 23 - 29 Nov 2014
|
CERN Yellow Report CERN 2016-001, pp.207-230
|
10.5170/CERN-2016-001.207
| null |
physics.acc-ph physics.plasm-ph
|
http://creativecommons.org/licenses/by/4.0/
|
In the frame of laser-driven wakefield acceleration, the main characteristics
oflaser propagation and plasma wave excitation are described, with an emphasis
onthe role of propagation distance for electron acceleration. To
optimizeinteraction length and maximize energy gain, operation at low plasma
density isthe most promising regime for achieving ultra-relativistic energies.
Among thepossible methods of extending propagation length at low plasma
density, laserguiding by grazing incidence reflection at the wall of dielectric
capillarytubes has several assets. The properties of laser guiding and the
measurement ofplasma waves over long distances are presented.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711112
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10569
|
Scientific Information Service CERN
|
M. Roth and M. Schollmeier
|
Ion Acceleration - Target Normal Sheath Acceleration
|
40 pages, contribution to the CAS - CERN Accelerator School: Plasma
Wake Acceleration, CERN, Geneva, Switzerland, 23 - 29 Nov 2014
|
CERN Yellow Report CERN 2016-001, pp. 231-270
|
10.5170/CERN-2016-001.231
| null |
physics.acc-ph physics.plasm-ph
|
http://creativecommons.org/licenses/by/4.0/
|
Energetic ions have been observed since the very first laser-plasma
experiments.Their origin was found to be the charge separation of electrons
heated by thelaser, which transfers energy to the ions accelerated in the
field. The adventof ultra-intense lasers with pulse lengths in the femtosecond
regime resulted inthe discovery of very energetic ions with characteristics
quite different fromthose driven by long-pulse lasers. Discovered in the late
1990s, these ion beamshave become the focus of intense research worldwide,
because of their uniqueproperties and high particle numbers. Based on their
non-isotropic, beam-likebehaviour, which is always perpendicular to the
emitting surface, theacceleration mechanism is called target normal sheath
acceleration (TNSA). Weaddress the physics of the mechanism and its dependence
on laser and targetparameters. Techniques to explore and diagnose the beams, to
make them usefulfor applications, are also addressed.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.714003
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10573
|
Scientific Information Service CERN
|
E. Gschwendtner
|
AWAKE, A Particle-driven Plasma Wakefield Acceleration Experiment
|
18 pages, contribution to the CAS - CERN Accelerator School: Plasma
Wake Acceleration, CERN, Geneva, Switzerland, 23 - 29 Nov 2014
|
CERN Yellow Report CERN 2016-001, pp.271-288
|
10.5170/CERN-2016-001.271
| null |
physics.acc-ph
|
http://creativecommons.org/licenses/by/4.0/
|
The Advanced Proton Driven Plasma Wakefield Acceleration Experiment (AWAKE)
aims at studying plasma wakefield generation and electron acceleration driven
by proton bunches. It is a proof-of-principle R&D experiment at CERN and the
world's first proton driven plasma wakefield acceleration experiment. The AWAKE
experiment will be installed in the former CNGS facility and uses the 400 GeV/c
proton beam bunches from the SPS. The first experiments will focus on the
self-modulation instability of the long (r.m.s ~12 cm) proton bunch in the
plasma. These experiments are planned for the end of 2016. Later, in 2017/2018,
low energy (~15 MeV) electrons will be externally injected to sample the
wakefields and be accelerated beyond 1 GeV.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.708956
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10579
|
Stefano Dafarra
|
Stefano Dafarra, Francesco Romano and Francesco Nori
|
Torque-Controlled Stepping-Strategy Push Recovery: Design and
Implementation on the iCub Humanoid Robot
| null | null |
10.1109/HUMANOIDS.2016.7803271
| null |
cs.RO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
One of the challenges for the robotics community is to deploy robots which
can reliably operate in real world scenarios together with humans. A crucial
requirement for legged robots is the capability to properly balance on their
feet, rejecting external disturbances. iCub is a state-of-the-art humanoid
robot which has only recently started to balance on its feet. While the current
balancing controller has proved successful in various scenarios, it still
misses the capability to properly react to strong pushes by taking steps. This
paper goes in this direction. It proposes and implements a control strategy
based on the Capture Point concept [1]. Instead of relying on position control,
like most of Capture Point related approaches, the proposed strategy generates
references for the momentum-based torque controller already implemented on the
iCub, thus extending its capabilities to react to external disturbances, while
retaining the advantages of torque control when interacting with the
environment. Experiments in the Gazebo simulator and on the iCub humanoid robot
validate the proposed strategy.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.706458
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10583
|
Soumyabrata Dev
|
Soumyabrata Dev, Florian M. Savoy, Yee Hui Lee, Stefan Winkler
|
Nighttime sky/cloud image segmentation
|
Accepted in Proc. IEEE International Conference on Image Processing
(ICIP), 2017
| null | null | null |
cs.CV
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Imaging the atmosphere using ground-based sky cameras is a popular approach
to study various atmospheric phenomena. However, it usually focuses on the
daytime. Nighttime sky/cloud images are darker and noisier, and thus harder to
analyze. An accurate segmentation of sky/cloud images is already challenging
because of the clouds' non-rigid structure and size, and the lower and less
stable illumination of the night sky increases the difficulty. Nonetheless,
nighttime cloud imaging is essential in certain applications, such as
continuous weather analysis and satellite communication.
In this paper, we propose a superpixel-based method to segment nighttime
sky/cloud images. We also release the first nighttime sky/cloud image
segmentation database to the research community. The experimental results show
the efficacy of our proposed algorithm for nighttime images.
| 2017-05-31T00:00:00
|
new_dataset
| true
| 0.702475
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10586
|
Zhenzhou Wu
|
Zhenzhou Wu and Xin Zheng and Daniel Dahlmeier
|
Character-Based Text Classification using Top Down Semantic Model for
Sentence Representation
| null | null | null | null |
cs.CL cs.LG
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Despite the success of deep learning on many fronts especially image and
speech, its application in text classification often is still not as good as a
simple linear SVM on n-gram TF-IDF representation especially for smaller
datasets. Deep learning tends to emphasize on sentence level semantics when
learning a representation with models like recurrent neural network or
recursive neural network, however from the success of TF-IDF representation, it
seems a bag-of-words type of representation has its strength. Taking advantage
of both representions, we present a model known as TDSM (Top Down Semantic
Model) for extracting a sentence representation that considers both the
word-level semantics by linearly combining the words with attention weights and
the sentence-level semantics with BiLSTM and use it on text classification. We
apply the model on characters and our results show that our model is better
than all the other character-based and word-based convolutional neural network
models by \cite{zhang15} across seven different datasets with only 1\% of their
parameters. We also demonstrate that this model beats traditional linear models
on TF-IDF vectors on small and polished datasets like news article in which
typically deep learning models surrender.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.710234
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10588
|
Scientific Information Service CERN
|
S.P.D. Mangles
|
An Overview of Recent Progress in Laser Wakefield Acceleration
Experiments
|
12 pages, contribution to the CAS - CERN Accelerator School: Plasma
Wake Acceleration, CERN, Geneva, Switzerland, 23 - 29 Nov 2014
|
CERN Yellow Report CERN 2016-001, pp.289-300
|
10.5170/CERN-2016-001.289
| null |
physics.acc-ph physics.plasm-ph
|
http://creativecommons.org/licenses/by/4.0/
|
The goal of this paper is to examine experimental progress in laser wakefield
acceleration over the past decade (2004-2014), and to use trends in the data to
understand some of the important physical processes. By examining a set of over
50 experiments, various trends concerning the relationship between plasma
density, accelerator length, laser power and the final electron beam en- ergy
are revealed. The data suggest that current experiments are limited by
dephasing and that current experiments typically require some pulse evolution
to reach the trapping threshold.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.713619
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10589
|
James P. Sethna
|
Lorien X. Hayden, Alexander A. Alemi, Paul H. Ginsparg, James P.
Sethna
|
Jeffrey's prior sampling of deep sigmoidal networks
| null | null | null | null |
cond-mat.dis-nn cs.CV
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Neural networks have been shown to have a remarkable ability to uncover low
dimensional structure in data: the space of possible reconstructed images form
a reduced model manifold in image space. We explore this idea directly by
analyzing the manifold learned by Deep Belief Networks and Stacked Denoising
Autoencoders using Monte Carlo sampling. The model manifold forms an only
slightly elongated hyperball with actual reconstructed data appearing
predominantly on the boundaries of the manifold. In connection with the results
we present, we discuss problems of sampling high-dimensional manifolds as well
as recent work [M. Transtrum, G. Hart, and P. Qiu, Submitted (2014)] discussing
the relation between high dimensional geometry and model reduction.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.712829
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10591
|
X. Sharon Hu
|
Xiaoming Chen, Jianxu Chen, Danny Z. Chen, and Xiaobo Sharon Hu
|
Optimizing Memory Efficiency for Convolution Kernels on Kepler GPUs
| null | null | null | null |
cs.DC cs.LG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Convolution is a fundamental operation in many applications, such as computer
vision, natural language processing, image processing, etc. Recent successes of
convolutional neural networks in various deep learning applications put even
higher demand on fast convolution. The high computation throughput and memory
bandwidth of graphics processing units (GPUs) make GPUs a natural choice for
accelerating convolution operations. However, maximally exploiting the
available memory bandwidth of GPUs for convolution is a challenging task. This
paper introduces a general model to address the mismatch between the memory
bank width of GPUs and computation data width of threads. Based on this model,
we develop two convolution kernels, one for the general case and the other for
a special case with one input channel. By carefully optimizing memory access
patterns and computation patterns, we design a communication-optimized kernel
for the special case and a communication-reduced kernel for the general case.
Experimental data based on implementations on Kepler GPUs show that our kernels
achieve 5.16X and 35.5% average performance improvement over the latest cuDNN
library, for the special case and the general case, respectively.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.713996
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10595
|
Christopher Portmann
|
Christopher Portmann
|
(Quantum) Min-Entropy Resources
|
39+18 pages, 11 figures
| null | null | null |
quant-ph cs.CR cs.IT math.IT
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We model (interactive) resources that provide Alice with a string $X$ and a
guarantee that any Eve interacting with her interface of the resource obtains a
(quantum) system $E$ such that the conditional (smooth) min-entropy of $X$
given $E$ is lower bounded by some $k$. This (abstract) resource specification
encompasses any setting that results in the honest players holding such a
string (or aborting). For example, it could be constructed from, e.g., noisy
channels, quantum key distribution (QKD), or a violation of Bell inequalities,
which all may be used to derive bounds on the min-entropy of $X$.
As a first application, we use this min-entropy resource to modularize key
distribution (KD) schemes by dividing them in two parts, which may be analyzed
separately. In the first part, a KD protocol constructs a min-entropy resource
given the (physical) resources available in the specific setting considered. In
the second, it distills secret key from the min-entropy resource---i.e., it
constructs a secret key resource. We prove security for a generic key
distillation protocol that may use any min-entropy resource. Since the notion
of resource construction is composable---security of a composed protocol
follows from the security of its parts--- this reduces proving security of a KD
protocol (e.g., QKD) to proving that it constructs a min-entropy resource.
As a second application, we provide a composable security proof for the
recent Fehr-Salvail protocol [EUROCRYPT 2017] that authenticates classical
messages with a quantum message authentication code (Q-MAC), and recycles all
the key upon successfully verifying the authenticity of the message. This
protocol uses (and recycles) a non-uniform key, which we model as consuming and
constructing a min-entropy resource.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709074
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10596
|
Zhulin Liu
|
Zhulin Liu and C. L. Philip Chen
|
Approximation learning methods of Harmonic Mappings in relation to Hardy
Spaces
|
2016 3rd International Conference on Informative and Cybernetics for
Computational Social Systems (ICCSS)
| null |
10.1109/ICCSS.2016.7586421
| null |
math.NA cs.LG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
A new Hardy space Hardy space approach of Dirichlet type problem based on
Tikhonov regularization and Reproducing Hilbert kernel space is discussed in
this paper, which turns out to be a typical extremal problem located on the
upper upper-high complex plane. If considering this in the Hardy space, the
optimization operator of this problem will be highly simplified and an
efficient algorithm is possible. This is mainly realized by the help of
reproducing properties of the functions in the Hardy space of upper-high
complex plane, and the detail algorithm is proposed. Moreover, harmonic
mappings, which is a significant geometric transformation, are commonly used in
many applications such as image processing, since it describes the energy
minimization mappings between individual manifolds. Particularly, when we focus
on the planer mappings between two Euclid planer regions, the harmonic mappings
are exist and unique, which is guaranteed solidly by the existence of harmonic
function. This property is attractive and simulation results are shown in this
paper to ensure the capability of applications such as planer shape distortion
and surface registration.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709627
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10608
|
Birte Schmidtmann
|
Birte Schmidtmann, Pawel Buchm\"uller, Manuel Torrilhon
|
Third-order Limiting for Hyperbolic Conservation Laws applied to
Adaptive Mesh Refinement and Non-Uniform 2D Grids
| null | null | null | null |
math.NA cs.NA
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In this paper we extend the recently developed third-order limiter function
$H_{3\text{L}}^{(c)}$ [J. Sci. Comput., (2016), 68(2), pp.~624--652] to make it
applicable for more elaborate test cases in the context of finite volume
schemes. This work covers the generalization to non-uniform grids in one and
two space dimensions, as well as two-dimensional Cartesian grids with adaptive
mesh refinement (AMR). The extension to 2D is obtained by the common approach
of dimensional splitting. In order to apply this technique without loss of
third-order accuracy, the order-fix developed by Buchm\"uller and Helzel [J.
Sci. Comput., (2014), 61(2), pp.~343--368] is incorporated into the scheme.
Several numerical examples on different grid configurations show that the
limiter function $H_{3\text{L}}^{(c)}$ maintains the optimal third-order
accuracy on smooth profiles and avoids oscillations in case of discontinuous
solutions.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.710979
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10614
|
Mahesh Babu Vaddi
|
Mahesh Babu Vaddi and B. Sundar Rajan
|
Near-Optimal Vector Linear Index Codes For Single Unicast Index Coding
Problems with Symmetric Neighboring Interference
|
14 pages, 8 figures and 3 tables. arXiv admin note: substantial text
overlap with arXiv:1705.05060, arXiv:1705.03192
| null | null | null |
cs.IT math.IT
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
A single unicast index coding problem (SUICP) with symmetric neighboring
interference (SNI) has equal number of $K$ messages and $K$ receivers, the
$k$th receiver $R_{k}$ wanting the $k$th message $x_{k}$ and having the
side-information $\mathcal{K}_{k}=(\mathcal{I}_{k} \cup x_{k})^c,$ where
${I}_k= \{x_{k-U},\dots,x_{k-2},x_{k-1}\}\cup\{x_{k+1},
x_{k+2},\dots,x_{k+D}\}$ is the interference with $D$ messages after and $U$
messages before its desired message. Maleki, Cadambe and Jafar obtained the
capacity of this single unicast index coding problem with symmetric neighboring
interference (SUICP-SNI) with $K$ tending to infinity and Blasiak, Kleinberg
and Lubetzky for the special case of $(D=U=1)$ with $K$ being finite. In our
previous work, we proved the capacity of SUICP-SNI for arbitrary $K$ and $D$
with $U=\text{gcd}(K,D+1)-1$. This paper deals with near-optimal linear code
construction for SUICP-SNI with arbitrary $K,U$ and $D.$ For SUICP-SNI with
arbitrary $K,U$ and $D$, we define a set of $2$-tuples such that for every
$(a,b)$ in that set the rate $D+1+\frac{a}{b}$ is achieved by using vector
linear index codes over every field. We prove that the set
$\mathcal{\mathbf{S}}$ consists of $(a,b)$ such that the rate of constructed
vector linear index codes are at most $\frac{K~\text{mod}~(D+1)}{\left \lfloor
\frac{K}{D+1} \right \rfloor}$ away from a known lower bound on broadcast rate
of SUICP-SNI. The three known results on the exact capacity of the SUICP-SNI
are recovered as special cases of our results. Also, we give a low complexity
decoding procedure for the proposed vector linear index codes for the
SUICP-SNI.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.704647
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10618
|
Lu-Xing Yang
|
Lu-Xing Yang, Tianrui Zhang, Xiaofan Yang, Yingbo Wu, Yuan Yan Tang
|
On the effectiveness of the truth-spreading/rumor-blocking strategy for
restraining rumors
|
rumor spreading, truth-spreading/rumor-blocking strategy,
effectiveness, individual-level spreading model, qualitative analysis of
dynamical system, network structure. arXiv admin note: substantial text
overlap with arXiv:1705.06604; text overlap with arXiv:1705.04818
| null | null | null |
cs.SI
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Spreading truths and blocking rumors are two typical strategies for
inhibiting rumors. In practice, a tradeoff between the two strategies, which is
known as the TSRB strategy, may achieve a better cost-effectiveness. This paper
is devoted to assessing the effectiveness of the TSRB strategy. For that
purpose, an individual-level spreading model (the generic URQT model) capturing
the interaction between a rumor and the truth is established. Under the model,
a set of criteria for the dying out of a rumor is presented. These criteria
capture the combined influence of the basic parameters and the network
structures on the effectiveness of the TSRB strategy. Experimental results show
that, when the rumor dies out, the dynamics of a simplified URQT model (the
linear URQT model) fits well with the actual rumor-truth interacting process.
Therefore, the generic URQT model and sometimes the linear URQT model provide a
proper basis for assessing the effectiveness of the TSRB strategy.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.710626
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10622
|
Didier Clamond
|
Didier Clamond (JAD)
|
Remarks on bernoulli constants, gauge conditions and phase velocities in
the context of water waves
| null | null | null | null |
physics.flu-dyn physics.class-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
This short note is about the gauge condition for the velocity potential, the
definitions of the Bernoulli constant and of the velocity speeds in the context
of water waves. These definitions are often implicit and thus the source of
confusion in the literature. This
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.714625
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10624
|
Maksim Skorobogatiy
|
Kathirvel Nallappan, Jingwen Li, Hichem Guerboukha, Andrey Markov,
Branko Petrov, Denis Morris and Maksim Skorobogatiy
|
A Dynamically Reconfigurable Terahertz Array Antenna for Near-field
Imaging Applications
| null | null | null | null |
physics.optics physics.ins-det
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
A proof of concept for high speed near-field imaging with sub-wavelength
resolution using SLM is presented. An 8 channel THz detector array antenna with
an electrode gap of 100 um and length of 5 mm is fabricated using the
commercially available GaAs semiconductor substrate. Each array antenna can be
excited simultaneously by spatially reconfiguring the optical probe beam and
the THz electric field can be recorded using 8 channel lock-in amplifiers. By
scanning the probe beam along the length of the array antenna, a 2D image can
be obtained with amplitude, phase and frequency information.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.707317
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10625
|
Cl\'ement Miklarz
|
Pascal Caron, Ludovic Mignot, Cl\'ement Miklarz
|
On the decidability of $k$-Block determinism
|
15 pages, 13 figures, Submitted to Information and Computation,
Continuing arXiv:1512.05475
| null | null | null |
cs.FL
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Br\"uggemann-Klein and Wood define a one-unambiguous regular language as a
language that can be recognized by a deterministic Glushkov automaton. They
give a procedure performed on the minimal DFA, the BW-test, to decide whether a
language is one-unambiguous. Block determinism is an extension of
one-unambiguity while considering non-empty words as symbols and
prefix-freeness as determinism. A block automaton is compact if it does not
have two equivalent states (same right language). We showed that a language is
$k$-block deterministic if it is recognized by some deterministic $k$-block
automaton passing the BW-test. In this paper, we show that any $k$-block
deterministic language is recognized by a compact deterministic $k$-block
automaton passing the BW-test. We also give a procedure which enumerates, for a
given language, the finite set of compact deterministic $k$-block automata. It
gives us a decidable procedure to test whether a language is $k$-block
deterministic.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.708602
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10630
|
Hemani Kaushal Dr.
|
Hemani Kaushal and Georges Kaddoum
|
Optical Communication in Space: Challenges and Mitigation Techniques
|
41 pages, 13 Figures and 8 Tables. arXiv admin note: substantial text
overlap with arXiv:1506.04836
|
IEEE Communications Surveys & Tutorials ( Volume: 19, Issue: 1,
Firstquarter 2017 ), pp. 57-96, 2016
|
10.1109/COMST.2016.2603518
| null |
cs.IT math.IT
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In recent years, free space optical communication has gained significant
importance owing to its unique features: large bandwidth, license-free
spectrum, high data rate, easy and quick deployability, less power and low mass
requirements. FSO communication uses the optical carrier in the near infrared
band to establish either terrestrial links within the Earth's atmosphere or
inter-satellite or deep space links or ground-to-satellite or
satellite-to-ground links. However, despite the great potential of FSO
communication, its performance is limited by the adverse effects viz.,
absorption, scattering, and turbulence of the atmospheric channel. This paper
presents a comprehensive survey on various challenges faced by FSO
communication system for ground-to-satellite or satellite-to-ground and
inter-satellite links. It also provides details of various performance
mitigation techniques in order to have high link availability and reliability.
The first part of the paper will focus on various types of impairments that
pose a serious challenge to the performance of optical communication system for
ground-to-satellite or satellite-to-ground and inter-satellite links. The
latter part of the paper will provide the reader with an exhaustive review of
various techniques both at physical layer as well as at the other layers i.e.,
link, network or transport layer to combat the adverse effects of the
atmosphere. It also uniquely presents a recently developed technique using
orbital angular momentum for utilizing the high capacity advantage of the
optical carrier in case of space-based and near-Earth optical communication
links. This survey provides the reader with comprehensive details on the use of
space-based optical backhaul links in order to provide high-capacity and
low-cost backhaul solutions.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.712242
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10633
|
Tom Vander Aa
|
Tom Vander Aa, Imen Chakroun and Tom Haber
|
Distributed Matrix Factorization using Asynchrounous Communication
|
arXiv admin note: substantial text overlap with arXiv:1705.04159
| null |
10.1016/j.procs.2017.05.009
| null |
cs.DC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Using the matrix factorization technique in machine learning is very common
mainly in areas like recommender systems. Despite its high prediction accuracy
and its ability to avoid over-fitting of the data, the Bayesian Probabilistic
Matrix Factorization algorithm (BPMF) has not been widely used on large scale
data because of the prohibitive cost. In this paper, we propose a distributed
high-performance parallel implementation of the BPMF using Gibbs sampling on
shared and distributed architectures. We show by using efficient load balancing
using work stealing on a single node, and by using asynchronous communication
in the distributed version we beat state of the art implementations.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.709693
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10638
|
Stefano Dafarra
|
Stefano Dafarra, Francesco Romano and Francesco Nori
|
A Receding Horizon Push Recovery Strategy for Balancing the iCub
Humanoid Robot
| null | null | null | null |
cs.RO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Balancing and reacting to strong and unexpected pushes is a critical
requirement for humanoid robots. We recently designed a capture point based
approach which interfaces with a momentum-based torque controller and we
implemented and validated it on the iCub humanoid robot. In this work we
implement a Receding Horizon control, also known as Model Predictive Control,
to add the possibility to predict the future evolution of the robot, especially
the constraints switching given by the hybrid nature of the system. We prove
that the proposed MPC extension makes the step-recovery controller more robust
and reliable when executing the recovery strategy. Experiments in simulation
show the results of the proposed approach.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.710353
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10639
|
Rick Smetsers
|
Rick Smetsers
|
Grammatical Inference as a Satisfiability Modulo Theories Problem
|
Submitted and selected for oral presentation at the LearnAut workshop
at LICS 2017
| null | null | null |
cs.FL cs.LG cs.LO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The problem of learning a minimal consistent model from a set of labeled
sequences of symbols is addressed from a satisfiability modulo theories
perspective. We present two encodings for deterministic finite automata and
extend one of these for Moore and Mealy machines. Our experimental results show
that these encodings improve upon the state-of-the-art, and are useful in
practice for learning small models.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.704124
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10640
|
Jordan Hachtel
|
Jordan A. Hachtel, Sang Yeon Cho, Roderick B. Davidson II, Matthew F.
Chisholm, Richard F. Haglund, Juan Carlos Idrobo, Sokrates T. Pantelides,
Benjamin J. Lawrie
|
Spatially and spectrally resolved orbital angular momentum interactions
in plasmonic vortex generators
| null | null | null | null |
physics.optics
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Understanding the near-field electromagnetic interactions that produce
optical orbital angular momentum (OAM) is central to the integration of twisted
light into nanotechnology. Here, we examine the cathodoluminescence (CL) of
plasmonic vortices carrying OAM generated in spiral nanostructures through
scanning transmission electron microscopy (STEM). The nanospiral geometry
defines the photonic local density of states (LDOS) sampled by STEM-CL, which
provides access to the phase and amplitude of the plasmonic vortex with
nanometer spatial and meV spectral resolution. We map the full spectral
dispersion of the plasmonic vortex in the spiral structure and examine the
effects of increasing topological charge on the plasmon phase and amplitude in
the detected CL signal. The vortex is mapped in CL over a broad spectral range,
and deviations between the predicted and detected positions of near-field
optical signatures of as much as 5 per cent are observed. Finally, enhanced
luminescence is observed from concentric spirals of like handedness compared to
that from concentric spirals of opposite handedness, indicating the potential
to couple plasmonic vortices to chiral nanostructures for sensitive detection
and manipulation of optical OAM.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711189
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10649
|
Vincent Neiger
|
Vincent Neiger, Thi Xuan Vu
|
Computing Canonical Bases of Modules of Univariate Relations
|
8 pages, uses acmart sigconf
| null |
10.1145/3087604.3087656
| null |
cs.SC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We study the computation of canonical bases of sets of univariate relations
$(p_1,\ldots,p_m) \in \mathbb{K}[x]^{m}$ such that $p_1 f_1 + \cdots + p_m f_m
= 0$; here, the input elements $f_1,\ldots,f_m$ are from a quotient
$\mathbb{K}[x]^n/\mathcal{M}$, where $\mathcal{M}$ is a $\mathbb{K}[x]$-module
of rank $n$ given by a basis $\mathbf{M}\in\mathbb{K}[x]^{n\times n}$ in
Hermite form. We exploit the triangular shape of $\mathbf{M}$ to generalize a
divide-and-conquer approach which originates from fast minimal approximant
basis algorithms. Besides recent techniques for this approach, we rely on
high-order lifting to perform fast modular products of polynomial matrices of
the form $\mathbf{P}\mathbf{F} \bmod \mathbf{M}$.
Our algorithm uses $O\tilde{~}(m^{\omega-1}D + n^{\omega} D/m)$ operations in
$\mathbb{K}$, where $D = \mathrm{deg}(\det(\mathbf{M}))$ is the
$\mathbb{K}$-vector space dimension of $\mathbb{K}[x]^n/\mathcal{M}$,
$O\tilde{~}(\cdot)$ indicates that logarithmic factors are omitted, and
$\omega$ is the exponent of matrix multiplication. This had previously only
been achieved for a diagonal matrix $\mathbf{M}$. Furthermore, our algorithm
can be used to compute the shifted Popov form of a nonsingular matrix within
the same cost bound, up to logarithmic factors, as the previously fastest known
algorithm, which is randomized.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.704637
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10654
|
Mahmood Mamivand
|
Mahmood Mamivand, Ying Yang, Jeremy Busby, Dane Morgan
|
Integrated Modeling of Second Phase Precipitation in Cold-Worked 316
Stainless Steels under Irradiation
| null |
Acta Materialia, Volume 130, 15 May 2017, Pages 94 to 110
| null | null |
cond-mat.mtrl-sci physics.app-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The current work combines the Cluster Dynamics (CD) technique and
CALPHAD-based precipitation modeling to address the second phase precipitation
in cold-worked (CW) 316 stainless steels (SS) under irradiation at 300-400 C.
CD provides the radiation enhanced diffusion and dislocation evolution as
inputs for the precipitation model. The CALPHAD-based precipitation model
treats the nucleation, growth and coarsening of precipitation processes based
on classical nucleation theory and evolution equations, and simulates the
composition, size and size distribution of precipitate phases. We benchmark the
model against available experimental data at fast reactor conditions (9.4 x
10^-7 dpa/s and 390 C) and then use the model to predict the phase instability
of CW 316 SS under light water reactor (LWR) extended life conditions (7 x
10^-8 dpa/s and 275 C). The model accurately predicts the gamma-prime (Ni3Si)
precipitation evolution under fast reactor conditions and that the formation of
this phase is dominated by radiation enhanced segregation. The model also
predicts a carbide volume fraction that agrees well with available experimental
data from a PWR reactor but is much higher than the volume fraction observed in
fast reactors. We propose that radiation enhanced dissolution and/or carbon
depletion at sinks that occurs at high flux could be the main sources of this
inconsistency. The integrated model predicts ~1.2% volume fraction for carbide
and ~3.0% volume fraction for gamma-prime for typical CW 316 SS (with 0.054
wt.% carbon) under LWR extended life conditions. This work provides valuable
insights into the magnitudes and mechanisms of precipitation in irradiated CW
316 SS for nuclear applications.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.710848
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10658
|
Vincent Neiger
|
Vincent Neiger, Johan Rosenkilde, Eric Schost
|
Fast Computation of the Roots of Polynomials Over the Ring of Power
Series
|
8 pages, uses acmart sigconf
| null |
10.1145/3087604.3087642
| null |
cs.SC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We give an algorithm for computing all roots of polynomials over a univariate
power series ring over an exact field $\mathbb{K}$. More precisely, given a
precision $d$, and a polynomial $Q$ whose coefficients are power series in $x$,
the algorithm computes a representation of all power series $f(x)$ such that
$Q(f(x)) = 0 \bmod x^d$. The algorithm works unconditionally, in particular
also with multiple roots, where Newton iteration fails. Our main motivation
comes from coding theory where instances of this problem arise and multiple
roots must be handled.
The cost bound for our algorithm matches the worst-case input and output size
$d \deg(Q)$, up to logarithmic factors. This improves upon previous algorithms
which were quadratic in at least one of $d$ and $\deg(Q)$. Our algorithm is a
refinement of a divide \& conquer algorithm by Alekhnovich (2005), where the
cost of recursive steps is better controlled via the computation of a factor of
$Q$ which has a smaller degree while preserving the roots.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.705299
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10659
|
Xiatian Zhu
|
Jingya Wang, Xiatian Zhu, Shaogang Gong
|
Discovering Visual Concept Structure with Sparse and Incomplete Tags
|
Artificial Intelligence journal 2017
| null | null | null |
cs.CV
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Discovering automatically the semantic structure of tagged visual data (e.g.
web videos and images) is important for visual data analysis and
interpretation, enabling the machine intelligence for effectively processing
the fast-growing amount of multi-media data. However, this is non-trivial due
to the need for jointly learning underlying correlations between heterogeneous
visual and tag data. The task is made more challenging by inherently sparse and
incomplete tags. In this work, we develop a method for modelling the inherent
visual data concept structures based on a novel Hierarchical-Multi-Label Random
Forest model capable of correlating structured visual and tag information so as
to more accurately interpret the visual semantics, e.g. disclosing meaningful
visual groups with similar high-level concepts, and recovering missing tags for
individual visual data samples. Specifically, our model exploits hierarchically
structured tags of different semantic abstractness and multiple tag statistical
correlations in addition to modelling visual and tag interactions. As a result,
our model is able to discover more accurate semantic correlation between
textual tags and visual features, and finally providing favourable visual
semantics interpretation even with highly sparse and incomplete tags. We
demonstrate the advantages of our proposed approach in two fundamental
applications, visual data clustering and missing tag completion, on
benchmarking video (i.e. TRECVID MED 2011) and image (i.e. NUS-WIDE) datasets.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711108
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
1705.10664
|
Jiaji Zhou
|
Jiaji Zhou, J. Andrew Bagnell and Matthew T. Mason
|
A Fast Stochastic Contact Model for Planar Pushing and Grasping: Theory
and Experimental Validation
|
Robotics: Science and Systems 2017
| null | null | null |
cs.RO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Based on the convex force-motion polynomial model for quasi-static sliding,
we derive the kinematic contact model to determine the contact modes and
instantaneous object motion on a supporting surface given a position controlled
manipulator. The inherently stochastic object-to-surface friction distribution
is modelled by sampling physically consistent parameters from appropriate
distributions, with only one parameter to control the amount of noise. Thanks
to the high fidelity and smoothness of convex polynomial models, the mechanics
of patch contact is captured while being computationally efficient without mode
selection at support points. The motion equations for both single and multiple
frictional contacts are given. Simulation based on the model is validated with
robotic pushing and grasping experiments.
| 2017-05-31T00:00:00
|
no_new_dataset
| false
| 0.711686
|
2026-01-25T00:43:33.318544
|
davanstrien/ModernBERT-base-is-new-arxiv-dataset
|
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