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Binary Image Selection (BISON): Interpretable Evaluation of Visual Grounding
Providing systems the ability to relate linguistic and visual content is one of the hallmarks of computer vision. Tasks such as image captioning and retrieval were designed to test this ability, but come with complex evaluation measures that gauge various other abilities and biases simultaneously. This paper presents...
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Parallelization does not Accelerate Convex Optimization: Adaptivity Lower Bounds for Non-smooth Convex Minimization
In this paper we study the limitations of parallelization in convex optimization. A convenient approach to study parallelization is through the prism of \emph{adaptivity} which is an information theoretic measure of the parallel runtime of an algorithm. Informally, adaptivity is the number of sequential rounds an alg...
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Velocity dependence of point masses, moving on timelike geodesics, in weak gravitational fields
Applying the principle of equivalence, analogous to Einstein's original 1907 approach demonstrating the bending of light in a gravitational field, we deduce that radial geodesics of point masses are velocity dependent. Then, using the Schwarzschild solution for observers at spatial infinity, we analyze the similar ca...
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Demand Response in the Smart Grid: the Impact of Consumers Temporal Preferences
In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work a...
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Distributed Nesterov gradient methods over arbitrary graphs
In this letter, we introduce a distributed Nesterov method, termed as $\mathcal{ABN}$, that does not require doubly-stochastic weight matrices. Instead, the implementation is based on a simultaneous application of both row- and column-stochastic weights that makes this method applicable to arbitrary (strongly-connect...
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Casualty Detection from 3D Point Cloud Data for Autonomous Ground Mobile Rescue Robots
One of the most important features of mobile rescue robots is the ability to autonomously detect casualties, i.e. human bodies, which are usually lying on the ground. This paper proposes a novel method for autonomously detecting casualties lying on the ground using obtained 3D point-cloud data from an on-board sensor...
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Representations of superconformal algebras and mock theta functions
It is well known that the normaized characters of integrable highest weight modules of given level over an affine Lie algebra $\hat{\frak{g}}$ span an $SL_2(\mathbf{Z})$-invariant space. This result extends to admissible $\hat{\frak{g}}$-modules, where $\frak{g}$ is a simple Lie algebra or $osp_{1|n}$. Applying the q...
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Anchored Network Users: Stochastic Evolutionary Dynamics of Cognitive Radio Network Selection
To solve the spectrum scarcity problem, the cognitive radio technology involves licensed users and unlicensed users. A fundamental issue for the network users is whether it is better to act as a licensed user by using a primary network or an unlicensed user by using a secondary network. To model the network selection...
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On the rates of convergence of Parallelized Averaged Stochastic Gradient Algorithms
The growing interest for high dimensional and functional data analysis led in the last decade to an important research developing a consequent amount of techniques. Parallelized algorithms, which consist in distributing and treat the data into different machines, for example, are a good answer to deal with large samp...
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On Convergence of Extended Dynamic Mode Decomposition to the Koopman Operator
Extended Dynamic Mode Decomposition (EDMD) is an algorithm that approximates the action of the Koopman operator on an $N$-dimensional subspace of the space of observables by sampling at $M$ points in the state space. Assuming that the samples are drawn either independently or ergodically from some measure $\mu$, it w...
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Random problems with R
R (Version 3.5.1 patched) has an issue with its random sampling functionality. R generates random integers between $1$ and $m$ by multiplying random floats by $m$, taking the floor, and adding $1$ to the result. Well-known quantization effects in this approach result in a non-uniform distribution on $\{ 1, \ldots, m\...
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Quasinormal modes as a distinguisher between general relativity and f(R) gravity
Quasi-Normal Modes (QNM) or ringdown phase of gravitational waves provide critical information about the structure of compact objects like Black Holes. Thus, QNMs can be a tool to test General Relativity (GR) and possible deviations from it. In the case of GR, it is known for a long time that a relation between two t...
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Polymorphism and the obstinate circularity of second order logic: a victims' tale
The investigations on higher-order type theories and on the related notion of parametric polymorphism constitute the technical counterpart of the old foundational problem of the circularity (or impredicativity) of second and higher order logic. However, the epistemological significance of such investigations, and of ...
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Bayesian significance test for discriminating between survival distributions
An evaluation of FBST, Fully Bayesian Significance Test, restricted to survival models is the main objective of the present paper. A Survival distribution should be chosen among the tree celebrated ones, lognormal, gamma, and Weibull. For this discrimination, a linear mixture of the three distributions, for which the...
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A Minimal Closed-Form Solution for Multi-Perspective Pose Estimation using Points and Lines
We propose a minimal solution for pose estimation using both points and lines for a multi-perspective camera. In this paper, we treat the multi-perspective camera as a collection of rigidly attached perspective cameras. These type of imaging devices are useful for several computer vision applications that require a l...
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Learning K-way D-dimensional Discrete Code For Compact Embedding Representations
Embedding methods such as word embedding have become pillars for many applications containing discrete structures. Conventional embedding methods directly associate each symbol with a continuous embedding vector, which is equivalent to applying linear transformation based on "one-hot" encoding of the discrete symbols...
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Attention based convolutional neural network for predicting RNA-protein binding sites
RNA-binding proteins (RBPs) play crucial roles in many biological processes, e.g. gene regulation. Computational identification of RBP binding sites on RNAs are urgently needed. In particular, RBPs bind to RNAs by recognizing sequence motifs. Thus, fast locating those motifs on RNA sequences is crucial and time-effic...
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Ramp Reversal Memory and Phase-Boundary Scarring in Transition Metal Oxides
Transition metal oxides (TMOs) are complex electronic systems which exhibit a multitude of collective phenomena. Two archetypal examples are VO2 and NdNiO3, which undergo a metal-insulator phase-transition (MIT), the origin of which is still under debate. Here we report the discovery of a memory effect in both system...
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A multi-channel approach for automatic microseismic event localization using RANSAC-based arrival time event clustering(RATEC)
In the presence of background noise and interference, arrival times picked from a surface microseismic data set usually include a number of false picks which lead to uncertainty in location estimation. To eliminate false picks and improve the accuracy of location estimates, we develop a classification algorithm (RATE...
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Universal in vivo Textural Model for Human Skin based on Optical Coherence Tomograms
Currently, diagnosis of skin diseases is based primarily on visual pattern recognition skills and expertise of the physician observing the lesion. Even though dermatologists are trained to recognize patterns of morphology, it is still a subjective visual assessment. Tools for automated pattern recognition can provide...
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Batched Large-scale Bayesian Optimization in High-dimensional Spaces
Bayesian optimization (BO) has become an effective approach for black-box function optimization problems when function evaluations are expensive and the optimum can be achieved within a relatively small number of queries. However, many cases, such as the ones with high-dimensional inputs, may require a much larger nu...
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Will a Large Economy Be Stable?
We study networks of firms with Leontief production functions. Relying on results from Random Matrix Theory, we argue that such networks generically become unstable when their size increases, or when the heterogeneity in productivities/connectivities becomes too strong. At marginal stability and for large heterogenei...
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Linear Convergence of Accelerated Stochastic Gradient Descent for Nonconvex Nonsmooth Optimization
In this paper, we study the stochastic gradient descent (SGD) method for the nonconvex nonsmooth optimization, and propose an accelerated SGD method by combining the variance reduction technique with Nesterov's extrapolation technique. Moreover, based on the local error bound condition, we establish the linear conver...
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TRINITY: Coordinated Performance, Energy and Temperature Management in 3D Processor-Memory Stacks
The consistent demand for better performance has lead to innovations at hardware and microarchitectural levels. 3D stacking of memory and logic dies delivers an order of magnitude improvement in available memory bandwidth. The price paid however is, tight thermal constraints. In this paper, we study the complex multi...
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Robust Covariate Shift Prediction with General Losses and Feature Views
Covariate shift relaxes the widely-employed independent and identically distributed (IID) assumption by allowing different training and testing input distributions. Unfortunately, common methods for addressing covariate shift by trying to remove the bias between training and testing distributions using importance wei...
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On the Ergodic Control of Ensembles
Across smart-grid and smart-city applications, there are problems where an ensemble of agents is to be controlled such that both the aggregate behaviour and individual-level perception of the system's performance are acceptable. In many applications, traditional PI control is used to regulate aggregate ensemble perfo...
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Relative merits of Phononics vs. Plasmonics: the energy balance approach
The common feature of various plasmonic schemes is their ability to confine optical fields of surface plasmon polaritons (SPPs) into sub-wavelength volumes and thus achieve a large enhancement of linear and nonlinear optical properties. This ability, however, is severely limited by the large ohmic loss inherent to ev...
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Memory footprint reduction for the FFT-based volume integral equation method via tensor decompositions
We present a method of memory footprint reduction for FFT-based, electromagnetic (EM) volume integral equation (VIE) formulations. The arising Green's function tensors have low multilinear rank, which allows Tucker decomposition to be employed for their compression, thereby greatly reducing the required memory storag...
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On a property of the nodal set of least energy sign-changing solutions for quasilinear elliptic equations
In this note we prove the Payne-type conjecture about the behaviour of the nodal set of least energy sign-changing solutions for the equation $-\Delta_p u = f(u)$ in bounded Steiner symmetric domains $\Omega \subset \mathbb{R}^N$ under the zero Dirichlet boundary conditions. The nonlinearity $f$ is assumed to be eith...
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Smooth contractible threefolds with hyperbolic $\mathbb{G}_{m}$-actions via ps-divisors
The aim of this note is to give an alternative proof of a theorem of Koras and Russell, that is, a characterization of smooth contractible affine varieties endowed with a hyperbolic action of the group $\mathbb{G}_{m}\simeq\mathbb{C}^{\text{*}}$, using the language of polyhedral divisors developed by Altmann and Haus...
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Ergodic Theorems for Nonconventional Arrays and an Extension of the Szemeredi Theorem
The paper is primarily concerned with the asymptotic behavior as $N\to\infty$ of averages of nonconventional arrays having the form $N^{-1}\sum_{n=1}^N\prod_{j=1}^\ell T^{P_j(n,N)}f_j$ where $f_j$'s are bounded measurable functions, $T$ is an invertible measure preserving transformation and $P_j$'s are polynomials of...
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Bellman Gradient Iteration for Inverse Reinforcement Learning
This paper develops an inverse reinforcement learning algorithm aimed at recovering a reward function from the observed actions of an agent. We introduce a strategy to flexibly handle different types of actions with two approximations of the Bellman Optimality Equation, and a Bellman Gradient Iteration method to comp...
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Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data
We consider the question of accurately and efficiently computing low-rank matrix or tensor factorizations given data compressed via random projections. This problem arises naturally in the many settings in which data is acquired via compressive sensing. We examine the approach of first performing factorization in the...
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Quantum gravity corrections to the thermodynamics and phase transition of Schwarzschild black hole
In this work, we derive a new kind of rainbow functions, which has generalized uncertainty principle parameter. Then, we investigate modified thermodynamic quantities and phase transition of rainbow Schwarzschild black hole by employing this new kind of rainbow functions. Our results demonstrate that the effect of ra...
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Non-abelian reciprocity laws and higher Brauer-Manin obstructions
We reinterpret Kim's non-abelian reciprocity maps for algebraic varieties as obstruction towers of mapping spaces of etale homotopy types, removing technical hypotheses such as global basepoints and cohomological constraints. We then extend the theory by considering alternative natural series of extensions, one of wh...
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Learning with Bounded Instance- and Label-dependent Label Noise
Instance- and label-dependent label noise (ILN) is widely existed in real-world datasets but has been rarely studied. In this paper, we focus on a particular case of ILN where the label noise rates, representing the probabilities that the true labels of examples flip into the corrupted labels, have upper bounds. We p...
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Community Detection in Hypergraphs, Spiked Tensor Models, and Sum-of-Squares
We study the problem of community detection in hypergraphs under a stochastic block model. Similarly to how the stochastic block model in graphs suggests studying spiked random matrices, our model motivates investigating statistical and computational limits of exact recovery in a certain spiked tensor model. In contr...
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Presentations of the saturated cluster modular groups of finite mutation type $X_6$ and $X_7$
We give finite presentations of the saturated cluster modular groups of type $X_6$ and $X_7$. We compute the first homology of these groups and conclude that they are different from Artin-Tits braid groups and mapping class groups of surfaces. We verify that the cluster modular group of type $X_7$ is generated by clu...
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Quantum Query Algorithms are Completely Bounded Forms
We prove a characterization of $t$-query quantum algorithms in terms of the unit ball of a space of degree-$2t$ polynomials. Based on this, we obtain a refined notion of approximate polynomial degree that equals the quantum query complexity, answering a question of Aaronson et al. (CCC'16). Our proof is based on a fu...
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Massively-Parallel Feature Selection for Big Data
We present the Parallel, Forward-Backward with Pruning (PFBP) algorithm for feature selection (FS) in Big Data settings (high dimensionality and/or sample size). To tackle the challenges of Big Data FS PFBP partitions the data matrix both in terms of rows (samples, training examples) as well as columns (features). By...
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Gravitational Wave Sources from Pop III Stars are Preferentially Located within the Cores of their Host Galaxies
The detection of gravitational waves (GWs) generated by merging black holes has recently opened up a new observational window into the Universe. The mass of the black holes in the first and third LIGO detections, ($36-29 \, \mathrm{M_{\odot}}$ and $32-19 \, \mathrm{M_{\odot}}$), suggests low-metallicity stars as thei...
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A Markov Chain Model for the Cure Rate of Non-Performing Loans
A Markov-chain model is developed for the purpose estimation of the cure rate of non-performing loans. The technique is performed collectively, on portfolios and it can be applicable in the process of calculation of credit impairment. It is efficient in terms of data manipulation costs which makes it accessible even ...
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Query-Efficient Black-box Adversarial Examples (superceded)
Note that this paper is superceded by "Black-Box Adversarial Attacks with Limited Queries and Information." Current neural network-based image classifiers are susceptible to adversarial examples, even in the black-box setting, where the attacker is limited to query access without access to gradients. Previous methods...
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Beyond the Erdős Matching Conjecture
A family $\mathcal F\subset {[n]\choose k}$ is $U(s,q)$ of for any $F_1,\ldots, F_s\in \mathcal F$ we have $|F_1\cup\ldots\cup F_s|\le q$. This notion generalizes the property of a family to be $t$-intersecting and to have matching number smaller than $s$. In this paper, we find the maximum $|\mathcal F|$ for $\mathc...
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pH dependence of charge multipole moments in proteins
Electrostatic interactions play a fundamental role in the structure and function of proteins. Due to ionizable amino acid residues present on the solvent-exposed surfaces of proteins, the protein charge is not constant but varies with the changes in the environment -- most notably, the pH of the surrounding solution....
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A streamlined, general approach for computing ligand binding free energies and its application to GPCR-bound cholesterol
The theory of receptor-ligand binding equilibria has long been well-established in biochemistry, and was primarily constructed to describe dilute aqueous solutions. Accordingly, few computational approaches have been developed for making quantitative predictions of binding probabilities in environments other than dil...
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Dynamics of one-dimensional electrons with broken spin-charge separation
Spin-charge separation is known to be broken in many physically interesting one-dimensional (1D) and quasi-1D systems with spin-orbit interaction because of which spin and charge degrees of freedom are mixed in collective excitations. Mixed spin-charge modes carry an electric charge and therefore can be investigated ...
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A Rational Distributed Process-level Account of Independence Judgment
It is inconceivable how chaotic the world would look to humans, faced with innumerable decisions a day to be made under uncertainty, had they been lacking the capacity to distinguish the relevant from the irrelevant---a capacity which computationally amounts to handling probabilistic independence relations. The highl...
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Automata in the Category of Glued Vector Spaces
In this paper we adopt a category-theoretic approach to the conception of automata classes enjoying minimization by design. The main instantiation of our construction is a new class of automata that are hybrid between deterministic automata and automata weighted over a field.
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Second order structural phase transitions, free energy curvature, and temperature-dependent anharmonic phonons in the self-consistent harmonic approximation: theory and stochastic implementation
The self-consistent harmonic approximation is an effective harmonic theory to calculate the free energy of systems with strongly anharmonic atomic vibrations, and its stochastic implementation has proved to be an efficient method to study, from first-principles, the anharmonic properties of solids. The free energy as...
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Prioritized Norms in Formal Argumentation
To resolve conflicts among norms, various nonmonotonic formalisms can be used to perform prioritized normative reasoning. Meanwhile, formal argumentation provides a way to represent nonmonotonic logics. In this paper, we propose a representation of prioritized normative reasoning by argumentation. Using hierarchical ...
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Fast and robust tensor decomposition with applications to dictionary learning
We develop fast spectral algorithms for tensor decomposition that match the robustness guarantees of the best known polynomial-time algorithms for this problem based on the sum-of-squares (SOS) semidefinite programming hierarchy. Our algorithms can decompose a 4-tensor with $n$-dimensional orthonormal components in t...
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Distributed Testing of Conductance
We study the problem of testing conductance in the setting of distributed computing and give a two-sided tester that takes $\mathcal{O}(\log(n) / (\epsilon \Phi^2))$ rounds to decide if a graph has conductance at least $\Phi$ or is $\epsilon$-far from having conductance at least $\Phi^2 / 1000$ in the distributed CON...
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Ultra high stiffness and thermal conductivity of graphene like C3N
Recently, single crystalline carbon nitride 2D material with a C3N stoichiometry has been synthesized. In this investigation, we explored the mechanical response and thermal transport along pristine, free-standing and single-layer C3N. To this aim, we conducted extensive first-principles density functional theory (DF...
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Automatic Liver Lesion Detection using Cascaded Deep Residual Networks
Automatic segmentation of liver lesions is a fundamental requirement towards the creation of computer aided diagnosis (CAD) and decision support systems (CDS). Traditional segmentation approaches depend heavily upon hand-crafted features and a priori knowledge of the user. As such, these methods are difficult to adop...
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Combinatorial metrics: MacWilliams-type identities, isometries and extension property
In this work we characterize the combinatorial metrics admitting a MacWilliams-type identity and describe the group of linear isometries of such metrics. Considering coverings that are not connected, we classify the metrics satisfying the MacWilliams extension property.
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The curtain remains open: NGC 2617 continues in a high state
Optical and near-infrared photometry, optical spectroscopy, and soft X-ray and UV monitoring of the changing look active galactic nucleus NGC 2617 show that it continues to have the appearance of a type-1 Seyfert galaxy. An optical light curve for 2010-2016 indicates that the change of type probably occurred between ...
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The topology on Berkovich affine lines over complete valuation rings
In this article, we give a full description of the topology of the one dimensional affine analytic space $\mathbb{A}_R^1$ over a complete valuation ring $R$ (i.e. a valuation ring with "real valued valuation" which is complete under the induced metric), when its field of fractions $K$ is algebraically closed. In part...
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An Original Mechanism for the Acceleration of Ultra-High-Energy Cosmic Rays
We suggest that ultra-high-energy (UHE) cosmic rays (CRs) may be accelerated in ultra-relativistic flows via a one-shot mechanism, the "espresso" acceleration, in which already-energetic particles are generally boosted by a factor of $\sim\Gamma^2$ in energy, where $\Gamma$ is the flow Lorentz factor. More precisely,...
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Expected Time to Extinction of SIS Epidemic Model Using Quasy Stationary Distribution
We study that the breakdown of epidemic depends on some parameters, that is expressed in epidemic reproduction ratio number. It is noted that when $R_0 $ exceeds 1, the stochastic model have two different results. But, eventually the extinction will be reached even though the major epidemic occurs. The question is ho...
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The gyrokinetic limit for the Vlasov-Poisson system with a point charge
We consider the asymptotics of large external magnetic field for a 2D Vlasov-Poisson system governing the evolution of a bounded density interacting with a point charge. In a suitable asymptotical regime, we show that the solution converges to a measure-valued solution of the Euler equation with a defect measure.
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Deriving Verb Predicates By Clustering Verbs with Arguments
Hand-built verb clusters such as the widely used Levin classes (Levin, 1993) have proved useful, but have limited coverage. Verb classes automatically induced from corpus data such as those from VerbKB (Wijaya, 2016), on the other hand, can give clusters with much larger coverage, and can be adapted to specific corpo...
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A propagation tool to connect remote-sensing observations with in-situ measurements of heliospheric structures
The remoteness of the Sun and the harsh conditions prevailing in the solar corona have so far limited the observational data used in the study of solar physics to remote-sensing observations taken either from the ground or from space. In contrast, the `solar wind laboratory' is directly measured in situ by a fleet of...
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Chemical-disorder-caused Medium Range Order in Covalent Glass
How atoms in covalent solids rearrange over a medium-range length-scale during amorphization is a long pursued question whose answer could profoundly shape our understanding on amorphous (a-) networks. Based on ab-intio calculations and reverse Monte Carlo simulations of experiments, we surprisingly find that even th...
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Optimal compromise between incompatible conditional probability distributions, with application to Objective Bayesian Kriging
Models are often defined through conditional rather than joint distributions, but it can be difficult to check whether the conditional distributions are compatible, i.e. whether there exists a joint probability distribution which generates them. When they are compatible, a Gibbs sampler can be used to sample from thi...
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Estimation for the Prediction of Point Processes with Many Covariates
Estimation of the intensity of a point process is considered within a nonparametric framework. The intensity measure is unknown and depends on covariates, possibly many more than the observed number of jumps. Only a single trajectory of the counting process is observed. Interest lies in estimating the intensity condi...
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Chordal SLE$_6$ explorations of a quantum disk
We consider a particular type of $\sqrt{8/3}$-Liouville quantum gravity surface called a doubly marked quantum disk (equivalently, a Brownian disk) decorated by an independent chordal SLE$_6$ curve $\eta$ between its marked boundary points. We obtain descriptions of the law of the quantum surfaces parameterized by th...
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Optimal rate list decoding over bounded alphabets using algebraic-geometric codes
We give new constructions of two classes of algebraic code families which are efficiently list decodable with small output list size from a fraction $1-R-\epsilon$ of adversarial errors where $R$ is the rate of the code, for any desired positive constant $\epsilon$. The alphabet size depends only $\epsilon$ and is ne...
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Quadratic Programming Approach to Fit Protein Complexes into Electron Density Maps
The paper investigates the problem of fitting protein complexes into electron density maps. They are represented by high-resolution cryoEM density maps converted into overlapping matrices and partly show a structure of a complex. The general purpose is to define positions of all proteins inside it. This problem is kn...
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Conditions for the equivalence between IQC and graph separation stability results
This paper provides a link between time-domain and frequency-domain stability results in the literature. Specifically, we focus on the comparison between stability results for a feedback interconnection of two nonlinear systems stated in terms of frequency-domain conditions. While the Integral Quadratic Constrain (IQ...
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Energy-Efficient Wireless Content Delivery with Proactive Caching
We propose an intelligent proactive content caching scheme to reduce the energy consumption in wireless downlink. We consider an online social network (OSN) setting where new contents are generated over time, and remain \textit{relevant} to the user for a random lifetime. Contents are downloaded to the user equipment...
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Low- and high-order gravitational harmonics of rigidly rotating Jupiter
The Juno Orbiter has provided improved estimates of the even gravitational harmonics J2 to J8 of Jupiter. To compute higher-order moments, new methods such as the Concentric Maclaurin Spheroids (CMS) method have been developed which surpass the so far commonly used Theory of Figures (ToF) method in accuracy. This pro...
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Language Modeling with Generative Adversarial Networks
Generative Adversarial Networks (GANs) have been promising in the field of image generation, however, they have been hard to train for language generation. GANs were originally designed to output differentiable values, so discrete language generation is challenging for them which causes high levels of instability in ...
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How AD Can Help Solve Differential-Algebraic Equations
A characteristic feature of differential-algebraic equations is that one needs to find derivatives of some of their equations with respect to time, as part of so called index reduction or regularisation, to prepare them for numerical solution. This is often done with the help of a computer algebra system. We show in ...
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Secure Coding Practices in Java: Challenges and Vulnerabilities
Java platform and third-party libraries provide various security features to facilitate secure coding. However, misusing these features can cost tremendous time and effort of developers or cause security vulnerabilities in software. Prior research was focused on the misuse of cryptography and SSL APIs, but did not ex...
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Complex Urban LiDAR Data Set
This paper presents a Light Detection and Ranging (LiDAR) data set that targets complex urban environments. Urban environments with high-rise buildings and congested traffic pose a significant challenge for many robotics applications. The presented data set is unique in the sense it is able to capture the genuine fea...
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Blind Source Separation Using Mixtures of Alpha-Stable Distributions
We propose a new blind source separation algorithm based on mixtures of alpha-stable distributions. Complex symmetric alpha-stable distributions have been recently showed to better model audio signals in the time-frequency domain than classical Gaussian distributions thanks to their larger dynamic range. However, inf...
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Student and instructor framing in upper-division physics
Upper-division physics students spend much of their time solving problems. In addition to their basic skills and background, their epistemic framing can form an important part of their ability to learn physics from these problems. Encouraging students to move toward productive framing may help them solve problems. Th...
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Deep Generative Model using Unregularized Score for Anomaly Detection with Heterogeneous Complexity
Accurate and automated detection of anomalous samples in a natural image dataset can be accomplished with a probabilistic model for end-to-end modeling of images. Such images have heterogeneous complexity, however, and a probabilistic model overlooks simply shaped objects with small anomalies. This is because the pro...
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Non-collinear magnetic structure and multipolar order in Eu$_2$Ir$_2$O$_7$
The magnetic properties of the pyrochlore iridate material Eu$_2$Ir$_2$O$_7$ (5$d^5$) have been studied based on the first principle calculations, where the crystal field splitting $\Delta$, spin-orbit coupling (SOC) $\lambda$ and Coulomb interaction $U$ within Ir 5$d$ orbitals are all playing significant roles. The ...
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OGLE-2013-BLG-1761Lb: A Massive Planet Around an M/K Dwarf
We report the discovery and the analysis of the planetary microlensing event, OGLE-2013-BLG-1761. There are some degenerate solutions in this event because the planetary anomaly is only sparsely sampled. But the detailed light curve analysis ruled out all stellar binary models and shows that the lens to be a planetar...
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Phase-Aware Single-Channel Speech Enhancement with Modulation-Domain Kalman Filtering
We present a single-channel phase-sensitive speech enhancement algorithm that is based on modulation-domain Kalman filtering and on tracking the speech phase using circular statistics. With Kalman filtering, using that speech and noise are additive in the complex STFT domain, the algorithm tracks the speech log-spect...
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Reduction and specialization of hyperelliptic continued fractions
For a monic polynomial $D(X)$ of even degree, express $\sqrt D$ as a Laurent series in $X^{-1}$; this yields a continued fraction expansion (similar to continued fractions of real numbers): \[\sqrt D=a_0+\dfrac{1}{a_1+\dfrac{1}{a_2+\dfrac{1}{\ddots}}},\quad a_i\text{ polynomials in }X.\] Such continued fractions were...
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Three years of SPHERE: the latest view of the morphology and evolution of protoplanetary discs
Spatially resolving the immediate surroundings of young stars is a key challenge for the planet formation community. SPHERE on the VLT represents an important step forward by increasing the opportunities offered by optical or near-infrared imaging instruments to image protoplanetary discs. The Guaranteed Time Observa...
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Tensor Methods for Nonlinear Matrix Completion
In the low rank matrix completion (LRMC) problem, the low rank assumption means that the columns (or rows) of the matrix to be completed are points on a low-dimensional linear algebraic variety. This paper extends this thinking to cases where the columns are points on a low-dimensional nonlinear algebraic variety, a ...
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Visual Interaction Networks
From just a glance, humans can make rich predictions about the future state of a wide range of physical systems. On the other hand, modern approaches from engineering, robotics, and graphics are often restricted to narrow domains and require direct measurements of the underlying states. We introduce the Visual Intera...
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Using polarimetry to retrieve the cloud coverage of Earth-like exoplanets
Context. Clouds have already been detected in exoplanetary atmospheres. They play crucial roles in a planet's atmosphere and climate and can also create ambiguities in the determination of atmospheric parameters such as trace gas mixing ratios. Knowledge of cloud properties is required when assessing the habitability...
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Dirac nodal lines and induced spin Hall effect in metallic rutile oxides
We have found Dirac nodal lines (DNLs) in the band structures of metallic rutile oxides IrO$_2$, OsO$_2$, and RuO$_2$ and revealed a large spin Hall conductivity contributed by these nodal lines, which explains a strong spin Hall effect (SHE) of IrO$_2$ discovered recently. Two types of DNLs exist. The first type for...
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Chaotic Dynamics Enhance the Sensitivity of Inner Ear Hair Cells
Hair cells of the auditory and vestibular systems are capable of detecting sounds that induce sub-nanometer vibrations of the hair bundle, below the stochastic noise levels of the surrounding fluid. Hair cells of certain species are also known to oscillate without external stimulation, indicating the presence of an u...
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A Robot Localization Framework Using CNNs for Object Detection and Pose Estimation
External localization is an essential part for the indoor operation of small or cost-efficient robots, as they are used, for example, in swarm robotics. We introduce a two-stage localization and instance identification framework for arbitrary robots based on convolutional neural networks. Object detection is performe...
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Executable Trigger-Action Comments
Natural language elements, e.g., todo comments, are frequently used to communicate among the developers and to describe tasks that need to be performed (actions) when specific conditions hold in the code repository (triggers). As projects evolve, development processes change, and development teams reorganize, these c...
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Cardinal Virtues: Extracting Relation Cardinalities from Text
Information extraction (IE) from text has largely focused on relations between individual entities, such as who has won which award. However, some facts are never fully mentioned, and no IE method has perfect recall. Thus, it is beneficial to also tap contents about the cardinalities of these relations, for example, ...
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A Decision Tree Approach to Predicting Recidivism in Domestic Violence
Domestic violence (DV) is a global social and public health issue that is highly gendered. Being able to accurately predict DV recidivism, i.e., re-offending of a previously convicted offender, can speed up and improve risk assessment procedures for police and front-line agencies, better protect victims of DV, and po...
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On the Necessity of Superparametric Geometry Representation for Discontinuous Galerkin Methods on Domains with Curved Boundaries
We provide numerical evidence demonstrating the necessity of employing a superparametric geometry representation in order to obtain optimal convergence orders on two-dimensional domains with curved boundaries when solving the Euler equations using Discontinuous Galerkin methods. However, concerning the obtention of o...
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Low-dose cryo electron ptychography via non-convex Bayesian optimization
Electron ptychography has seen a recent surge of interest for phase sensitive imaging at atomic or near-atomic resolution. However, applications are so far mainly limited to radiation-hard samples because the required doses are too high for imaging biological samples at high resolution. We propose the use of non-conv...
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Efficient Charge Collection in Coplanar Grid Radiation Detectors
We have modeled laser-induced transient current waveforms in radiation coplanar grid detectors. Poisson's equation has been solved by finite element method and currents induced by photo-generated charge were obtained using Shockley-Ramo theorem. The spectral response on a radiation flux has been modeled by Monte-Carl...
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Thermalization near integrability in a dipolar quantum Newton's cradle
Isolated quantum many-body systems with integrable dynamics generically do not thermalize when taken far from equilibrium. As one perturbs such systems away from the integrable point, thermalization sets in, but the nature of the crossover from integrable to thermalizing behavior is an unresolved and actively discuss...
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Hausdorff dimension of the boundary of bubbles of additive Brownian motion and of the Brownian sheet
We first consider the additive Brownian motion process $(X(s_1,s_2),\ (s_1,s_2) \in \mathbb{R}^2)$ defined by $X(s_1,s_2) = Z_1(s_1) - Z_2 (s_2)$, where $Z_1$ and $Z_2 $ are two independent (two-sided) Brownian motions. We show that with probability one, the Hausdorff dimension of the boundary of any connected compon...
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Inverse mean curvature flow in quaternionic hyperbolic space
In this paper we complete the study started in [Pi2] of evolution by inverse mean curvature flow of star-shaped hypersurface in non-compact rank one symmetric spaces. We consider the evolution by inverse mean curvature flow of a closed, mean convex and star-shaped hypersurface in the quaternionic hyperbolic space. We...
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Mosquito detection with low-cost smartphones: data acquisition for malaria research
Mosquitoes are a major vector for malaria, causing hundreds of thousands of deaths in the developing world each year. Not only is the prevention of mosquito bites of paramount importance to the reduction of malaria transmission cases, but understanding in more forensic detail the interplay between malaria, mosquito v...
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