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Gradient descent GAN optimization is locally stable
Despite the growing prominence of generative adversarial networks (GANs), optimization in GANs is still a poorly understood topic. In this paper, we analyze the "gradient descent" form of GAN optimization i.e., the natural setting where we simultaneously take small gradient steps in both generator and discriminator p...
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Transition rates and radiative lifetimes of Ca I
We tabulate spontaneous emission rates for all possible 811 electric-dipole-allowed transitions between the 75 lowest-energy states of Ca I. These involve the $4sns$ ($n=4-8$), $4snp$ ($n=4-7$), $4snd$ ($n=3-6$), $4snf$ ($n=4-6$), $4p^2$, and $3d4p$ electronic configurations. We compile the transition rates by carryi...
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Defect entropies and enthalpies in Barium Fluoride
Various experimental techniques, have revealed that the predominant intrinsic point defects in BaF$_2$ are anion Frenkel defects. Their formation enthalpy and entropy as well as the corresponding parameters for the fluorine vacancy and fluorine interstitial motion have been determined. In addition, low temperature di...
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Surprise-Based Intrinsic Motivation for Deep Reinforcement Learning
Exploration in complex domains is a key challenge in reinforcement learning, especially for tasks with very sparse rewards. Recent successes in deep reinforcement learning have been achieved mostly using simple heuristic exploration strategies such as $\epsilon$-greedy action selection or Gaussian control noise, but ...
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Local and collective magnetism of EuFe$_2$As$_2$
We present an experimental study of the local and collective magnetism of $\mathrm{EuFe_2As_2}$, that is isostructural with the high temperature superconductor parent compound $\mathrm{BaFe_2As_2}$. In contrast to $\mathrm{BaFe_2As_2}$, where only Fe spins order, $\mathrm{EuFe_2As_2}$ has an additional magnetic trans...
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Newton slopes for twisted Artin--Schreier--Witt Towers
We fix a monic polynomial $f(x) \in \mathbb F_q[x]$ over a finite field of characteristic $p$ of degree relatively prime to $p$. Let $a\mapsto \omega(a)$ be the Teichmüller lift of $\mathbb F_q$, and let $\chi:\mathbb{Z}\to \mathbb C_p^\times$ be a finite character of $\mathbb Z_p$. The $L$-function associated to the...
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Active model learning and diverse action sampling for task and motion planning
The objective of this work is to augment the basic abilities of a robot by learning to use new sensorimotor primitives to enable the solution of complex long-horizon problems. Solving long-horizon problems in complex domains requires flexible generative planning that can combine primitive abilities in novel combinati...
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End-to-end distance and contour length distribution functions of DNA helices
We present a computational method to evaluate the end-to-end and the contour length distribution functions of short DNA molecules described by a mesoscopic Hamiltonian. The method generates a large statistical ensemble of possible configurations for each dimer in the sequence, selects the global equilibrium twist con...
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Online Estimation of Multiple Dynamic Graphs in Pattern Sequences
Many time-series data including text, movies, and biological signals can be represented as sequences of correlated binary patterns. These patterns may be described by weighted combinations of a few dominant structures that underpin specific interactions among the binary elements. To extract the dominant correlation s...
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Fluid Communities: A Competitive, Scalable and Diverse Community Detection Algorithm
We introduce a community detection algorithm (Fluid Communities) based on the idea of fluids interacting in an environment, expanding and contracting as a result of that interaction. Fluid Communities is based on the propagation methodology, which represents the state-of-the-art in terms of computational cost and sca...
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Identification of Dynamic Systems with Interval Arithmetic
This paper aims to identify three electrical systems: a series RLC circuit, a motor/generator coupled system, and the Duffing-Ueda oscillator. In order to obtain the system's models was used the error reduction ratio and the Akaike information criterion. Our approach to handle the numerical errors was the interval ar...
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Four Fundamental Questions in Probability Theory and Statistics
This study has the purpose of addressing four questions that lie at the base of the probability theory and statistics, and includes two main steps. As first, we conduct the textual analysis of the most significant works written by eminent probability theorists. The textual analysis turns out to be a rather innovative...
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Connections on parahoric torsors over curves
We define parahoric $\cG$--torsors for certain Bruhat--Tits group scheme $\cG$ on a smooth complex projective curve $X$ when the weights are real, and also define connections on them. We prove that a $\cG$--torsor is given by a homomorphism from $\pi_1(X\setminus D)$ to a maximal compact subgroup of $G$, where $D\, \...
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On Reduced Input-Output Dynamic Mode Decomposition
The identification of reduced-order models from high-dimensional data is a challenging task, and even more so if the identified system should not only be suitable for a certain data set, but generally approximate the input-output behavior of the data source. In this work, we consider the input-output dynamic mode dec...
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Safety-Aware Apprenticeship Learning
Apprenticeship learning (AL) is a kind of Learning from Demonstration techniques where the reward function of a Markov Decision Process (MDP) is unknown to the learning agent and the agent has to derive a good policy by observing an expert's demonstrations. In this paper, we study the problem of how to make AL algori...
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Solitary wave solutions and their interactions for fully nonlinear water waves with surface tension in the generalized Serre equations
Some effects of surface tension on fully-nonlinear, long, surface water waves are studied by numerical means. The differences between various solitary waves and their interactions in subcritical and supercritical surface tension regimes are presented. Analytical expressions for new peaked travelling wave solutions ar...
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Relative weak mixing of W*-dynamical systems via joinings
A characterization of relative weak mixing in W*-dynamical systems in terms of a relatively independent joining is proven.
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An assessment of Fe XX - Fe XXII emission lines in SDO/EVE data as diagnostics for high density solar flare plasmas using EUVE stellar observations
The Extreme Ultraviolet Variability Experiment (EVE) on the Solar Dynamics Observatory obtains extreme-ultraviolet (EUV) spectra of the full-disk Sun at a spectral resolution of ~1 A and cadence of 10 s. Such a spectral resolution would normally be considered to be too low for the reliable determination of electron d...
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Multi-Scale Spatially Weighted Local Histograms in O(1)
Weighting pixel contribution considering its location is a key feature in many fundamental image processing tasks including filtering, object modeling and distance matching. Several techniques have been proposed that incorporate Spatial information to increase the accuracy and boost the performance of detection, trac...
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A note on minimal dispersion of point sets in the unit cube
We study the dispersion of a point set, a notion closely related to the discrepancy. Given a real $r\in (0,1)$ and an integer $d\geq 2$, let $N(r,d)$ denote the minimum number of points inside the $d$-dimensional unit cube $[0,1]^d$ such that they intersect every axis-aligned box inside $[0,1]^d$ of volume greater th...
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Limit theorems in bi-free probability theory
In this paper additive bi-free convolution is defined for general Borel probability measures, and the limiting distributions for sums of bi-free pairs of selfadjoint commuting random variables in an infinitesimal triangular array are determined. These distributions are characterized by their bi-freely infinite divisi...
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Axiomatisability and hardness for universal Horn classes of hypergraphs
We characterise finite axiomatisability and intractability of deciding membership for universal Horn classes generated by finite loop-free hypergraphs.
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Snyder Like Modified Gravity in Newton's Spacetime
This work is focused on searching a geodesic interpretation of the dynamics of a particle under the effects of a Snyder like deformation in the background of the Kepler problem. In order to accomplish that task, a newtonian spacetime is used. Newtonian spacetime is not a metric manifold, but allows to introduce a tor...
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Dissipatively Coupled Waveguide Networks for Coherent Diffusive Photonics
A photonic circuit is generally described as a structure in which light propagates by unitary exchange and transfers reversibly between channels. In contrast, the term `diffusive' is more akin to a chaotic propagation in scattering media, where light is driven out of coherence towards a thermal mixture. Based on the ...
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Inadequate Risk Analysis Might Jeopardize The Functional Safety of Modern Systems
In the early 90s, researchers began to focus on security as an important property to address in combination with safety. Over the years, researchers have proposed approaches to harmonize activities within the safety and security disciplines. Despite the academic efforts to identify interdependencies and to propose co...
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Simultaneous determination of the drift and diffusion coefficients in stochastic differential equations
In this work, we consider a one-dimensional It{ô} diffusion process X t with possibly nonlinear drift and diffusion coefficients. We show that, when the diffusion coefficient is known, the drift coefficient is uniquely determined by an observation of the expectation of the process during a small time interval, and st...
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A compactness theorem for four-dimensional shrinking gradient Ricci solitons
Haslhofer and Müller proved a compactness Theorem for four-dimensional shrinking gradient Ricci solitons, with the only assumption being that the entropy is uniformly bounded from below. However, the limit in their result could possibly be an orbifold Ricci shrinker. In this paper we prove a compactness theorem for n...
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Demand-Independent Optimal Tolls
Wardrop equilibria in nonatomic congestion games are in general inefficient as they do not induce an optimal flow that minimizes the total travel time. Network tolls are a prominent and popular way to induce an optimum flow in equilibrium. The classical approach to find such tolls is marginal cost pricing which requi...
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An analytic formulation for positive-unlabeled learning via weighted integral probability metric
We consider the problem of learning a binary classifier from only positive and unlabeled observations (PU learning). Although recent research in PU learning has succeeded in showing theoretical and empirical performance, most existing algorithms need to solve either a convex or a non-convex optimization problem and t...
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Benchmarking Data Analysis and Machine Learning Applications on the Intel KNL Many-Core Processor
Knights Landing (KNL) is the code name for the second-generation Intel Xeon Phi product family. KNL has generated significant interest in the data analysis and machine learning communities because its new many-core architecture targets both of these workloads. The KNL many-core vector processor design enables it to e...
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A Proof of the Conjecture of Lehmer and of the Conjecture of Schinzel-Zassenhaus
The conjecture of Lehmer is proved to be true. The proof mainly relies upon: (i) the properties of the Parry Upper functions $f_{house(\alpha)}(z)$ associated with the dynamical zeta functions $\zeta_{house(\alpha)}(z)$ of the Rényi--Parry arithmetical dynamical systems, for $\alpha$ an algebraic integer $\alpha$ of ...
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Pseudo asymptotically periodic solutions for fractional integro-differential neutral equations
In this paper, we study the existence and uniqueness of pseudo $S$-asymptotically $\omega$-periodic mild solutions of class $r$ for fractional integro-differential neutral equations. An example is presented to illustrate the application of the abstract results.
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Updating the silent speech challenge benchmark with deep learning
The 2010 Silent Speech Challenge benchmark is updated with new results obtained in a Deep Learning strategy, using the same input features and decoding strategy as in the original article. A Word Error Rate of 6.4% is obtained, compared to the published value of 17.4%. Additional results comparing new auto-encoder-ba...
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Magnetic field control of cycloidal domains and electric polarization in multiferroic BiFeO$_3$
The magnetic field induced rearrangement of the cycloidal spin structure in ferroelectric mono-domain single crystals of the room-temperature multiferroic BiFeO$_3$ is studied using small-angle neutron scattering (SANS). The cycloid propagation vectors are observed to rotate when magnetic fields applied perpendicular...
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DepQBF 6.0: A Search-Based QBF Solver Beyond Traditional QCDCL
We present the latest major release version 6.0 of the quantified Boolean formula (QBF) solver DepQBF, which is based on QCDCL. QCDCL is an extension of the conflict-driven clause learning (CDCL) paradigm implemented in state of the art propositional satisfiability (SAT) solvers. The Q-resolution calculus (QRES) is a...
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On Optimization of Radiative Dipole Body Array Coils for 7 Tesla MRI
In this contribution we present numerical and experimental results of a parametric study of radiative dipole antennas in a phased array configuration for efficient body magnetic resonance imaging at 7T via parallel transmit. For magnetic resonance imaging (MRI) at ultrahigh fields (7T and higher) dipole antennas are ...
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Speaking Style Authentication Using Suprasegmental Hidden Markov Models
The importance of speaking style authentication from human speech is gaining an increasing attention and concern from the engineering community. The importance comes from the demand to enhance both the naturalness and efficiency of spoken language human-machine interface. Our work in this research focuses on proposin...
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A fixed point formula and Harish-Chandra's character formula
The main result in this paper is a fixed point formula for equivariant indices of elliptic differential operators, for proper actions by connected semisimple Lie groups on possibly noncompact manifolds, with compact quotients. For compact groups and manifolds, this reduces to the Atiyah-Segal-Singer fixed point formu...
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The phonon softening due to melting of the ferromagnetic order in elemental iron
We study the fundamental question of the lattice dynamics of a metallic ferromagnet in the regime where the static long range magnetic order is replaced by the fluctuating local moments embedded in a metallic host. We use the \textit{ab initio} Density Functional Theory(DFT)+embedded Dynamical Mean-Field Theory(eDMFT...
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Decomposing manifolds into Cartesian products
The decomposability of a Cartesian product of two nondecomposable manifolds into products of lower dimensional manifolds is studied. For 3-manifolds we obtain an analog of a result due to Borsuk for surfaces, and in higher dimensions we show that similar analogs do not exist unless one imposes further restrictions su...
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Performance of the MAGIC telescopes under moonlight
MAGIC, a system of two imaging atmospheric Cherenkov telescopes, achieves its best performance under dark conditions, i.e. in absence of moonlight or twilight. Since operating the telescopes only during dark time would severely limit the duty cycle, observations are also performed when the Moon is present in the sky....
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Mastering Heterogeneous Behavioural Models
Heterogeneity is one important feature of complex systems, leading to the complexity of their construction and analysis. Moving the heterogeneity at model level helps in mastering the difficulty of composing heterogeneous models which constitute a large system. We propose a method made of an algebra and structure mor...
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Approximation and Convergence Properties of Generative Adversarial Learning
Generative adversarial networks (GAN) approximate a target data distribution by jointly optimizing an objective function through a "two-player game" between a generator and a discriminator. Despite their empirical success, however, two very basic questions on how well they can approximate the target distribution rema...
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Driver Distraction Identification with an Ensemble of Convolutional Neural Networks
The World Health Organization (WHO) reported 1.25 million deaths yearly due to road traffic accidents worldwide and the number has been continuously increasing over the last few years. Nearly fifth of these accidents are caused by distracted drivers. Existing work of distracted driver detection is concerned with a sm...
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Driver Action Prediction Using Deep (Bidirectional) Recurrent Neural Network
Advanced driver assistance systems (ADAS) can be significantly improved with effective driver action prediction (DAP). Predicting driver actions early and accurately can help mitigate the effects of potentially unsafe driving behaviors and avoid possible accidents. In this paper, we formulate driver action prediction...
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A simple neural network module for relational reasoning
Relational reasoning is a central component of generally intelligent behavior, but has proven difficult for neural networks to learn. In this paper we describe how to use Relation Networks (RNs) as a simple plug-and-play module to solve problems that fundamentally hinge on relational reasoning. We tested RN-augmented...
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Computing low-rank approximations of large-scale matrices with the Tensor Network randomized SVD
We propose a new algorithm for the computation of a singular value decomposition (SVD) low-rank approximation of a matrix in the Matrix Product Operator (MPO) format, also called the Tensor Train Matrix format. Our tensor network randomized SVD (TNrSVD) algorithm is an MPO implementation of the randomized SVD algorit...
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Path Cover and Path Pack Inequalities for the Capacitated Fixed-Charge Network Flow Problem
Capacitated fixed-charge network flows are used to model a variety of problems in telecommunication, facility location, production planning and supply chain management. In this paper, we investigate capacitated path substructures and derive strong and easy-to-compute \emph{path cover and path pack inequalities}. Thes...
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Bridging the Gap Between Value and Policy Based Reinforcement Learning
We establish a new connection between value and policy based reinforcement learning (RL) based on a relationship between softmax temporal value consistency and policy optimality under entropy regularization. Specifically, we show that softmax consistent action values correspond to optimal entropy regularized policy p...
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Chalcogenide Glass-on-Graphene Photonics
Two-dimensional (2-D) materials are of tremendous interest to integrated photonics given their singular optical characteristics spanning light emission, modulation, saturable absorption, and nonlinear optics. To harness their optical properties, these atomically thin materials are usually attached onto prefabricated ...
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Speaker verification using end-to-end adversarial language adaptation
In this paper we investigate the use of adversarial domain adaptation for addressing the problem of language mismatch between speaker recognition corpora. In the context of speaker verification, adversarial domain adaptation methods aim at minimizing certain divergences between the distribution that the utterance-lev...
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Real elliptic curves and cevian geometry
We study the elliptic curve $E_a: (ax+1)y^2+(ax+1)(x-1)y+x^2-x=0$, which we call the geometric normal form of an elliptic curve. We show that any elliptic curve whose $j$-invariant is real is isomorphic to a curve $E_a$ in geometric normal form, and show that for $a \notin \{0, -1, -9\}$, the points on $E_a$, minus a...
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Omni $n$-Lie algebras and linearization of higher analogues of Courant algebroids
In this paper, we introduce the notion of an omni $n$-Lie algebra and show that they are linearization of higher analogues of standard Courant algebroids. We also introduce the notion of a nonabelian omni $n$-Lie algebra and show that they are linearization of higher analogues of Courant algebroids associated to Namb...
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Musical Instrument Recognition Using Their Distinctive Characteristics in Artificial Neural Networks
In this study an Artificial Neural Network was trained to classify musical instruments, using audio samples transformed to the frequency domain. Different features of the sound, in both time and frequency domain, were analyzed and compared in relation to how much information that could be derived from that limited da...
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Revealing structure components of the retina by deep learning networks
Deep convolutional neural networks (CNNs) have demonstrated impressive performance on visual object classification tasks. In addition, it is a useful model for predication of neuronal responses recorded in visual system. However, there is still no clear understanding of what CNNs learn in terms of visual neuronal cir...
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Generalized Yangians and their Poisson counterparts
By a generalized Yangian we mean a Yangian-like algebra of one of two classes. One of these classes consists of the so-called braided Yangians, introduced in our previous paper. The braided Yangians are in a sense similar to the reflection equation algebra. The generalized Yangians of second class, called the Yangian...
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Asymptotics of Hankel determinants with a one-cut regular potential and Fisher-Hartwig singularities
We obtain asymptotics of large Hankel determinants whose weight depends on a one-cut regular potential and any number of Fisher-Hartwig singularities. This generalises two results: 1) a result of Berestycki, Webb and Wong [5] for root-type singularities, and 2) a result of Its and Krasovsky [37] for a Gaussian weight...
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Beyond linear galaxy alignments
Galaxy intrinsic alignments (IA) are a critical uncertainty for current and future weak lensing measurements. We describe a perturbative expansion of IA, analogous to the treatment of galaxy biasing. From an astrophysical perspective, this model includes the expected large-scale alignment mechanisms for galaxies that...
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Modelling thermo-electro-mechanical effects in orthotropic cardiac tissue
In this paper we introduce a new mathematical model for the active contraction of cardiac muscle, featuring different thermo-electric and nonlinear conductivity properties. The passive hyperelastic response of the tissue is described by an orthotropic exponential model, whereas the ionic activity dictates active cont...
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Debt-Prone Bugs: Technical Debt in Software Maintenance
Fixing bugs is an important phase in software development and maintenance. In practice, the process of bug fixing may conflict with the release schedule. Such confliction leads to a trade-off between software quality and release schedule, which is known as the technical debt metaphor. In this article, we propose the ...
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Khovanov-Rozansky homology and higher Catalan sequences
We give a simple recursion which computes the triply graded Khovanov-Rozansky homology of several infinite families of knots and links, including the $(n,nm\pm 1)$ and $(n,nm)$ torus links for $n,m\geq 1$. We interpret our results in terms of Catalan combinatorics, proving a conjecture of Gorsky's. Our computations a...
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New face of multifractality: Multi-branched left-sidedness and phase transitions in multifractality of interevent times
We develop an extended multifractal analysis based on the Legendre-Fenchel transform rather than the routinely used Legendre transform. We apply this analysis to studying time series consisting of inter-event times. As a result, we discern the non-monotonic behavior of the generalized Hurst exponent - the fundamental...
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Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions
By building up on the recent theory that established the connection between implicit generative modeling and optimal transport, in this study, we propose a novel parameter-free algorithm for learning the underlying distributions of complicated datasets and sampling from them. The proposed algorithm is based on a func...
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Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization
Iterative Hard Thresholding (IHT) is a class of projected gradient descent methods for optimizing sparsity-constrained minimization models, with the best known efficiency and scalability in practice. As far as we know, the existing IHT-style methods are designed for sparse minimization in primal form. It remains open...
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Binary Ensemble Neural Network: More Bits per Network or More Networks per Bit?
Binary neural networks (BNN) have been studied extensively since they run dramatically faster at lower memory and power consumption than floating-point networks, thanks to the efficiency of bit operations. However, contemporary BNNs whose weights and activations are both single bits suffer from severe accuracy degrad...
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Generalized connected sum formula for the Arnold invariants of generic plane curves
We define the generalized connected sum for generic closed plane curves, generalizing the strange sum defined by Arnold, and completely describe how the Arnold invariants $J^{\pm}$ and $\mathit{St}$ behave under the generalized connected sums.
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Smart patterned surfaces with programmable thermal emissivity and their design through combinatorial strategies
The emissivity of common materials remains constant with temperature variations, and cannot drastically change. However, it is possible to design its entire behaviour as a function of temperature, and to significantly modify the thermal emissivity of a surface through the combination of different materials and patter...
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STAR: Spatio-Temporal Altimeter Waveform Retracking using Sparse Representation and Conditional Random Fields
Satellite radar altimetry is one of the most powerful techniques for measuring sea surface height variations, with applications ranging from operational oceanography to climate research. Over open oceans, altimeter return waveforms generally correspond to the Brown model, and by inversion, estimated shape parameters ...
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Magnetization jump in one dimensional $J-Q_{2}$ model with anisotropic exchange
We investigate the adiabatic magnetization process of the one-dimensional $J-Q_{2}$ model with XXZ anisotropy $g$ in an external magnetic field $h$ by using density matrix renormalization group (DMRG) method. According to the characteristic of the magnetization curves, we draw a magnetization phase diagram consisting...
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CoMID: Context-based Multi-Invariant Detection for Monitoring Cyber-Physical Software
Cyber-physical software continually interacts with its physical environment for adaptation in order to deliver smart services. However, the interactions can be subject to various errors when the software's assumption on its environment no longer holds, thus leading to unexpected misbehavior or even failure. To addres...
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Asymptotics of multivariate contingency tables with fixed marginals
We consider the asymptotic distribution of a cell in a 2 x ... x 2 contingency table as the fixed marginal totals tend to infinity. The asymptotic order of the cell variance is derived and a useful diagnostic is given for determining whether the cell has a Poisson limit or a Gaussian limit. There are three forms of P...
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On the Faithfulness of 1-dimensional Topological Quantum Field Theories
This paper explores 1-dimensional topological quantum field theories. We separately deal with strict and strong 1-dimensional topological quantum field theories. The strict one is regarded as a symmetric monoidal functor between the category of 1-cobordisms and the category of matrices, and the strong one is a symmet...
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Distribution of the periodic points of the Farey map
We expand the cross section of the geodesic flow in the tangent bundle of the modular surface given by Series to produce another section whose return map under the geodesic flow is a double cover of the natural extension of the Farey map. We use this cross section to extend the correspondence between the closed geode...
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Marangoni effects on a thin liquid film coating a sphere with axial or radial thermal gradients
We study the time evolution of a thin liquid film coating the outer surface of a sphere in the presence of gravity, surface tension and thermal gradients. We derive the fourth-order nonlinear partial differential equation that models the thin film dynamics, including Marangoni terms arising from the dependence of sur...
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Fooling the classifier: Ligand antagonism and adversarial examples
Machine learning algorithms are sensitive to so-called adversarial perturbations. This is reminiscent of cellular decision-making where antagonist ligands may prevent correct signaling, like during the early immune response. We draw a formal analogy between neural networks used in machine learning and the general cla...
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A Simplified Approach to Analyze Complementary Sensitivity Trade-offs in Continuous-Time and Discrete-Time Systems
A simplified approach is proposed to investigate the continuous-time and discrete-time complementary sensitivity Bode integrals (CSBIs) in this note. For continuous-time feedback systems with unbounded frequency domain, the CSBI weighted by $1/\omega^2$ is considered, where this simplified method reveals a more expli...
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Comparing Graph Clusterings: Set partition measures vs. Graph-aware measures
In this paper, we propose a family of graph partition similarity measures that take the topology of the graph into account. These graph-aware measures are alternatives to using set partition similarity measures that are not specifically designed for graph partitions. The two types of measures, graph-aware and set par...
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Competitive Resource Allocation in HetNets: the Impact of Small-cell Spectrum Constraints and Investment Costs
Heterogeneous wireless networks with small-cell deployments in licensed and unlicensed spectrum bands are a promising approach for expanding wireless connectivity and service. As a result, wireless service providers (SPs) are adding small-cells to augment their existing macro-cell deployments. This added flexibility ...
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Gradient Reversal Against Discrimination
No methods currently exist for making arbitrary neural networks fair. In this work we introduce GRAD, a new and simplified method to producing fair neural networks that can be used for auto-encoding fair representations or directly with predictive networks. It is easy to implement and add to existing architectures, h...
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Non-commutative crepant resolutions for some toric singularities I
We give a criterion for the existence of non-commutative crepant resolutions (NCCR's) for certain toric singularities. In particular we recover Broomhead's result that a 3-dimensional toric Gorenstein singularity has a NCCR. Our result also yields the existence of a NCCR for a 4-dimensional toric Gorenstein singulari...
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High temperature pairing in a strongly interacting two-dimensional Fermi gas
We observe many-body pairing in a two-dimensional gas of ultracold fermionic atoms at temperatures far above the critical temperature for superfluidity. For this, we use spatially resolved radio-frequency spectroscopy to measure pairing energies spanning a wide range of temperatures and interaction strengths. In the ...
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Untangling the hairball: fitness based asymptotic reduction of biological networks
Complex mathematical models of interaction networks are routinely used for prediction in systems biology. However, it is difficult to reconcile network complexities with a formal understanding of their behavior. Here, we propose a simple procedure (called $\bar \varphi$) to reduce biological models to functional subm...
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Exotica and the status of the strong cosmic censor conjecture in four dimensions
An immense class of physical counterexamples to the four dimensional strong cosmic censor conjecture---in its usual broad formulation---is exhibited. More precisely, out of any closed and simply connected 4-manifold an open Ricci-flat Lorentzian 4-manifold is constructed which is not globally hyperbolic and no pertur...
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Centralities in Simplicial Complexes
Complex networks can be used to represent complex systems which originate in the real world. Here we study a transformation of these complex networks into simplicial complexes, where cliques represent the simplices of the complex. We extend the concept of node centrality to that of simplicial centrality and study sev...
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The Samuel realcompactification
For a uniform space (X, $\mu$), we introduce a realcompactification of X by means of the family $U_{\mu}(X)$ of all the real-valued uniformly continuous functions, in the same way that the known Samuel compactification is given by $U^{*}_{\mu}(X)$ the set of all the bounded functions in $U_{\mu}(X)$. We will call it ...
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Segmented Terahertz Electron Accelerator and Manipulator (STEAM)
Acceleration and manipulation of ultrashort electron bunches are the basis behind electron and X-ray devices used for ultrafast, atomic-scale imaging and spectroscopy. Using laser-generated THz drivers enables intrinsic synchronization as well as dramatic gains in field strengths, field gradients and component compac...
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The $2$-nd Hessian type equation on almost Hermitian manifolds
In this paper, we derive the second order estimate to the $2$-nd Hessian type equation on a compact almost Hermitian manifold.
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Learning graphs from data: A signal representation perspective
The construction of a meaningful graph topology plays a crucial role in the effective representation, processing, analysis and visualization of structured data. When a natural choice of the graph is not readily available from the data sets, it is thus desirable to infer or learn a graph topology from the data. In thi...
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Universal edge transport in interacting Hall systems
We study the edge transport properties of $2d$ interacting Hall systems, displaying single-mode chiral edge currents. For this class of many-body lattice models, including for instance the interacting Haldane model, we prove the quantization of the edge charge conductance and the bulk-edge correspondence. Instead, th...
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Brownian dynamics of elongated particles in a quasi-2D isotropic liquid
We demonstrate experimentally that the long-range hydrodynamic interactions in an incompressible quasi 2D isotropic fluid result in an anisotropic viscous drag acting on elongated particles. The anisotropy of the drag is increasing with increasing ratio of the particle length to the hydrodynamic scale given by the Sa...
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Photonic Band Structure of Two-dimensional Atomic Lattices
Two-dimensional atomic arrays exhibit a number of intriguing quantum optical phenomena, including subradiance, nearly perfect reflection of radiation and long-lived topological edge states. Studies of emission and scattering of photons in such lattices require complete treatment of the radiation pattern from individu...
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Multifractal analysis of the time series of daily means of wind speed in complex regions
In this paper, we applied the multifractal detrended fluctuation analysis to the daily means of wind speed measured by 119 weather stations distributed over the territory of Switzerland. The analysis was focused on the inner time fluctuations of wind speed, which could be more linked with the local conditions of the ...
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Deep Episodic Value Iteration for Model-based Meta-Reinforcement Learning
We present a new deep meta reinforcement learner, which we call Deep Episodic Value Iteration (DEVI). DEVI uses a deep neural network to learn a similarity metric for a non-parametric model-based reinforcement learning algorithm. Our model is trained end-to-end via back-propagation. Despite being trained using the mo...
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Disproval of the validated planets K2-78b, K2-82b, and K2-92b
Transiting super-Earths orbiting bright stars in short orbital periods are interesting targets for the study of planetary atmospheres. While selecting super-Earths suitable for further characterization from the ground among a list of confirmed and validated exoplanets detected by K2, we found some suspicious cases th...
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Long-lived mesoscopic entanglement between two damped infinite harmonic chains
We consider two chains, each made of $N$ independent oscillators, immersed in a common thermal bath and study the dynamics of their mutual quantum correlations in the thermodynamic, large-$N$ limit. We show that dissipation and noise due to the presence of the external environment are able to generate collective quan...
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Measured Multiseries and Integration
A paper by Bruno Salvy and the author introduced measured multiseries and gave an algorithm to compute these for a large class of elementary functions, modulo a zero-equivalence method for constants. This gave a theoretical background for the implementation that Salvy was developing at that time. The main result of t...
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Spectral Approach to Verifying Non-linear Arithmetic Circuits
This paper presents a fast and effective computer algebraic method for analyzing and verifying non-linear integer arithmetic circuits using a novel algebraic spectral model. It introduces a concept of algebraic spectrum, a numerical form of polynomial expression; it uses the distribution of coefficients of the monomi...
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Signal-based Bayesian Seismic Monitoring
Detecting weak seismic events from noisy sensors is a difficult perceptual task. We formulate this task as Bayesian inference and propose a generative model of seismic events and signals across a network of spatially distributed stations. Our system, SIGVISA, is the first to directly model seismic waveforms, allowing...
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Multi-Label Learning with Global and Local Label Correlation
It is well-known that exploiting label correlations is important to multi-label learning. Existing approaches either assume that the label correlations are global and shared by all instances; or that the label correlations are local and shared only by a data subset. In fact, in the real-world applications, both cases...
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Complexity of Verifying Nonblockingness in Modular Supervisory Control
Complexity analysis becomes a common task in supervisory control. However, many results of interest are spread across different topics. The aim of this paper is to bring several interesting results from complexity theory and to illustrate their relevance to supervisory control by proving new nontrivial results concer...
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