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An Analytic Formula for Numbers of Restricted Partitions from Conformal Field Theory
We study the correlators of irregular vertex operators in two-dimensional conformal field theory (CFT) in order to propose an exact analytic formula for calculating numbers of partitions, that is: 1) for given $N,k$, finding the total number $\lambda(N|k)$ of length $k$ partitions of $N$: $N=n_1+...+n_k;0<n_1\leq{n_2...
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Hyperopic Cops and Robbers
We introduce a new variant of the game of Cops and Robbers played on graphs, where the robber is invisible unless outside the neighbor set of a cop. The hyperopic cop number is the corresponding analogue of the cop number, and we investigate bounds and other properties of this parameter. We characterize the cop-win g...
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New pinching estimates for Inverse curvature flows in space forms
We prove new pinching estimate for the inverse curvature flow of strictly convex hypersurfaces in the space form $N$ of constant sectional curvature $K_N$ with speed given by $F^{-\alpha}$, where $\alpha\in (0,1]$ for $K_N=0,-1$ and $\alpha=1$ for $K_N=1$, $F$ is a smooth, symmetric homogeneous of degree one function...
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automan: a simple, Python-based, automation framework for numerical computing
We present an easy-to-use, Python-based framework that allows a researcher to automate their computational simulations. In particular the framework facilitates assembling several long-running computations and producing various plots from the data produced by these computations. The framework makes it possible to repr...
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Extensive characterization of a high Reynolds number decelerating boundary layer using advanced optical metrology
An experiment conducted in the framework of the EUHIT project and designed to characterize large scale structures in an adverse pressure gradient boundary layer flow is presented. Up to 16 sCMOS cameras were used in order to perform large scale turbulent boundary layer PIV measurements with a large field of view and ...
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Q-analogues of the Fibo-Stirling numbers
Let $F_n$ denote the $n^{th}$ Fibonacci number relative to the initial conditions $F_0=0$ and $F_1=1$. Bach, Paudyal, and Remmel introduced Fibonacci analogues of the Stirling numbers called Fibo-Stirling numbers of the first and second kind. These numbers serve as the connection coefficients between the Fibo-falling...
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Hybrid Dirac Semimetal in CaAgBi Materials Family
Based on their formation mechanisms, Dirac points in three-dimensional systems can be classified as accidental or essential. The former can be further distinguished into type-I and type-II, depending on whether the Dirac cone spectrum is completely tipped over along certain direction. Here, we predict the coexistence...
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On the martingale property in the rough Bergomi model
We consider a class of fractional stochastic volatility models (including the so-called rough Bergomi model), where the volatility is a superlinear function of a fractional Gaussian process. We show that the stock price is a true martingale if and only if the correlation $\rho$ between the driving Brownian motions of...
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Weighted Surface Algebras
A finite-dimensional algebra $A$ over an algebraically closed field $K$ is called periodic if it is periodic under the action of the syzygy operator in the category of $A-A-$ bimodules. The periodic algebras are self-injective and occur naturally in the study of tame blocks of group algebras, actions of finite groups...
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A Statistical Learning Approach to Modal Regression
This paper studies the nonparametric modal regression problem systematically from a statistical learning view. Originally motivated by pursuing a theoretical understanding of the maximum correntropy criterion based regression (MCCR), our study reveals that MCCR with a tending-to-zero scale parameter is essentially mo...
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Teaching a Machine to Read Maps with Deep Reinforcement Learning
The ability to use a 2D map to navigate a complex 3D environment is quite remarkable, and even difficult for many humans. Localization and navigation is also an important problem in domains such as robotics, and has recently become a focus of the deep reinforcement learning community. In this paper we teach a reinfor...
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The fan beam model for the pulse evolution of PSR J0737-3039B
Average radio pulse profile of a pulsar B in a double pulsar system PSR J0737-3039A/B exhibits an interesting behaviour. During the observation period between 2003 and 2009, the profile evolves from a single-peaked to a double-peaked form, following disappearance in 2008 indicating that the geodetic precession of the...
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Resilience of Core-Periphery Networks in the Case of Rich-Club
Core-periphery networks are structures that present a set of central and densely connected nodes, namely the core, and a set of non-central and sparsely connected nodes, namely the periphery. The rich-club refers to a set in which the highest degree nodes show a high density of connections. Thus, a network that displ...
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Reservoir of Diverse Adaptive Learners and Stacking Fast Hoeffding Drift Detection Methods for Evolving Data Streams
The last decade has seen a surge of interest in adaptive learning algorithms for data stream classification, with applications ranging from predicting ozone level peaks, learning stock market indicators, to detecting computer security violations. In addition, a number of methods have been developed to detect concept ...
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Extremes in Random Graphs Models of Complex Networks
Regarding the analysis of Web communication, social and complex networks the fast finding of most influential nodes in a network graph constitutes an important research problem. We use two indices of the influence of those nodes, namely, PageRank and a Max-linear model. We consider the PageRank %both as %Galton-Watso...
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Estimates of the Reconstruction Error in Partially Redressed Warped Frames Expansions
In recent work, redressed warped frames have been introduced for the analysis and synthesis of audio signals with non-uniform frequency and time resolutions. In these frames, the allocation of frequency bands or time intervals of the elements of the representation can be uniquely described by means of a warping map. ...
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On the Optimality of Secret Key Agreement via Omniscience
For the multiterminal secret key agreement problem under a private source model, it is known that the maximum key rate, i.e., the secrecy capacity, can be achieved through communication for omniscience, but the omniscience strategy can be strictly suboptimal in terms of minimizing the public discussion rate. While a ...
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Learning Motion Predictors for Smart Wheelchair using Autoregressive Sparse Gaussian Process
Constructing a smart wheelchair on a commercially available powered wheelchair (PWC) platform avoids a host of seating, mechanical design and reliability issues but requires methods of predicting and controlling the motion of a device never intended for robotics. Analog joystick inputs are subject to black-box transf...
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Kernelized Hashcode Representations for Relation Extraction
Kernel methods have produced state-of-the-art results for a number of NLP tasks such as relation extraction, but suffer from poor scalability due to the high cost of computing kernel similarities between natural language structures. A recently proposed technique, kernelized locality-sensitive hashing (KLSH), can sign...
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Can Adversarial Networks Hallucinate Occluded People With a Plausible Aspect?
When you see a person in a crowd, occluded by other persons, you miss visual information that can be used to recognize, re-identify or simply classify him or her. You can imagine its appearance given your experience, nothing more. Similarly, AI solutions can try to hallucinate missing information with specific deep l...
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John, the semi-conductor : a tool for comprovisation
This article presents "John", an open-source software designed to help collective free improvisation. It provides generated screen-scores running on distributed, reactive web-browsers. The musicians can then concurrently edit the scores in their own browser. John is used by ONE, a septet playing improvised electro-ac...
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Eigenvalue and Eigenfunction for the $PT$-symmetric Potential $V = - (ix)^N$
The real energy spectrum from the $PT$-symmetric Hamiltonian $H = p^2 - (ix)^N$ with $x\in\mathbb{C}$ was examined within one pair of Stokes wedges in 1998 by Bender and Boettcher. For this Hamiltonian we discuss the following three questions. First, since their paper used a Runge-Kutta method to integrate along a pa...
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Random walks on activity-driven networks with attractiveness
Virtually all real-world networks are dynamical entities. In social networks, the propensity of nodes to engage in social interactions (activity) and their chances to be selected by active nodes (attractiveness) are heterogeneously distributed. Here, we present a time-varying network model where each node and the dyn...
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Predicting B Cell Receptor Substitution Profiles Using Public Repertoire Data
B cells develop high affinity receptors during the course of affinity maturation, a cyclic process of mutation and selection. At the end of affinity maturation, a number of cells sharing the same ancestor (i.e. in the same "clonal family") are released from the germinal center, their amino acid frequency profile refl...
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Energy Efficient Mobile Edge Computing in Dense Cellular Networks
Merging Mobile Edge Computing (MEC), which is an emerging paradigm to meet the increasing computation demands from mobile devices, with the dense deployment of Base Stations (BSs), is foreseen as a key step towards the next generation mobile networks. However, new challenges arise for designing energy efficient netwo...
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Delone dynamical systems and spectral convergence
In the realm of Delone sets in locally compact, second countable, Hausdorff groups, we develop a dynamical systems approach in order to study the continuity behavior of measured quantities arising from point sets. A special focus is both on the autocorrelation, as well as on the density of states for random bounded o...
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On biconservative surfaces in Euclidean spaces
In this paper, we study biconservative surfaces with parallel normalized mean curvature vector in $\mathbb{E}^4$. We obtain complete local classification in $\mathbb{E}^4$ for a biconservative PNMCV surface. We also give an example to show the existence of PNMCV biconservative surfaces in $\mathbb{E}^4$.
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Automatic implementation of material laws: Jacobian calculation in a finite element code with TAPENADE
In an effort to increase the versatility of finite element codes, we explore the possibility of automatically creating the Jacobian matrix necessary for the gradient-based solution of nonlinear systems of equations. Particularly, we aim to assess the feasibility of employing the automatic differentiation tool TAPENAD...
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Asymptotic analysis for Hamilton-Jacobi equations with large drift term
We investigate the asymptotic behavior of solutions of Hamilton-Jacobi equations with large drift term in an open subset of two-dimensional Euclidean space. When the drift is given by $\varepsilon^{-1} (H_{x_2}, -H_{x_1})$ of a Hamiltonian $H$, with $\varepsilon > 0$, we establish the convergence, as $\varepsilon \to...
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An Upper Bound of the Minimal Dispersion via Delta Covers
For a point set of $n$ elements in the $d$-dimensional unit cube and a class of test sets we are interested in the largest volume of a test set which does not contain any point. For all natural numbers $n$, $d$ and under the assumption of a $delta$-cover with cardinality $\vert \Gamma_\delta \vert$ we prove that ther...
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Three-dimensional band structure of LaSb and CeSb:Absence of band inversion
We have performed angle-resolved photoemission spectroscopy (ARPES) of LaSb and CeSb, a candidate of topological insulator. Using soft-x-ray photons, we have accurately determined the three-dimensional bulk band structure and revealed that the band inversion at the Brillouin-zone corner - a prerequisite for realizing...
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Stellar-to-halo mass relation of cluster galaxies
In the hierarchical formation model, galaxy clusters grow by accretion of smaller groups or isolated galaxies. During the infall into the centre of a cluster, the properties of accreted galaxies change. In particular, both observations and numerical simulations suggest that its dark matter halo is stripped by the tid...
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Undecidability and Finite Automata
Using a novel rewriting problem, we show that several natural decision problems about finite automata are undecidable (i.e., recursively unsolvable). In contrast, we also prove three related problems are decidable. We apply one result to prove the undecidability of a related problem about k-automatic sets of rational...
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A globally stable attractor that is locally unstable everywhere
We construct two examples of invariant manifolds that despite being locally unstable at every point in the transverse direction are globally stable. Using numerical simulations we show that these invariant manifolds temporarily repel nearby trajectories but act as global attractors. We formulate an explanation for su...
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On Centers and Central Lines of Triangles in the Elliptic Plane
We determine barycentric coordinates of triangle centers in the elliptic plane. The main focus is put on centers that lie on lines whose euclidean limit (triangle excess --> 0) is the Euler line or the Brocard line. We also investigate curves which can serve in elliptic geometry as substitutes for the euclidean nine-...
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Stopping Active Learning based on Predicted Change of F Measure for Text Classification
During active learning, an effective stopping method allows users to limit the number of annotations, which is cost effective. In this paper, a new stopping method called Predicted Change of F Measure will be introduced that attempts to provide the users an estimate of how much performance of the model is changing at...
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Statistical properties of random clique networks
In this paper, a random clique network model to mimic the large clustering coefficient and the modular structure that exist in many real complex networks, such as social networks, artificial networks, and protein interaction networks, is introduced by combining the random selection rule of the Erdös and Rényi (ER) mo...
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Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
The paucity of videos in current action classification datasets (UCF-101 and HMDB-51) has made it difficult to identify good video architectures, as most methods obtain similar performance on existing small-scale benchmarks. This paper re-evaluates state-of-the-art architectures in light of the new Kinetics Human Act...
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Selfish Cops and Active Robber: Multi-Player Pursuit Evasion on Graphs
We introduce and study the game of "Selfish Cops and Active Robber" (SCAR) which can be seen as an multiplayer variant of the "classic" two-player Cops and Robbers (CR) game. In classic CR all cops are controlled by a single player, who has no preference over which cop captures the robber. In SCAR, on the other hand,...
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Singly-Thermostated Ergodicity in Gibbs' Canonical Ensemble and the 2016 Ian Snook Prize Award
The 2016 Snook Prize has been awarded to Diego Tapias, Alessandro Bravetti, and David Sanders for their paper -- Ergodicity of One-Dimensional Systems Coupled to the Logistic Thermostat. They introduced a relatively stiff hyperbolic tangent thermostat force and successfully tested its ability to reproduce Gibbs' cano...
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Robust Estimation via Robust Gradient Estimation
We provide a new computationally-efficient class of estimators for risk minimization. We show that these estimators are robust for general statistical models: in the classical Huber epsilon-contamination model and in heavy-tailed settings. Our workhorse is a novel robust variant of gradient descent, and we provide co...
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SMT Solving for Vesicle Traffic Systems in Cells
In biology, there are several questions that translate to combinatorial search. For example, vesicle traffic systems that move cargo within eukaryotic cells have been proposed to exhibit several graph properties such as three connectivity. These properties are consequences of underlying biophysical constraints. A nat...
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Endemicity and prevalence of multipartite viruses under heterogeneous between-host transmission
Multipartite viruses replicate through a puzzling evolutionary strategy. Their genome is segmented into two or more parts, and encapsidated in separate particles that appear to propagate independently. Completing the replication cycle, however, requires the full genome, so that a persistent infection of a host requir...
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Correlating Cell Shape and Cellular Stress in Motile Confluent Tissues
Collective cell migration is a highly regulated process involved in wound healing, cancer metastasis and morphogenesis. Mechanical interactions among cells provide an important regulatory mechanism to coordinate such collective motion. Using a Self-Propelled Voronoi (SPV) model that links cell mechanics to cell shape...
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Eigenvalue Decay Implies Polynomial-Time Learnability for Neural Networks
We consider the problem of learning function classes computed by neural networks with various activations (e.g. ReLU or Sigmoid), a task believed to be computationally intractable in the worst-case. A major open problem is to understand the minimal assumptions under which these classes admit provably efficient algori...
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A New Steganographic Technique Matching the Secret Message and Cover image Binary Value
Steganography involves hiding a secret message or image inside another cover image. Changes are made in the cover image without affecting visual quality of the image. In contrast to cryptography, Steganography provides complete secrecy of the communication. Security of very sensitive data can be enhanced by combining...
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On topological fluid mechanics of non-ideal systems and virtual frozen-in dynamics
Euler and Navier-Stokes have variant systems with dynamical invariance of helicity and thus (weak) topological equivalence, allowing a strong `frozen-in' (to, or, dually, `Lie-carried' by the \textit{virtual} velocity $V$) formulation of the vorticity with a flavor of `inverse Helmholtz theorem'. We remark on the non...
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Topological AdS/CFT
We define a holographic dual to the Donaldson-Witten topological twist of $\mathcal{N}=2$ gauge theories on a Riemannian four-manifold. This is described by a class of asymptotically locally hyperbolic solutions to $\mathcal{N}=4$ gauged supergravity in five dimensions, with the four-manifold as conformal boundary. U...
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Using highly uniform and smooth Selenium colloids as low-loss magnetodielectric building blocks of optical metafluids
We systematically analyzed magnetodielectric resonances of Se colloids for the first time to exploit the possibility for use as building blocks of all-dielectric optical metafluids. By taking synergistic advantages of Se colloids, including (i) high-refractive-index at optical frequencies, (ii) unprecedented structur...
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A Vector Field Method for Radiating Black Hole Spacetimes
We develop a commuting vector field method for a general class of radiating spacetimes. The metrics considered are certain long range perturbations of Minkowski space including those constructed from global stability problems in general relativity. Our method provides sharp peeling estimates for solutions to both lin...
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Experimental Constraint on an Exotic Spin- and Velocity-Dependent Interaction in the Sub-meV Range of Axion Mass with a Spin-Exchange Relaxation-Free Magnetometer
We conducted a search for an exotic spin- and velocity-dependent interaction for polarized electrons with an experimental approach based on a high-sensitivity spin-exchange relaxation-free (SERF) magnetometer, which serves as both a source of polarized electrons and a magnetic-field sensor. The experiment aims to sen...
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Generalization Error in Deep Learning
Deep learning models have lately shown great performance in various fields such as computer vision, speech recognition, speech translation, and natural language processing. However, alongside their state-of-the-art performance, it is still generally unclear what is the source of their generalization ability. Thus, an...
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Block Compressive Sensing of Image and Video with Nonlocal Lagrangian Multiplier and Patch-based Sparse Representation
Although block compressive sensing (BCS) makes it tractable to sense large-sized images and video, its recovery performance has yet to be significantly improved because its recovered images or video usually suffer from blurred edges, loss of details, and high-frequency oscillatory artifacts, especially at a low subra...
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A multi-phase-field method for surface tension-induced elasticity
A consistent treatment of the coupling of surface energy and elasticity within the multi-phase- field framework is presented. The model accurately reproduces stress distribution in a number of analytically tractable, yet non-trivial, cases including different types of spherical heterogeneities and a thin plate suspen...
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On the restriction theorem for paraboloid in $\mathbb R^4$
We prove that recent breaking by Zahl of the $\frac32$ barrier in Wolff's estimate on the Kakeya maximal operator in $\mathbb R^4$ leads to improving the $\frac{14}{5}$ threshold for the restriction problem for the paraboloid in $\mathbb R^4$. One of the ingredients is a new trilinear estimate. The proofs are deliber...
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Existence of Stein Kernels under a Spectral Gap, and Discrepancy Bound
We establish existence of Stein kernels for probability measures on $\mathbb{R}^d$ satisfying a Poincaré inequality, and obtain bounds on the Stein discrepancy of such measures. Applications to quantitative central limit theorems are discussed, including a new CLT in Wasserstein distance $W_2$ with optimal rate and d...
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High-order asynchrony-tolerant finite difference schemes for partial differential equations
Synchronizations of processing elements (PEs) in massively parallel simulations, which arise due to communication or load imbalances between PEs, significantly affect the scalability of scientific applications. We have recently proposed a method based on finite-difference schemes to solve partial differential equatio...
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Hazard Analysis and Risk Assessment for an Automated Unmanned Protective Vehicle
For future application of automated vehicles in public traffic, ensuring functional safety is essential. In this context, a hazard analysis and risk assessment is an important input for designing functionally vehicle automation systems. In this contribution, we present a detailed hazard analysis and risk assessment (...
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Detailed experimental and numerical analysis of a cylindrical cup deep drawing: pros and cons of using solid-shell elements
The Swift test was originally proposed as a formability test to reproduce the conditions observed in deep drawing operations. This test consists on forming a cylindrical cup from a circular blank, using a flat bottom cylindrical punch and has been extensively studied using both analytical and numerical methods. This ...
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Hubble Frontier Fields: systematic errors in strong lensing models of galaxy clusters - Implications for cosmography
Strong gravitational lensing by galaxy clusters is a fundamental tool to study dark matter and constrain the geometry of the Universe. Recently, the Hubble Space Telescope Frontier Fields programme has allowed a significant improvement of mass and magnification measurements but lensing models still have a residual ro...
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A Note on the Spectral Transfer Morphisms for Affine Hecke Algebras
E. Opdam introduced the tool of spectral transfer morphism (STM) of affine Hecke algebras to study the formal degrees of unipotent discrete series representations. He established a uniqueness property of STM for the affine Hecke algebras associated of unipotent discrete series representations. Based on this result, O...
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Batch-Expansion Training: An Efficient Optimization Framework
We propose Batch-Expansion Training (BET), a framework for running a batch optimizer on a gradually expanding dataset. As opposed to stochastic approaches, batches do not need to be resampled i.i.d. at every iteration, thus making BET more resource efficient in a distributed setting, and when disk-access is constrain...
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Coordinate Descent with Bandit Sampling
Coordinate descent methods usually minimize a cost function by updating a random decision variable (corresponding to one coordinate) at a time. Ideally, we would update the decision variable that yields the largest decrease in the cost function. However, finding this coordinate would require checking all of them, whi...
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Closing the gap for pseudo-polynomial strip packing
The set of 2-dimensional packing problems builds an important class of optimization problems and Strip Packing together with 2-dimensional Bin Packing and 2-dimensional Knapsack is one of the most famous of these problems. Given a set of rectangular axis parallel items and a strip with bounded width and infinite heig...
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Notes on the replica symmetric solution of the classical and quantum SK model, including the matrix of second derivatives and the spin glass susceptibility
A review of the replica symmetric solution of the classical and quantum, infinite-range, Sherrington-Kirkpatrick spin glass is presented.
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Self-supervised Knowledge Distillation Using Singular Value Decomposition
To solve deep neural network (DNN)'s huge training dataset and its high computation issue, so-called teacher-student (T-S) DNN which transfers the knowledge of T-DNN to S-DNN has been proposed. However, the existing T-S-DNN has limited range of use, and the knowledge of T-DNN is insufficiently transferred to S-DNN. T...
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Can justice be fair when it is blind? How social network structures can promote or prevent the evolution of despotism
Hierarchy is an efficient way for a group to organize, but often goes along with inequality that benefits leaders. To control despotic behaviour, followers can assess leaders decisions by aggregating their own and their neighbours experience, and in response challenge despotic leaders. But in hierarchical social netw...
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GSAE: an autoencoder with embedded gene-set nodes for genomics functional characterization
Bioinformatics tools have been developed to interpret gene expression data at the gene set level, and these gene set based analyses improve the biologists' capability to discover functional relevance of their experiment design. While elucidating gene set individually, inter gene sets association is rarely taken into ...
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Natasha: Faster Non-Convex Stochastic Optimization Via Strongly Non-Convex Parameter
Given a nonconvex function that is an average of $n$ smooth functions, we design stochastic first-order methods to find its approximate stationary points. The convergence of our new methods depends on the smallest (negative) eigenvalue $-\sigma$ of the Hessian, a parameter that describes how nonconvex the function is...
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Higher-Order Bounded Model Checking
We present a Bounded Model Checking technique for higher-order programs. The vehicle of our study is a higher-order calculus with general references. Our technique is a symbolic state syntactical translation based on SMT solvers, adapted to a setting where the values passed and stored during computation can be functi...
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Smoothing for the fractional Schrodinger equation on the torus and the real line
In this paper we study the cubic fractional nonlinear Schrodinger equation (NLS) on the torus and on the real line. Combining the normal form and the restricted norm methods we prove that the nonlinear part of the solution is smoother than the initial data. Our method applies to both focusing and defocusing nonlinear...
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Deep Learning Based Cryptographic Primitive Classification
Cryptovirological augmentations present an immediate, incomparable threat. Over the last decade, the substantial proliferation of crypto-ransomware has had widespread consequences for consumers and organisations alike. Established preventive measures perform well, however, the problem has not ceased. Reverse engineer...
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The Alexandrov-Fenchel type inequalities, revisited
Various Alexandrov-Fenchel type inequalities have appeared and played important roles in convex geometry, matrix theory and complex algebraic geometry. It has been noticed for some time that they share some striking analogies and have intimate relationships. The purpose of this article is to shed new light on this by...
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Development of non-modal shear induced instabilities in atmospheric tornadoes
In this paper we consider the role of nonmodal instabilities in the dynamics of atmospheric tornadoes. For this purpose we consider the Euler equation, continuity equation and the equation of state and linearise them. As an example we study several different velocity profiles: the so-called Rankine vortex model; the ...
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DeepSketch2Face: A Deep Learning Based Sketching System for 3D Face and Caricature Modeling
Face modeling has been paid much attention in the field of visual computing. There exist many scenarios, including cartoon characters, avatars for social media, 3D face caricatures as well as face-related art and design, where low-cost interactive face modeling is a popular approach especially among amateur users. In...
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Time-Inhomogeneous Branching Processes Conditioned on Non-Extinction
In this paper, we consider time-inhomogeneous branching processes and time-inhomogeneous birth-and-death processes, in which the offspring distribution and birth and death rates (respectively) vary in time. A classical result of branching processes states that in the critical regime, a process conditioned on non-exti...
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The Dirichlet-to-Neumann operator for quantum graphs
For a compact, connected metric graphs with a boundary that consists of $k$ vertices, we prove that an arbitrary symmetric $k\times k$ matrix with real entries can be realized as the Dirichlet-to-Neumann operator for the Laplacian plus a constant.
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A study of the dual problem of the one-dimensional L-infinity optimal transport problem with applications
The Monge-Kantorovich problem for the infinite Wasserstein distance presents several peculiarities. Among them the lack of convexity and then of a direct duality. We study in dimension 1 the dual problem introduced by Barron, Bocea and Jensen. We construct a couple of Kantorovich potentials which is "as less trivial ...
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Strong coupling Bose polarons in a BEC
We use a non-perturbative renormalization group approach to develop a unified picture of the Bose polaron problem, where a mobile impurity is strongly interacting with a surrounding Bose-Einstein condensate (BEC). A detailed theoretical analysis of the phase diagram is presented and the polaron-to-molecule transition...
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Triangle packing in (sparse) tournaments: approximation and kernelization
Given a tournament T and a positive integer k, the C_3-Pakcing-T problem asks if there exists a least k (vertex-)disjoint directed 3-cycles in T. This is the dual problem in tournaments of the classical minimal feedback vertex set problem. Surprisingly C_3-Pakcing-T did not receive a lot of attention in the literatur...
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Asymptotics of Chebyshev Polynomials, II. DCT Subsets of $\mathbb{R}$
We prove Szegő-Widom asymptotics for the Chebyshev polynomials of a compact subset of $\mathbb{R}$ which is regular for potential theory and obeys the Parreau-Widom and DCT conditions.
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Tracking Urban Human Activity from Mobile Phone Calling Patterns
Timings of human activities are marked by circadian clocks which in turn are entrained to different environmental signals. In an urban environment the presence of artificial lighting and various social cues tend to disrupt the natural entrainment with the sunlight. However, it is not completely understood to what ext...
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Efficient conversion from rotating matrix to rotation axis and angle by extending Rodrigues' formula
In computational 3D geometric problems involving rotations, it is often that people have to convert back and forth between a rotational matrix and a rotation described by an axis and a corresponding angle. For this purpose, Rodrigues' rotation formula is a very popular expression to use because of its simplicity and ...
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Statistical methods for characterizing transfusion-related changes in regional oxygenation using Near-infrared spectroscopy (NIRS) in preterm infants
Near infrared spectroscopy (NIRS) is an imaging-based diagnostic tool that provides non-invasive and continuous evaluation of regional tissue oxygenation in real-time. In recent years, NIRS has show promise as a useful monitoring technology to help detect relative tissue ischemia that could lead to significant morbid...
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To understand deep learning we need to understand kernel learning
Generalization performance of classifiers in deep learning has recently become a subject of intense study. Deep models, typically over-parametrized, tend to fit the training data exactly. Despite this "overfitting", they perform well on test data, a phenomenon not yet fully understood. The first point of our paper is...
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Atomic Data Revisions for Transitions Relevant to Observations of Interstellar, Circumgalactic, and Intergalactic Matter
Measurements of element abundances in galaxies from astrophysical spectroscopy depend sensitively on the atomic data used. With the goal of making the latest atomic data accessible to the community, we present a compilation of selected atomic data for resonant absorption lines at wavelengths longward of 911.753 {\AA}...
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Using Nonlinear Normal Modes for Execution of Efficient Cyclic Motions in Soft Robots
With the aim of getting closer to the performance of the animal muscleskeletal system, elastic elements are purposefully introduced in the mechanical structure of soft robots. Indeed, previous works have extensively shown that elasticity can endow robots with the ability of performing tasks with increased efficiency,...
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Efficient Deep Learning on Multi-Source Private Data
Machine learning models benefit from large and diverse datasets. Using such datasets, however, often requires trusting a centralized data aggregator. For sensitive applications like healthcare and finance this is undesirable as it could compromise patient privacy or divulge trade secrets. Recent advances in secure an...
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Analytical solution of the integral equation for partial wave Coulomb t-matrices at excited-state energy
Starting from the integral representation of the three-dimensional Coulomb transition matrix elaborated by us formerly with the use of specific symmetry of the interaction in a four-dimensional Euclidean space introduced by Fock, the possibility of the analytical solving of the integral equation for the partial wave ...
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Equilateral $p$-gons in $\mathbb R^d$ and deformed spheres and mod $p$ Fadell-Husseini index
We introduce the concept of $r$-equilateral $m$-gons. We prove the existence of $r$-equilateral $p$-gons in $\mathbb R^d$ if $r<d$ and the existence of equilateral $p$-gons in the image of continuous injective maps $f:S^d\to \mathbb R^{d+1}$. Our ideas are based mainly in the paper of Y. Soibelman \cite{soibelman}, i...
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Jónsson posets
According to Kearnes and Oman (2013), an ordered set $P$ is \emph{Jónsson} if it is infinite and the cardinality of every proper initial segment of $P$ is strictly less than the cardinaliy of $P$. We examine the structure of Jónsson posets.
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Hypotheses testing on infinite random graphs
Drawing on some recent results that provide the formalism necessary to definite stationarity for infinite random graphs, this paper initiates the study of statistical and learning questions pertaining to these objects. Specifically, a criterion for the existence of a consistent test for complex hypotheses is presente...
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On compact splitting complex submanifolds of quotients of bounded symmetric domains
In the current article our primary objects of study are compact complex submanifolds of quotient manifolds of irreducible bounded symmetric domains by torsion free discrete lattices of automorphisms. We are interested in the characterization of the totally geodesic submanifolds among compact splitting complex submani...
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Octupolar Tensors for Liquid Crystals
A third-order three-dimensional symmetric traceless tensor, called the \emph{octupolar} tensor, has been introduced to study tetrahedratic nematic phases in liquid crystals. The octupolar \emph{potential}, a scalar-valued function generated on the unit sphere by that tensor, should ideally have four maxima capturing ...
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Efficient boundary corrected Strang splitting
Strang splitting is a well established tool for the numerical integration of evolution equations. It allows the application of tailored integrators for different parts of the vector field. However, it is also prone to order reduction in the case of non-trivial boundary conditions. This order reduction can be remedied...
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SOS-convex Semi-algebraic Programs and its Applications to Robust Optimization: A Tractable Class of Nonsmooth Convex Optimization
In this paper, we introduce a new class of nonsmooth convex functions called SOS-convex semialgebraic functions extending the recently proposed notion of SOS-convex polynomials. This class of nonsmooth convex functions covers many common nonsmooth functions arising in the applications such as the Euclidean norm, the ...
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An Uncertainty Principle for Estimates of Floquet Multipliers
We derive a Cramér-Rao lower bound for the variance of Floquet multiplier estimates that have been constructed from stable limit cycles perturbed by noise. To do so, we consider perturbed periodic orbits in the plane. We use a periodic autoregressive process to model the intersections of these orbits with cross secti...
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Shielding Google's language toxicity model against adversarial attacks
Lack of moderation in online communities enables participants to incur in personal aggression, harassment or cyberbullying, issues that have been accentuated by extremist radicalisation in the contemporary post-truth politics scenario. This kind of hostility is usually expressed by means of toxic language, profanity ...
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Diagrammatic Monte-Carlo for weak-coupling expansion of non-Abelian lattice field theories: large-N U(N)xU(N) principal chiral model
We develop numerical tools for Diagrammatic Monte-Carlo simulations of non-Abelian lattice field theories in the t'Hooft large-N limit based on the weak-coupling expansion. First we note that the path integral measure of such theories contributes a bare mass term in the effective action which is proportional to the b...
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Training Shallow and Thin Networks for Acceleration via Knowledge Distillation with Conditional Adversarial Networks
There is an increasing interest on accelerating neural networks for real-time applications. We study the student-teacher strategy, in which a small and fast student network is trained with the auxiliary information learned from a large and accurate teacher network. We propose to use conditional adversarial networks t...
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