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End-to-end semantic face segmentation with conditional random fields as convolutional, recurrent and adversarial networks
Recent years have seen a sharp increase in the number of related yet distinct advances in semantic segmentation. Here, we tackle this problem by leveraging the respective strengths of these advances. That is, we formulate a conditional random field over a four-connected graph as end-to-end trainable convolutional and...
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Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent
Coherent uncertainty quantification is a key strength of Bayesian methods. But modern algorithms for approximate Bayesian posterior inference often sacrifice accurate posterior uncertainty estimation in the pursuit of scalability. This work shows that previous Bayesian coreset construction algorithms---which build a ...
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Practical Bayesian optimization in the presence of outliers
Inference in the presence of outliers is an important field of research as outliers are ubiquitous and may arise across a variety of problems and domains. Bayesian optimization is method that heavily relies on probabilistic inference. This allows outstanding sample efficiency because the probabilistic machinery provi...
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Is there any polynomial upper bound for the universal labeling of graphs?
A {\it universal labeling} of a graph $G$ is a labeling of the edge set in $G$ such that in every orientation $\ell$ of $G$ for every two adjacent vertices $v$ and $u$, the sum of incoming edges of $v$ and $u$ in the oriented graph are different from each other. The {\it universal labeling number} of a graph $G$ is t...
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An Empirical Study on Team Formation in Online Games
Online games provide a rich recording of interactions that can contribute to our understanding of human behavior. One potential lesson is to understand what motivates people to choose their teammates and how their choices leadto performance. We examine several hypotheses about team formation using a large, longitudin...
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Nematic superconductivity in Cu$_{x}$Bi$_{2}$Se$_{3}$: The surface Andreev bound states
We study theoretically the topological surface states (TSSs) and the possible surface Andreev bound states (SABSs) of Cu$_{x}$Bi$_{2}$Se$_{3}$ which is known to be a topological insulator at $x=0$. The superconductivity (SC) pairing of this compound is assumed to have the broken spin-rotation symmetry, similar to tha...
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The structure of a minimal $n$-chart with two crossings II: Neighbourhoods of $Γ_1\cupΓ_{n-1}$
Given a 2-crossing minimal chart $\Gamma$, a minimal chart with two crossings, set $\alpha=\min\{~i~|~$there exists an edge of label $i$ containing a white vertex$\}$, and $\beta=\max\{~i~|~$there exists an edge of label $i$ containing a white vertex$\}$. In this paper we study the structure of a neighbourhood of $\G...
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Generating Shared Latent Variables for Robots to Imitate Human Movements and Understand their Physical Limitations
Assistive robotics and particularly robot coaches may be very helpful for rehabilitation healthcare. In this context, we propose a method based on Gaussian Process Latent Variable Model (GP-LVM) to transfer knowledge between a physiotherapist, a robot coach and a patient. Our model is able to map visual human body fe...
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Superconvergence analysis of linear FEM based on the polynomial preserving recovery and Richardson extrapolation for Helmholtz equation with high wave number
We study superconvergence property of the linear finite element method with the polynomial preserving recovery (PPR) and Richardson extrapolation for the two dimensional Helmholtz equation. The $H^1$-error estimate with explicit dependence on the wave number $k$ {is} derived. First, we prove that under the assumption...
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Semi-blind source separation with multichannel variational autoencoder
This paper proposes a multichannel source separation technique called the multichannel variational autoencoder (MVAE) method, which uses a conditional VAE (CVAE) to model and estimate the power spectrograms of the sources in a mixture. By training the CVAE using the spectrograms of training examples with source-class...
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Quantitative characterization of pore structure of several biochars with 3D imaging
Pore space characteristics of biochars may vary depending on the used raw material and processing technology. Pore structure has significant effects on the water retention properties of biochar amended soils. In this work, several biochars were characterized with three-dimensional imaging and image analysis. X-ray co...
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First-principles-based method for electron localization: Application to monolayer hexagonal boron nitride
We present a first-principles-based many-body typical medium dynamical cluster approximation method for characterizing electron localization in disordered structures. This method applied to monolayer hexagonal boron nitride shows that the presence of a boron vacancies could turn this wide-gap insulator into a correla...
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Compressed H$_3$S: inter-sublattice Coulomb coupling in a high-$\textit{T}$$_C$ superconductor
Upon thermal annealing at or above room temperature (RT) and high pressure $\it P$ $\sim$ 155 GPa, H$_3$S exhibits superconductivity at $\it T_C$ $\sim$ 200 K. Various theoretical frameworks with strong electron-phonon coupling and Coulomb repulsion have reproduced this record-level $\it T_C$. Of particular relevance...
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A physiology--based parametric imaging method for FDG--PET data
Parametric imaging is a compartmental approach that processes nuclear imaging data to estimate the spatial distribution of the kinetic parameters governing tracer flow. The present paper proposes a novel and efficient computational method for parametric imaging which is potentially applicable to several compartmental...
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Item Recommendation with Evolving User Preferences and Experience
Current recommender systems exploit user and item similarities by collaborative filtering. Some advanced methods also consider the temporal evolution of item ratings as a global background process. However, all prior methods disregard the individual evolution of a user's experience level and how this is expressed in ...
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On some integrals of Hardy
We consider some properties of integrals considered by Hardy and Koshliakov, and which have also been further extended recently by Dixit. We establish a new general integral formula from some observations about the digamma function. We also obtain lower and upper bounds for Hardy's integral through properties of the ...
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Complexity of short generating functions
We give complexity analysis of the class of short generating functions (GF). Assuming $\#P \not\subseteq FP/poly$, we show that this class is not closed under taking many intersections, unions or projections of GFs, in the sense that these operations can increase the bitlength of coefficients of GFs by a super-polyno...
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Finite-Size Effects in Non-Neutral Two-Dimensional Coulomb Fluids
Thermodynamic potential of a neutral two-dimensional (2D) Cou\-lomb fluid, confined to a large domain with a smooth boundary, exhibits at any (inverse) temperature $\beta$ a logarithmic finite-size correction term whose universal prefactor depends only on the Euler number of the domain and the conformal anomaly numbe...
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Type Safe Redis Queries: A Case Study of Type-Level Programming in Haskell
Redis is an in-memory data structure store, often used as a database, with a Haskell interface Hedis. Redis is dynamically typed --- a key can be discarded and re-associated to a value of a different type, and a command, when fetching a value of a type it does not expect, signals a runtime error. We develop a domain-...
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Ground state solutions for a nonlinear Choquard equation
We discuss the existence of ground state solutions for the Choquard equation $$-\Delta u=(I_\alpha*F(u))F'(u)\quad\quad\quad\text{in }\mathbb R^N.$$ We prove the existence of solutions under general hypotheses, investigating in particular the case of a homogeneous nonlinearity $F(u)=\frac{|u|^p}p$. The cases $N=2$ an...
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Ultrashort dark solitons interactions and nonlinear tunneling in the modified nonlinear Schrödinger equation with variable coefficients
We present the study of the dark soliton dynamics in an inhomogenous fiber by means of a variable coefficient modified nonlinear Schrödinger equation (Vc-MNLSE) with distributed dispersion, self-phase modulation, self-steepening and linear gain/loss. The ultrashort dark soliton pulse evolution and interaction is stud...
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Long-range p-d exchange interaction in a ferromagnet-semiconductor Co/CdMgTe/CdTe quantum well hybrid structure
The exchange interaction between magnetic ions and charge carriers in semiconductors is considered as prime tool for spin control. Here, we solve a long-standing problem by uniquely determining the magnitude of the long-range $p-d$ exchange interaction in a ferromagnet-semiconductor (FM-SC) hybrid structure where a 1...
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Parsec-scale Faraday rotation and polarization of 20 active galactic nuclei jets
We perform polarimetry analysis of 20 active galactic nuclei (AGN) jets using the Very Long Baseline Array (VLBA) at 1.4, 1.6, 2.2, 2.4, 4.6, 5.0, 8.1, 8.4, and 15.4 GHz. The study allowed us to investigate linearly polarized properties of the jets at parsec-scales: distribution of the Faraday rotation measure (RM) a...
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Positive scalar curvature and connected sums
Let $N$ be a closed enlargeable manifold in the sense of Gromov-Lawson and $M$ a closed spin manifold of equal dimension, a famous theorem of Gromov-Lawson states that the connected sum $M\# N$ admits no metric of positive scalar curvature. We present a potential generalization of this result to the case where $M$ is...
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Optical computing by injection-locked lasers
A programmable optical computer has remained an elusive concept. To construct a practical computing primitive equivalent to an electronic Boolean logic, one should find a nonlinear phenomenon that overcomes weaknesses present in many optical processing schemes. Ideally, the nonlinearity should provide a functionally ...
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On the joint asymptotic distribution of the restricted estimators in multivariate regression model
The main Theorem of Jain et al.[Jain, K., Singh, S., and Sharma, S. (2011), Re- stricted estimation in multivariate measurement error regression model; JMVA, 102, 2, 264-280] is established in its full generality. Namely, we derive the joint asymp- totic normality of the unrestricted estimator (UE) and the restricted...
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Rotational spectroscopy, tentative interstellar detection, and chemical modelling of N-methylformamide
N-methylformamide, CH3NHCHO, may be an important molecule for interstellar pre-biotic chemistry because it contains a peptide bond. The rotational spectrum of the most stable trans conformer of CH3NHCHO is complicated by strong torsion-rotation interaction due to the low barrier of the methyl torsion. We use two abso...
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Dynamic anisotropy in MHD turbulence induced by mean magnetic field
In this paper, we study the development of anisotropy in strong MHD turbulence in the presence of a large scale magnetic field B 0 by analyzing the results of direct numerical simulations. Our results show that the developed anisotropy among the different components of the velocity and magnetic field is a direct outc...
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Dealing with the exponential wall in electronic structure calculations
An alternative to Density Functional Theory are wavefunction based electronic structure calculations for solids. In order to perform them the Exponential Wall (EW) problem has to be resolved. It is caused by an exponential increase of the number of configurations with increasing electron number N. There are different...
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Influence maximization on correlated networks through community identification
The identification of the minimal set of nodes that maximizes the propagation of information is one of the most important problems in network science. In this paper, we introduce a new method to find the set of initial spreaders to maximize the information propagation in complex networks. We evaluate this method in a...
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Conformal metrics with prescribed fractional scalar curvature on conformal infinities with positive fractional Yamabe constants
Let $(X, g^+)$ be an asymptotically hyperbolic manifold and $(M, [\hat{h}])$ its conformal infinity. Our primary aim in this paper is to introduce the prescribed fractional scalar curvature problem on $M$ and provide solutions under various geometric conditions on $X$ and $M$. We also obtain the existence results for...
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A Short Review of Ethical Challenges in Clinical Natural Language Processing
Clinical NLP has an immense potential in contributing to how clinical practice will be revolutionized by the advent of large scale processing of clinical records. However, this potential has remained largely untapped due to slow progress primarily caused by strict data access policies for researchers. In this paper, ...
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kd-switch: A Universal Online Predictor with an application to Sequential Two-Sample Testing
We propose a novel online predictor for discrete labels conditioned on multivariate features in $\mathbb{R}^d$. The predictor is pointwise universal: it achieves a normalized log loss performance asymptotically as good as the true conditional entropy of the labels given the features. The predictor is based on a featu...
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A Heat Equation on some Adic Completions of Q and Ultrametric Analysis
This article deals with a Markov process related to the fundamental solution of a heat equation on the direct product ring Q_S, where Q_S is a finite direct product of p-adic fields. The techniques developed here are different from the well known ones: they are geometrical and very simple. As a result, the techniques...
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A simple alteration of the peridynamics correspondence principle to eliminate zero-energy deformation
We look for an enhancement of the correspondence model of peridynamics with a view to eliminating the zero-energy deformation modes. Since the non-local integral definition of the deformation gradient underlies the problem, we initially look for a remedy by introducing a class of localizing corrections to the integra...
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Interpretable Active Learning
Active learning has long been a topic of study in machine learning. However, as increasingly complex and opaque models have become standard practice, the process of active learning, too, has become more opaque. There has been little investigation into interpreting what specific trends and patterns an active learning ...
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Orbital-Free Density-Functional Theory Simulations of Displacement Cascade in Aluminum
Here, we report orbital-free density-functional theory (OF DFT) molecular dynamics simulations of the displacement cascade in aluminum. The electronic effect is our main concern. The displacement threshold energies are calculated using OF DFT and classical molecular dynamics (MD) and the comparison reveals the role o...
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Binary systems with an RR Lyrae component - progress in 2016
In this contribution, we summarize the progress made in the investigation of binary candidates with an RR Lyrae component in 2016. We also discuss the actual status of the RRLyrBinCan database.
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Covering and tiling hypergraphs with tight cycles
Given $3 \leq k \leq s$, we say that a $k$-uniform hypergraph $C^k_s$ is a tight cycle on $s$ vertices if there is a cyclic ordering of the vertices of $C^k_s$ such that every $k$ consecutive vertices under this ordering form an edge. We prove that if $k \ge 3$ and $s \ge 2k^2$, then every $k$-uniform hypergraph on $...
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DNA methylation markers to assess biological age
Among the different biomarkers of aging based on omics and clinical data, DNA methylation clocks stand apart providing unmatched accuracy in assessing the biological age of both humans and animal models of aging. Here, we discuss robustness of DNA methylation clocks and bounds on their out-of-sample performance and r...
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Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine (SVM) for Malware Classification
Effective and efficient mitigation of malware is a long-time endeavor in the information security community. The development of an anti-malware system that can counteract an unknown malware is a prolific activity that may benefit several sectors. We envision an intelligent anti-malware system that utilizes the power ...
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Exponential profiles from stellar scattering off interstellar clumps and holes in dwarf galaxy discs
Holes and clumps in the interstellar gas of dwarf irregular galaxies are gravitational scattering centers that heat field stars and change their radial and vertical distributions. Because the gas structures are extended and each stellar scattering is relatively weak, the stellar orbits remain nearly circular and the ...
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Visualizations for an Explainable Planning Agent
In this paper, we report on the visualization capabilities of an Explainable AI Planning (XAIP) agent that can support human in the loop decision making. Imposing transparency and explainability requirements on such agents is especially important in order to establish trust and common ground with the end-to-end autom...
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Generative adversarial interpolative autoencoding: adversarial training on latent space interpolations encourage convex latent distributions
We present a neural network architecture based upon the Autoencoder (AE) and Generative Adversarial Network (GAN) that promotes a convex latent distribution by training adversarially on latent space interpolations. By using an AE as both the generator and discriminator of a GAN, we pass a pixel-wise error function ac...
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Attribute-Guided Face Generation Using Conditional CycleGAN
We are interested in attribute-guided face generation: given a low-res face input image, an attribute vector that can be extracted from a high-res image (attribute image), our new method generates a high-res face image for the low-res input that satisfies the given attributes. To address this problem, we condition th...
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Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models
In unsupervised data generation tasks, besides the generation of a sample based on previous observations, one would often like to give hints to the model in order to bias the generation towards desirable metrics. We propose a method that combines Generative Adversarial Networks (GANs) and reinforcement learning (RL) ...
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Pluripotential theory on the support of closed positive currents and applications to dynamics in $\mathbb{C}^n$
We extend certain classical theorems in pluripotential theory to a class of functions defined on the support of a $(1,1)$-closed positive current $T$, analogous to plurisubharmonic functions, called $T$-plurisubharmonic functions. These functions are defined as limits, on the support of $T$, of sequences of plurisubh...
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Inconsistency of Measure-Theoretic Probability and Random Behavior of Microscopic Systems
We report an inconsistency found in probability theory (also referred to as measure-theoretic probability). For probability measures induced by real-valued random variables, we deduce an "equality" such that one side of the "equality" is a probability, but the other side is not. For probability measures induced by ex...
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Robustness of Quasiparticle Interference Test for Sign-changing Gaps in Multiband Superconductors
Recently, a test for a sign-changing gap function in a candidate multiband unconventional superconductor involving quasiparticle interference data was proposed. The test was based on the antisymmetric, Fourier transformed conductance maps integrated over a range of momenta $\bf q$ corresponding to interband processes...
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Adaptive User Perspective Rendering for Handheld Augmented Reality
Handheld Augmented Reality commonly implements some variant of magic lens rendering, which turns only a fraction of the user's real environment into AR while the rest of the environment remains unaffected. Since handheld AR devices are commonly equipped with video see-through capabilities, AR magic lens applications ...
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A distributed primal-dual algorithm for computation of generalized Nash equilibria with shared affine coupling constraints via operator splitting methods
In this paper, we propose a distributed primal-dual algorithm for computation of a generalized Nash equilibrium (GNE) in noncooperative games over network systems. In the considered game, not only each player's local objective function depends on other players' decisions, but also the feasible decision sets of all th...
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Inverse dynamic and spectral problems for the one-dimensional Dirac system on a finite tree
We consider inverse dynamic and spectral problems for the one dimensional Dirac system on a finite tree. Our aim will be to recover the topology of a tree (lengths and connectivity of edges) as well as matrix potentials on each edge. As inverse data we use the Weyl-Titchmarsh matrix function or the dynamic response o...
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Extensions of isomorphisms of subvarieties in flexile varieties
Let $X$ be a quasi-affine algebraic variety isomorphic to the complement of a closed subvariety of dimension at most $n-3$ in $\C^n$. We find some conditions under which an isomorphism of two closed subvarieties of $X$ can be extended to an automorphism of $X$.
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Frequentist coverage and sup-norm convergence rate in Gaussian process regression
Gaussian process (GP) regression is a powerful interpolation technique due to its flexibility in capturing non-linearity. In this paper, we provide a general framework for understanding the frequentist coverage of point-wise and simultaneous Bayesian credible sets in GP regression. As an intermediate result, we devel...
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Most Probable Evolution Trajectories in a Genetic Regulatory System Excited by Stable Lévy Noise
We study the most probable trajectories of the concentration evolution for the transcription factor activator in a genetic regulation system, with non-Gaussian stable Lévy noise in the synthesis reaction rate taking into account. We calculate the most probable trajectory by spatially maximizing the probability densit...
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Simplified derivation of the collision probability of two objects in independent Keplerian orbits
Many topics in planetary studies demand an estimate of the collision probability of two objects moving on nearly Keplerian orbits. In the classic works of Öpik (1951) and Wetherill (1967), the collision probability was derived by linearizing the motion near the collision points, and there is now a vast literature usi...
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Optically Coupled Methods for Microwave Impedance Microscopy
Scanning Microwave Impedance Microscopy (MIM) measurement of photoconductivity with 50 nm resolution is demonstrated using a modulated optical source. The use of a modulated source allows for measurement of photoconductivity in a single scan without a reference region on the sample, as well as removing most topograph...
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Generalized feedback vertex set problems on bounded-treewidth graphs: chordality is the key to single-exponential parameterized algorithms
It has long been known that Feedback Vertex Set can be solved in time $2^{\mathcal{O}(w\log w)}n^{\mathcal{O}(1)}$ on $n$-vertex graphs of treewidth $w$, but it was only recently that this running time was improved to $2^{\mathcal{O}(w)}n^{\mathcal{O}(1)}$, that is, to single-exponential parameterized by treewidth. W...
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Electron-phonon coupling mechanisms for hydrogen-rich metals at high pressure
The mechanisms for strong electron-phonon coupling predicted for hydrogen-rich alloys with high superconducting critical temperature ($T_c$) are examined within the Migdal-Eliashberg theory. Analysis of the functional derivative of $T_c$ with respect to the electron-phonon spectral function shows that at low pressure...
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Competitive Equilibrium For almost All Incomes
Competitive equilibrium from equal incomes (CEEI) is a well-known rule for fair allocation of resources among agents with different preferences. It has many advantages, among them is the fact that a CEEI allocation is both Pareto efficient and envy-free. However, when the resources are indivisible, a CEEI allocation ...
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Converting of algebraic Diophantine equations to a diagonal form with the help of an integer non-orthogonal transformation, maintaining the asymptotic behavior of the number of its integer solutions
The author showed that any homogeneous algebraic Diophantine equation of the second order can be converted to a diagonal form using an integer non-orthogonal transformation maintaining asymptotic behavior of the number of its integer solutions. In this paper, we consider the transformation to the diagonal form of a w...
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A Deep Learning Approach with an Attention Mechanism for Automatic Sleep Stage Classification
Automatic sleep staging is a challenging problem and state-of-the-art algorithms have not yet reached satisfactory performance to be used instead of manual scoring by a sleep technician. Much research has been done to find good feature representations that extract the useful information to correctly classify each epo...
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Laser Wakefield Accelerators
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 accelera...
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Permutation complexity of images of Sturmian words by marked morphisms
We show that the permutation complexity of the image of a Sturmian word by a binary marked morphism is $n+k$ for some constant $k$ and all lengths $n$ sufficiently large.
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Three principles of data science: predictability, computability, and stability (PCS)
We propose the predictability, computability, and stability (PCS) framework to extract reproducible knowledge from data that can guide scientific hypothesis generation and experimental design. The PCS framework builds on key ideas in machine learning, using predictability as a reality check and evaluating computation...
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The Elasticity of Puiseux Monoids
Let $M$ be an atomic monoid and let $x$ be a non-unit element of $M$. The elasticity of $x$, denoted by $\rho(x)$, is the ratio of its largest factorization length to its shortest factorization length, and it measures how far is $x$ from having a unique factorization. The elasticity $\rho(M)$ of $M$ is the supremum o...
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Barcode Embeddings for Metric Graphs
Stable topological invariants are a cornerstone of persistence theory and applied topology, but their discriminative properties are often poorly-understood. In this paper we study a rich homology-based invariant first defined by Dey, Shi, and Wang, which we think of as embedding a metric graph in the barcode space. W...
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On the extremal extensions of a non-negative Jacobi operator
We consider minimal non-negative Jacobi operator with $p\times p-$matrix entries. Using the technique of boundary triplets and the corresponding Weyl functions, we describe the Friedrichs and Krein extensions of the minimal Jacobi operator. Moreover, we parameterize the set of all non-negative self-adjoint extensions...
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Note on the geodesic Monte Carlo
Geodesic Monte Carlo (gMC) is a powerful algorithm for Bayesian inference on non-Euclidean manifolds. The original gMC algorithm was cleverly derived in terms of its progenitor, the Riemannian manifold Hamiltonian Monte Carlo (RMHMC). Here, it is shown that alternative and theoretically simpler derivations are availa...
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Google Scholar and the gray literature: A reply to Bonato's review
Recently, a review concluded that Google Scholar (GS) is not a suitable source of information "for identifying recent conference papers or other gray literature publications". The goal of this letter is to demonstrate that GS can be an effective tool to search and find gray literature, as long as appropriate search s...
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A Next-Best-Smell Approach for Remote Gas Detection with a Mobile Robot
The problem of gas detection is relevant to many real-world applications, such as leak detection in industrial settings and landfill monitoring. Using mobile robots for gas detection has several advantages and can reduce danger for humans. In our work, we address the problem of planning a path for a mobile robotic pl...
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KZ-Calogero correspondence revisited
We discuss the correspondence between the Knizhnik-Zamolodchikov equations associated with $GL(N)$ and the $n$-particle quantum Calogero model in the case when $n$ is not necessarily equal to $N$. This can be viewed as a natural "quantization" of the quantum-classical correspondence between quantum Gaudin and classic...
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Spectral up- and downshifting of Akhmediev breathers under wind forcing
We experimentally and numerically investigate the effect of wind forcing on the spectral dynamics of Akhmediev breathers, a wave-type known to model the modulation instability. We develop the wind model to the same order in steepness as the higher order modifcation of the nonlinear Schroedinger equation, also referre...
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High Rate LDPC Codes from Difference Covering Arrays
This paper presents a combinatorial construction of low-density parity-check (LDPC) codes from difference covering arrays. While the original construction by Gallagher was by randomly allocating bits in a sparse parity-check matrix, over the past 20 years researchers have used a variety of more structured approaches ...
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Bootstrapping spectral statistics in high dimensions
Statistics derived from the eigenvalues of sample covariance matrices are called spectral statistics, and they play a central role in multivariate testing. Although bootstrap methods are an established approach to approximating the laws of spectral statistics in low-dimensional problems, these methods are relatively ...
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On parabolic subgroups of Artin-Tits groups of spherical type
We show that, in an Artin-Tits group of spherical type, the intersection of two parabolic subgroups is a parabolic subgroup. Moreover, we show that the set of parabolic subgroups forms a lattice with respect to inclusion. This extends to all Artin-Tits groups of spherical type a result that was previously known for b...
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A statistical test for the Zipf's law by deviations from the Heaps' law
We explore a probabilistic model of an artistic text: words of the text are chosen independently of each other in accordance with a discrete probability distribution on an infinite dictionary. The words are enumerated 1, 2, $\ldots$, and the probability of appearing the $i$'th word is asymptotically a power function....
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Weakly Supervised Classification in High Energy Physics
As machine learning algorithms become increasingly sophisticated to exploit subtle features of the data, they often become more dependent on simulations. This paper presents a new approach called weakly supervised classification in which class proportions are the only input into the machine learning algorithm. Using ...
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Profit Driven Decision Trees for Churn Prediction
Customer retention campaigns increasingly rely on predictive models to detect potential churners in a vast customer base. From the perspective of machine learning, the task of predicting customer churn can be presented as a binary classification problem. Using data on historic behavior, classification algorithms are ...
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Carrier loss mechanisms in textured crystalline Si-based solar cells
A quite general device analysis method that allows the direct evaluation of optical and recombination losses in crystalline silicon (c-Si)-based solar cells has been developed. By applying this technique, the optical and physical limiting factors of the state-of-the-art solar cells with ~20% efficiencies have been re...
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The generating function for the Airy point process and a system of coupled Painlevé II equations
For a wide class of Hermitian random matrices, the limit distribution of the eigenvalues close to the largest one is governed by the Airy point process. In such ensembles, the limit distribution of the k-th largest eigenvalue is given in terms of the Airy kernel Fredholm determinant or in terms of Tracy-Widom formula...
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Gradient-based Training of Slow Feature Analysis by Differentiable Approximate Whitening
This paper proposes Power Slow Feature Analysis, a gradient-based method to extract temporally-slow features from a high-dimensional input stream that varies on a faster time-scale, and a variant of Slow Feature Analysis (SFA). While displaying performance comparable to hierarchical extensions to the SFA algorithm, s...
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Quantum Critical Behavior in the Asymptotic Limit of High Disorder: Entropy Stabilized NiCoCr0.8 Alloys
The behavior of matter near a quantum critical point (QCP) is one of the most exciting and challenging areas of physics research. Emergent phenomena such as high-temperature superconductivity are linked to the proximity to a QCP. Although significant progress has been made in understanding quantum critical behavior i...
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Multilayer Network Modeling of Integrated Biological Systems
Biological systems, from a cell to the human brain, are inherently complex. A powerful representation of such systems, described by an intricate web of relationships across multiple scales, is provided by complex networks. Recently, several studies are highlighting how simple networks -- obtained by aggregating or ne...
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Fast, Autonomous Flight in GPS-Denied and Cluttered Environments
One of the most challenging tasks for a flying robot is to autonomously navigate between target locations quickly and reliably while avoiding obstacles in its path, and with little to no a-priori knowledge of the operating environment. This challenge is addressed in the present paper. We describe the system design an...
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Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks
Efforts to reduce the numerical precision of computations in deep learning training have yielded systems that aggressively quantize weights and activations, yet employ wide high-precision accumulators for partial sums in inner-product operations to preserve the quality of convergence. The absence of any framework to ...
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The Berkovich realization for rigid analytic motives
We prove that the functor associating to a rigid analytic variety the singular complex of the underlying Berkovich topological space is motivic, and defines the maximal Artin quotient of a motive. We use this to generalize Berkovich's results on the weight-zero part of the étale cohomology of a variety defined over a...
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Rates of estimation for determinantal point processes
Determinantal point processes (DPPs) have wide-ranging applications in machine learning, where they are used to enforce the notion of diversity in subset selection problems. Many estimators have been proposed, but surprisingly the basic properties of the maximum likelihood estimator (MLE) have received little attenti...
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Negative refraction in Weyl semimetals
We theoretically propose that Weyl semimetals may exhibit negative refraction at some frequencies close to the plasmon frequency, allowing transverse magnetic (TM) electromagnetic waves with frequencies smaller than the plasmon frequency to propagate in the Weyl semimetals. The idea is justified by the calculation of...
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Towards Object Life Cycle-Based Variant Generation of Business Process Models
Variability management of process models is a major challenge for Process-Aware Information Systems. Process model variants can be attributed to any of the following reasons: new technologies, governmental rules, organizational context or adoption of new standards. Current approaches to manage variants of process mod...
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Detection of sub-MeV Dark Matter with Three-Dimensional Dirac Materials
We propose the use of three-dimensional Dirac materials as targets for direct detection of sub-MeV dark matter. Dirac materials are characterized by a linear dispersion for low-energy electronic excitations, with a small band gap of O(meV) if lattice symmetries are broken. Dark matter at the keV scale carrying kineti...
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Formation of Local Resonance Band Gaps in Finite Acoustic Metamaterials: A Closed-form Transfer Function Model
The objective of this paper is to use transfer functions to comprehend the formation of band gaps in locally resonant acoustic metamaterials. Identifying a recursive approach for any number of serially arranged locally resonant mass in mass cells, a closed form expression for the transfer function is derived. Analysi...
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Online Multi-Label Classification: A Label Compression Method
Many modern applications deal with multi-label data, such as functional categorizations of genes, image labeling and text categorization. Classification of such data with a large number of labels and latent dependencies among them is a challenging task, and it becomes even more challenging when the data is received o...
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Mutual Alignment Transfer Learning
Training robots for operation in the real world is a complex, time consuming and potentially expensive task. Despite significant success of reinforcement learning in games and simulations, research in real robot applications has not been able to match similar progress. While sample complexity can be reduced by traini...
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Tangent: Automatic differentiation using source-code transformation for dynamically typed array programming
The need to efficiently calculate first- and higher-order derivatives of increasingly complex models expressed in Python has stressed or exceeded the capabilities of available tools. In this work, we explore techniques from the field of automatic differentiation (AD) that can give researchers expressive power, perfor...
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Scalar and Tensor Parameters for Importing Tensor Index Notation including Einstein Summation Notation
In this paper, we propose a method for importing tensor index notation, including Einstein summation notation, into functional programming. This method involves introducing two types of parameters, i.e, scalar and tensor parameters, and simplified tensor index rules that do not handle expressions that are valid only ...
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Evidence for coherent spicule oscillations by correcting Hinode/SOT Ca II H in the southeast limb of the Sun
Wave theories of heating the chromosphere, corona, and solar wind due to photospheric fluctuations are strengthened by the existence of observed wave coherency up to the transition region (TR). The coherency of solar spicules' intensity oscillations was explored using the Solar Optical Telescope (SOT) on the Hinode s...
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Dynamics and transverse relaxation of an unconventional spin-rotation mode in a two-dimensional strongly magnetized electron gas
An unconventional spin-rotation mode emerging in a quantum Hall ferromagnet due to excitation by a laser pulse is studied. This state, macroscopically representing a rotation of the entire electron spin-system to a certain angle, microscopically is not equivalent to a coherent turn of all spins as a single-whole and ...
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Opinion diversity and community formation in adaptive networks
It is interesting and of significant importance to investigate how network structures co-evolve with opinions. The existing models of such co-evolution typically lead to the final states where network nodes either reach a global consensus or break into separated communities, each of which holding its own community co...
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On the local and global comparison of generalized Bajraktarević means
Given two continuous functions $f,g:I\to\mathbb{R}$ such that $g$ is positive and $f/g$ is strictly monotone, a measurable space $(T,A)$, a measurable family of $d$-variable means $m: I^d\times T\to I$, and a probability measure $\mu$ on the measurable sets $A$, the $d$-variable mean $M_{f,g,m;\mu}:I^d\to I$ is defin...
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