November 2019 arXiv papers

Michael B. Marcus, Jay Rosen

Permanental sequences with non-symmetric kernels that are generalization of the potentials of a Markov chain with state space $\{0,1/2, \ldots, 1/n,\ldots\}$ that was introduced by Kolmogorov, are studied. Depending on a parameter in the kernels we obtain an exact rate of divergence of the sequence at $0$, an exact local modulus of continuity of the sequence

Ulysse Côté-Allard, Evan Campbell, Angkoon Phinyomark, François Laviolette

The research in myoelectric control systems primarily focuses on extracting discriminative representations from the electromyographic (EMG) signal by designing handcrafted features. Recently, deep learning techniques have been applied to the challenging task of EMG-based gesture recognition. The adoption of these techniques slowly shifts the focus from featu

Adrian B. Culver, Natan Andrei

We present here the details of a method [A. B. Culver and N. Andrei, Phys. Rev. B 103, L201103 (2021)] for calculating the time-dependent many-body wavefunction that follows a local quench. We apply the method to the voltage-driven nonequilibrium Kondo model to find the exact time-evolving wavefunction following a quench where the dot is suddenly attached to

Mohammad-Hassan Naddaf, Bozena Czerny, Ryszard Szczerba

In Failed Radiatively Accelerated Dusty Outflow (FRADO) model which provides the source of material above the accretion disk (AD) as an option to explain the formation mechanism of Broad Line Region (BLR) in AGNs, the BLR inner radius ($\rm{BLR}_{in}$ hereafter) is set by the condition that the dust evaporates immediately upon departure from the AD surface.

Nassim Nicholas Taleb, Pasquale Cirillo

This is an epistemological approach to errors in both inference and risk management, leading to necessary structural properties for the probability distribution. Many mechanisms have been used to show the emergence of fat tails. Here we follow an alternative route, the epistemological one, using counterfactual analysis, and show how nested uncertainty, that

Alexander Migdal

We advance the vortex cell approach to turbulence \cite{TSVS} by elaborating the Clebsch field dynamics on the surface of vortex cells. We argue that resulting statistical system can be described as 3D Ising model interacting with Compactified Bosonic String on the Riemann surface describing phase boundary. The cells come out as $σ=1$ phase of the Ising mode

Robert Glas, H. -Thomas Janka, Francesco Capozzi, Manibrata Sen

Neutrinos from a supernova (SN) might undergo fast flavor conversions near the collapsed stellar core. We perform a detailed study of this intriguing possibility, analyzing time-dependent state-of-the-art 3D SN models of 9 and 20 Msun. Both models were computed with multi-D three-flavor neutrino transport based on a two-moment solver, and both exhibit the pr

Quang Dao, Christina Meng, Julian Wellman, Zixuan Xu

Nestohedra are a family of convex polytopes that includes permutohedra, associahedra, and graph associahedra. In this paper, we study an extension of such polytopes, called extended nestohedra. We show that these objects are indeed the boundaries of simple polytopes, answering a question of Lam and Pylyavskyy. We also study the duals of (extended) nestohedra

Shervin Minaee, Amirali Abdolrashidi, Hang Su, Mohammed Bennamoun

Deep learning-based models have been very successful in achieving state-of-the-art results in many of the computer vision, speech recognition, and natural language processing tasks in the last few years. These models seem a natural fit for handling the ever-increasing scale of biometric recognition problems, from cellphone authentication to airport security

Francesca Grogan, Huan Lei, Xiantao Li, Nathan A. Baker

The complexity of molecular dynamics simulations necessitates dimension reduction and coarse-graining techniques to enable tractable computation. The generalized Langevin equation (GLE) describes coarse-grained dynamics in reduced dimensions. In spite of playing a crucial role in non-equilibrium dynamics, the memory kernel of the GLE is often ignored because

Iván Tulli

The Ooguri-Vafa space is a 4-dimensional incomplete hyperkähler manifold, defined on the total space of a singular torus fibration with one singular nodal fiber. It has been proposed that the Ooguri-Vafa hyperkähler metric should be part of the local model of the hyperkähler metric of the Hitchin moduli spaces, near the most generic kind of singular locus of

Brian White

We prove that every stationary polyhedral varifold minimizes area in the following senses: (1) its area cannot be decreased by a one-to-one Lipschitz ambient deformation that coincides with the identity outside of a compact set, and (2) it is the varifold associated to a mass-minimizing flat chain with coefficients in a certain metric abelian group. NOTE: Af

Burak Kocuk

It is well-known that the second-order cone can be outer-approximated to an arbitrary accuracy $ε$ by a polyhedral cone of compact size defined by irrational data. In this paper, we propose two rational polyhedral outer-approximations of compact size retaining the same guaranteed accuracy $ε$. The first outer-approximation has the same size as the optimal bu

Amnon Geifman, Yoni Kasten, Meirav Galun, Ronen Basri

Global methods to Structure from Motion have gained popularity in recent years. A significant drawback of global methods is their sensitivity to collinear camera settings. In this paper, we introduce an analysis and algorithms for averaging bifocal tensors (essential or fundamental matrices) when either subsets or all of the camera centers are collinear. We

Peter Ván, Sumiyoshi Abe

Discovery of a novel thermodynamic aspect of nonrelativistic gravity is reported. Here, initially, an unspecified scalar field potential is considered and treated not as an externally applied field but as a thermodynamic variable on an equal footing with the fluid variables. It is shown that the second law of thermodynamics imposes a stringent constraint on

P. O. Kazinski, I. S. Kalinichenko

The problem of a scalar particle in a constant crossed electromagnetic field ($\mathbf{E}\perp\mathbf{H}$ and $|\mathbf{E}|=|\mathbf{H}|$) is examined. The high-temperature expansion of the grand thermodynamic potential and vacuum energy with account for non-perturbative corrections are derived. The contribution from particles and antiparticles is considered

Miguel R. Nuñez-Chávez

This paper deals with the analysis of the internal control with constraint of positive kind of a parabolic PDE with nonlinear diffusion when the time horizon is large enough. The minimal controllability time will be strictly positive. We prove a global steady state constrained controllability result for a quasilinear parabolic with nonlinearity in the diffus

Adi Glücksam

We present two companion results: Phragmén-Lindelöf type tight bounds on the minimal possible growth of subharmonic functions with recurrent zero set, and tight bounds on the maximal possible decay of the harmonic measure of the outer boundary of colander sets.

C. N. Ragiadakos

The characteristic property of the 2-dimensional Polyakov action is its independence on the metric tensor, without being topological. A renormalizable 4-dimensional action is found satisfying this fundamental property. The fundamental quantity of this pseudo-conformal field theory (PCFT) is the lorentzian Cauchy-Riemann (LCR) structure. This action describes

Tao Chen, Michael Ludkovski

We investigate the adaptive robust control framework for portfolio optimization and loss-based hedging under drift and volatility uncertainty. Adaptive robust problems offer many advantages but require handling a double optimization problem (infimum over market measures, supremum over the control) at each instance. Moreover, the underlying Bellman equations

Luis A. Anchordoqui, Ignatios Antoniadis, Dieter Lust, Jorge F. Soriano

[Abridged] We realize the Agrawal-Obied-Vafa (AOV) swampland proposal of fading dark matter by the model of Salam-Sezgin and its string realization of Cvetic-Gibbons-Pope. The model describes a compactification of 6-dimensional supergravity with a monopole background on a 2-sphere. In 4 dimensions, there are 2 scalar fields, $X$ and $Y $, and the effective p

Charlotte Rochereau, Benoît Sagot, Emmanuel Dupoux

Neural language models trained with a predictive or masked objective have proven successful at capturing short and long distance syntactic dependencies. Here, we focus on verb argument structure in German, which has the interesting property that verb arguments may appear in a relatively free order in subordinate clauses. Therefore, checking that the verb arg

Markus Fulmek

In a recent paper, Lai and Rohatgi proved a "shuffling theorem" for lozenge tilings of a hexagon with "dents" (i.e., missing triangles). Here, we shall point out that this follows immediately from the enumeration of Gelfand--Tsetlin patterns with given bottom row. This observation is also contained in a recent preprint of Byun.

Luca Ganassali, Marc Lelarge, Laurent Massoulié

In this paper we analyze a simple spectral method (EIG1) for the problem of matrix alignment, consisting in aligning their leading eigenvectors: given two matrices $A$ and $B$, we compute $v_1$ and $v'_1$ two corresponding leading eigenvectors. The algorithm returns the permutation $\hatπ$ such that the rank of coordinate $\hatπ(i)$ in $v_1$ and that of

Charlotte Knierim, Pascal Su

A classical result by Hajnal and Szemerédi from 1970 determines the minimal degree conditions necessary to guarantee for a graph to contain a $K_r$-factor. Namely, any graph on $n$ vertices, with minimum degree $δ(G) \ge \left(1-\frac{1}{r}\right) n$ and $r$ dividing $n$ has a $K_r$-factor. This result is tight but the extremal examples are unique in that th

Linfeng Jiang, Enrico Calzavarini, Chao Sun

Inertialess anisotropic particles in a Rayleigh-Bénard turbulent flow show maximal tumbling rates for weakly oblate shapes, in contrast with the universal behaviour observed in developed turbulence where the mean tumbling rate monotonically decreases with the particle aspect ratio. This is due to the concurrent effect of turbulent fluctuations and of a mean

Michael Brannan, Alexandru Chirvasitu, Ami Viselter

We prove a number of property (T) permanence results for locally compact quantum groups under exact sequences and the presence of invariant states, analogous to their classical versions. Along the way we characterize the existence of invariant weights on quantum homogeneous spaces of quotient type, and relate invariant states for LCQG actions on von Neumann

Yoshiki Ito, Taro Toyoizumi

Traveling waves are commonly observed across the brain. While previous studies have suggested the role of traveling waves in learning, the mechanism is still unclear. We adopted a computational approach to investigate the effect of traveling waves on synaptic plasticity. Our results indicate that traveling waves facilitate the learning of poly-synaptic netwo

Nora Frankl, Andrey Kupavskii

The following generalisation of the Erdős unit distance problem was recently suggested by Palsson, Senger and Sheffer. Given $k$ positive real numbers $δ_1,\dots,δ_k$, a $(k+1)$-tuple $(p_1,\dots,p_{k+1})$ in $\mathbb{R}^d$ is called a $(δ,k)$-chain if $\|p_j-p_{j+1}\| = δ_j$ for every $1\leq j \leq k$. What is the maximum number $C_k^d(n)$ of $(k,δ)$-chains

Scott Collier, Alexander Maloney, Henry Maxfield, Ioannis Tsiares

We obtain an asymptotic formula for the average value of the operator product expansion coefficients of any unitary, compact two dimensional CFT with $c>1$. This formula is valid when one or more of the operators has large dimension or -- in the presence of a twist gap -- has large spin. Our formula is universal in the sense that it depends only on the centr

Rossana Capuani, Prerona Dutta, Khai T. Nguyen

We establish a sharp estimate for a minimal number of binary digits (bits) needed to represent all bounded total generalized variation functions taking values in a general totally bounded metric space $(E,ρ)$ up to an accuracy of $\varepsilon>0$ with respect to the ${\bf L}^1$-distance. Such an estimate is explicitly computed in terms of doubling and packing

Cinjon Resnick, Zeping Zhan, Joan Bruna

Self-supervised research improved greatly over the past half decade, with much of the growth being driven by objectives that are hard to quantitatively compare. These techniques include colorization, cyclical consistency, and noise-contrastive estimation from image patches. Consequently, the field has settled on a handful of measurements that depend on linea

P. A. Azeef Muhammed, M. V. Volkov, K. Auinger

Locally inverse semigroups are regular semigroups whose idempotents form pseudo-semilattices. We characterise the categories that correspond to locally inverse semigroups in the realm of Nambooripad's cross-connection theory. Further, we specialise our cross-connection description of locally inverse semigroups to inverse semigroups and completely 0-simpl

Jakub Koncki

We calculate the equivariant motivic Chern class for configuration space of a quasiprojective (maybe singular) variety and the space of vectors with different directions. We prove the formulas for generating series of these classes. We generalize the localization theorems results about Bialynicki-Birula decomposition to acquire some stability for the motivic

Joachim von zur Gathen, Mark Giesbrecht, Konstantin Ziegler

The functional (de)composition of polynomials is a topic in pure and computer algebra with many applications. The structure of decompositions of (suitably normalized) polynomials f(x) = g(h(x)) in F[x] over a field F is well understood in many cases, but less well when the degree of f is divisible by the positive characteristic p of F. This work investigates

Mehmet S. Ismail

In this paper, I introduce a novel benchmark in games, super-Nash performance, and a solution concept, optimin, whereby players maximize their minimal payoff under unilateral profitable deviations by other players. Optimin achieves super-Nash performance in that, for every Nash equilibrium, there exists an optimin where each player not only receives but also

Yilong Xie, Gang Chen, Laszlo Pal Csernai

With the PICR hydrodynamic model, we study the polarization splitting between $Λ$ and $\barΛ$ at RHIC BES energy range, based on the meson field mechanism. Our results fit to the experimental data fairly well. Besides, two unexpected effect emerges: (1) the baryon density gradient has non-trivial and negative contribution to the polarization splitting; (2) f

Pablo Diaz

The melonic sector has been proven to be dominant in tensor models at large N. This is true as long as the observables we consider, composites of 2n tensors, are small. That is, if n is much smaller than N. In this paper, I argue that, in order to recover geometries (and then gravity) in the continuum limit, n must grow like N. In that case, I provide exampl

Sirshendu Bhattacharyya, Subinay Dasgupta

Dynamical phase transition in quantum many body systems is usually studied by taking it in the ground state and then quenching a parameter to a new value. We investigate here the dynamics when one performs the time evolution of a generic state and observe that the rate function related to the Loschmidt echo shows non-analytic behavior of two types, one relat

Matthew D. Frye, Jeremy M. Hutson

Characterizing quasibound states from coupled-channel scattering calculations can be a laborious task, involving extensive manual iteration and fitting. We present an automated procedure, based on the phase shift or S-matrix eigenphase sum, that reliably converges on a quasibound state (or scattering resonance) from some distance away. It may be used for bot

Hongshuo Chen, Heinz Siedentop

We show that the molecular relativistic Thomas-Fermi-Weizsäcker functional consisting of atoms of atomic numbers $Z_1,...,Z_k$ has a minimizer, if the particle number $N$ is constrained to a number less or equal to the total nuclear charge $Z:=Z_1+...+Z_K$. Moreover, there is no minimizer, if the particle number exceeds $2.56 Z$. This gives lower and upper b

Zhimin Yuan, Jiajin Yi, Zhengrong Luo, Zhongdao Jia

Although deep encoder-decoder networks have achieved astonishing performance for mitochondria segmentation from electron microscopy (EM) images, they still produce coarse segmentations with lots of discontinuities and false positives. Besides, the need for labor intensive annotations of large 3D dataset and huge memory overhead by 3D models are also major li

Guocheng Qian, Abdulellah Abualshour, Guohao Li, Ali Thabet

The effectiveness of learning-based point cloud upsampling pipelines heavily relies on the upsampling modules and feature extractors used therein. For the point upsampling module, we propose a novel model called NodeShuffle, which uses a Graph Convolutional Network (GCN) to better encode local point information from point neighborhoods. NodeShuffle is versat

Abdullah Salama, Oleksiy Ostapenko, Tassilo Klein, Moin Nabi

Deep Learning models have become the dominant approach in several areas due to their high performance. Unfortunately, the size and hence computational requirements of operating such models can be considerably high. Therefore, this constitutes a limitation for deployment on memory and battery constrained devices such as mobile phones or embedded systems. To a

Mulham Hijazi, Apostolos Pilaftsis

We study the effects of Goldstone modes on the stability of the vacuum in a $U(1)$ theory for a complex scalar field. The dynamics of the field resemble those of Keplerian motion in the presence of time-dependent friction, whose equations of motion imply a conserved quantity, $L$, reminiscent of conserved angular momentum. They also imply a persistent infini

Samuel G. G. Johnston, Amaury Lambert

We introduce a Poissonization method to study the coalescent structure of uniform samples from branching processes. This method relies on the simple observation that a uniform sample of size $k$ taken from a random set with positive Lebesgue measure may be represented as a mixture of Poisson samples with rate $λ$ and mixing measure $k \mathrm{d} λ/ λ$. We de

Andrei Bogatyrev

The best uniform rational approximation of the \emph{sign} function on two intervals separated by zero was explicitly solved by E.I. Zolotarëv in 1877. This optimization problem is the initial step in the staircase of the so called approximation problems for multiband filters which are of great importance for electrical engineering. We show that known in the

Hiroo Azuma

In this paper, we show that there are instances where eavesdropping causes noise reduction for a quantum key distribution (QKD) protocol. To witness these phenomena, we investigate a fault-tolerant six-state QKD protocol over a collective unitary noise channel. In this protocol, legitimate users send and receive two-qubit states that belong to the noiseless

Xiao Yang, Fangyun Wei, Hongyang Zhang, Jun Zhu

We consider universal adversarial patches for faces -- small visual elements whose addition to a face image reliably destroys the performance of face detectors. Unlike previous work that mostly focused on the algorithmic design of adversarial examples in terms of improving the success rate as an attacker, in this work we show an interpretation of such patche

Guohao Li, Guocheng Qian, Itzel C. Delgadillo, Matthias Müller

Architecture design has become a crucial component of successful deep learning. Recent progress in automatic neural architecture search (NAS) shows a lot of promise. However, discovered architectures often fail to generalize in the final evaluation. Architectures with a higher validation accuracy during the search phase may perform worse in the evaluation. A

Qisi Wang, M. Horio, K. von Arx, Y. Shen

We use resonant inelastic x-ray scattering to investigate charge-stripe correlations in La$_{1.675}$Eu$_{0.2}$Sr$_{0.125}$CuO$_4$. By differentiating elastic from inelastic scattering, it is demonstrated that charge-stripe correlations precede both the structural low-temperature tetragonal phase and the transport-defined pseudogap onset. The scattering peak

Sina Ebrahimi, Abulfazl Zakeri, Behzad Akbari, Nader Mokari

Network slicing is a crucial part of the 5G networks that communication service providers (CSPs) seek to deploy. By exploiting three main enabling technologies, namely, software-defined networking (SDN), network function virtualization (NFV), and network slicing, communication services can be served to the end-users in an efficient, scalable, and flexible ma

Junning Huang, Sirui Xie, Jiankai Sun, Qiurui Ma

Autonomous driving systems have a pipeline of perception, decision, planning, and control. The decision module processes information from the perception module and directs the execution of downstream planning and control modules. On the other hand, the recent success of deep learning suggests that this pipeline could be replaced by end-to-end neural control

Ibrahim Al-Dayel, Sharief Deshmukh, Olga Belova

In this paper, we show that given a nontrivial concircular vector field $\boldsymbol{u}$ on a Riemannian manifold $(M,g)$ with potential function $f$, there exists a unique smooth function $ρ$ on $M$ that connects $\boldsymbol{u}$ to the gradient of potential function $\nabla f$, which we call the connecting function of the concircular vector field $\boldsym

V. Del Duca, S. Druc, J. M. Drummond, C. Duhr

We propose an all-loop expression for scattering amplitudes in planar N=4 super Yang-Mills theory in multi-Regge kinematics valid for all multiplicities, all helicity configurations and arbitrary logarithmic accuracy. Our expression is arrived at from comparing explicit perturbative results with general expectations from the integrable structure of a closely

Mohsen Tajallifar, Sina Ebrahimi, Mohammad Reza Javan, Nader Mokari

In this paper, we propose a novel resource management scheme that jointly allocates the transmit power and computational resources in a centralized radio access network architecture. The network comprises a set of computing nodes to which the requested tasks of different users are offloaded. The optimization problem minimizes the energy consumption of task o

Łukasz T. Stȩpień

Some exact solutions of boundary or initial conditions formulated for Bogomolny equations (derived by using the strong necessary conditions and associated with some ordinary equation and some partial differential equations), have been found. Besides, a degeneracy of the hamiltonian for the restricted baby Skyrme model has been established.

Paulo J. Almeida, Julia Lieb

Maximum distance profile (MDP) convolutional codes have been proven to be very suitable for transmission over an erasure channel. In addition, the subclass of complete MDP convolutional codes has the ability to restart decoding after a burst of erasures. However, there is a lack of constructions of these codes over fields of small size. In this paper, we int

Isac Arnekvist, Dmytro Kalpakchi

This work is a reproducibility study of the paper of Antoniou and Storkey [2019], published at NeurIPS 2019. Our results are in parts similar to the ones reported in the original paper, supporting the central claim of the paper that the proposed novel method, called Self-Critique and Adapt (SCA), improves the performance of MAML++. The conducted additional e

Yang Song, Qiyu Kang, Wee Peng Tay

Though deep learning has been applied successfully in many scenarios, malicious inputs with human-imperceptible perturbations can make it vulnerable in real applications. This paper proposes an error-correcting neural network (ECNN) that combines a set of binary classifiers to combat adversarial examples in the multi-class classification problem. To build an

Jeffrey Hawke, Richard Shen, Corina Gurau, Siddharth Sharma

Hand-crafting generalised decision-making rules for real-world urban autonomous driving is hard. Alternatively, learning behaviour from easy-to-collect human driving demonstrations is appealing. Prior work has studied imitation learning (IL) for autonomous driving with a number of limitations. Examples include only performing lane-following rather than follo

Anton Kolonin

The problem of reliable democratic governance is important for survival of any community, and it will be more critical over time communities with levels of social connectivity in society rapidly increasing with speeds and scales of electronic communication. In order to face such challenge, different sorts of rating and reputation systems are being developed,

Michel Waldschmidt

Let $s_0,s_1,\dots,s_{m-1}$ be complex numbers and $r_0,\dots,r_{m-1}$ rational integers in the range $0\le r_j\le m-1$. Our first goal is to prove that if an entire function $f$ of sufficiently small exponential type satisfies $f^{(mn+r_j)}(s_j)\in{\mathbb Z}$ for $0\le j\le m-1$ and all sufficiently large $n$, then $f$ is a polynomial. Under suitable assum

Nadia Labai, Tomer Kotek, Magdalena Ortiz, Helmut Veith

We introduce a novel automata model, called pebble-intervals automata (PIA), and study its power and closure properties. PIAs are tailored for a decidable fragment of FO that is important for reasoning about structures that use data values from infinite domains: the two-variable fragment with one total preorder and its induced successor relation, one linear

Michael Luo, Jiahao Yao, Richard Liaw, Eric Liang

The practical usage of reinforcement learning agents is often bottlenecked by the duration of training time. To accelerate training, practitioners often turn to distributed reinforcement learning architectures to parallelize and accelerate the training process. However, modern methods for scalable reinforcement learning (RL) often tradeoff between the throug

Yanli Ai, Liming Dou, Chenwei Yang, Luming Sun

We analyze the X-ray, optical, and mid-infrared data of a "changing-look" Seyfert galaxy \sdssj15 at $z\simeq0.086$. Over a period of one decade (2009 - 2018), its broad H$α$ line intensity increased by a factor of $\sim$4. Meanwhile, the X-ray emission in 2014 as observed by \chandra\ was about five times brighter than that in 2010 by {\it Suzaku},

Gaurav Sinha, Ayush Chauhan, Aurghya Maiti, Naman Poddar

We study the problem of separating a mixture of distributions, all of which come from interventions on a known causal bayesian network. Given oracle access to marginals of all distributions resulting from interventions on the network, and estimates of marginals from the mixture distribution, we want to recover the mixing proportions of different mixture comp

Jia-Hong Huang, Modar Alfadly, Bernard Ghanem, Marcel Worring

Deep neural networks have been playing an essential role in the task of Visual Question Answering (VQA). Until recently, their accuracy has been the main focus of research. Now there is a trend toward assessing the robustness of these models against adversarial attacks by evaluating the accuracy of these models under increasing levels of noisiness in the inp

Yihang Ding, Xiaosheng Xiao, Kewei Liu, Shuzheng Fan

Dissipative nonlinear wave dynamics have been investigated extensively in mode-locked lasers with single transverse-mode, whereas there are few studies related to three-dimensional nonlinear dynamics within lasers. Recently, spatiotemporal mode-locking (STML) was proposed in lasers with small modal (i.e., transverse-mode) dispersion, which has been considere

Adel P. Kazemi, Farshad Kazemnejad

The total dominator total coloring of a graph is a total coloring of the graph such that each object of the graph is adjacent or incident to every object of some color class. The minimum namber of the color classes of a total dominator total coloring of a graph is called the total dominator total chromatic number of the graph. Here, we will find the total do

Lucy Linder, Michael Jungo, Jean Hennebert, Claudiu Musat

This paper presents SwissCrawl, the largest Swiss German text corpus to date. Composed of more than half a million sentences, it was generated using a customized web scraping tool that could be applied to other low-resource languages as well. The approach demonstrates how freely available web pages can be used to construct comprehensive text corpora, which a

Shady Abu Hussein, Tom Tirer, Raja Giryes

The single image super-resolution task is one of the most examined inverse problems in the past decade. In the recent years, Deep Neural Networks (DNNs) have shown superior performance over alternative methods when the acquisition process uses a fixed known downsampling kernel-typically a bicubic kernel. However, several recent works have shown that in pract

Wei Sun, Xian-Hui Ge

We examine the complexity/volume conjecture and further investigate the possible connections between complexity and partition function. The complexity/volume 2.0 states that the complexity growth rate $\mathcal{\dot{C}}\sim PV$. In the standard statistics, there is a fundamental relation among $PV$, the grand potential $Ω$ and the partition function $\mathca

Karthikeya Racharla, Vineet Kumar, Chaudhari Bhushan Jayant, Ankit Khairkar

This work aims to examine one of the cornerstone problems of Musical Instrument Retrieval (MIR), in particular, instrument classification. IRMAS (Instrument recognition in Musical Audio Signals) data set is chosen for this purpose. The data includes musical clips recorded from various sources in the last century, thus having a wide variety of audio quality.

Giuseppina di Blasio, Pier Domenico Lamberti

We study the dependence of the first eigenvalue of the Finsler $p$-Laplacian and the corresponding eigenfunctions upon perturbation of the domain and we generalize a few results known for the standard $p$-Laplacian. In particular, we prove a Frechét differentiability result for the eigenvalues, we compute the corresponding Hadamard formulas and we prove a co

Guillaume Tahar

A branched affine structure on a compact topological surface with marked points is a complex affine structure outside the marked points. We give a proof of an unpublished foundational theorem of Veech, stating that any branched affine surface can be decomposed into affine triangles and some annulus-shaped cylinders. Then, we prove that any pair of such decom

Bin He, Di Zhou, Jinghui Xiao, Xin jiang

Complex node interactions are common in knowledge graphs, and these interactions also contain rich knowledge information. However, traditional methods usually treat a triple as a training unit during the knowledge representation learning (KRL) procedure, neglecting contextualized information of the nodes in knowledge graphs (KGs). We generalize the modeling

Biao Zhang, Peter Wonka

In this paper we propose a new framework for point cloud instance segmentation. Our framework has two steps: an embedding step and a clustering step. In the embedding step, our main contribution is to propose a probabilistic embedding space for point cloud embedding. Specifically, each point is represented as a tri-variate normal distribution. In the cluster

Huangxing Lin, Weihong Zeng, Xinghao Ding, Yue Huang

The performance of a deep neural network is highly dependent on its training, and finding better local optimal solutions is the goal of many optimization algorithms. However, existing optimization algorithms show a preference for descent paths that converge slowly and do not seek to avoid bad local optima. In this work, we propose Learning Rate Dropout (LRD)

Omid Zabeti

Suppose $X$ is a locally solid vector lattice. In this paper, we introduce the notion "$AM$-property" in $X$ as an extension for $AM$-spaces in the category of all Banach lattices. With the aid of this concept, we characterize spaces in which bounded sets and order bounded sets agree. This, in turn, characterizes conditions under which each class of

Laurent Condat, Daichi Kitahara, Andrés Contreras, Akira Hirabayashi

Convex nonsmooth optimization problems, whose solutions live in very high dimensional spaces, have become ubiquitous. To solve them, the class of first-order algorithms known as proximal splitting algorithms is particularly adequate: they consist of simple operations, handling the terms in the objective function separately. In this overview, we demystify a s

Rafaela Castro, Yania M. Souto, Eduardo Ogasawara, Fabio Porto

Applying machine learning models to meteorological data brings many opportunities to the Geosciences field, such as predicting future weather conditions more accurately. In recent years, modeling meteorological data with deep neural networks has become a relevant area of investigation. These works apply either recurrent neural networks (RNN) or some hybrid a

K. Sheshadri, A. Chainani

A model of a mixture of spinless fermions and spin-zero hardcore bosons, with filling fractions $ρ_F$ and $ρ_B$, respectively, on a two-dimensional square lattice with {\em composite} hopping $t$ is presented. In this model, hopping swaps the locations of a fermion and a boson at nearest-neighbor sites. When $ρ_F+ρ_B=1$, the fermion hopping amplitude $ϕ$ and

Dominik M. Juraschek, Prineha Narang, Nicola A. Spaldin

The magneto-optical and opto-magnetic effects describe the interaction of light with a magnetic medium. The most prominent examples are the Faraday and Cotton-Mouton effects that modify the transmission of light through a medium, and the inverse Faraday and inverse Cotton-Mouton effects that produce effective magnetic fields for the spin in the material. Her

Mutasim Mim

We prove that the Wiener Index $W(G)$ of a Maximal Planar graph $G$ with $n$ vertices satisfies $W(G) \leq \Big{\lfloor} \frac{1}{18}(n^3 + 3n^2) \Big{\rfloor}$ for $3 \leq n \leq 18$.

Md. Hasibur Rahman, Chowdhury Rafeed Rahman, Ruhul Amin, Md. Habibur Rahman Sifat

Question classification (QC) is the primary step of the Question Answering (QA) system. Question Classification (QC) system classifies the questions in particular classes so that Question Answering (QA) System can provide correct answers for the questions. Our system categorizes the factoid type questions asked in natural language after extracting features o

Igor Lima, Josyane Pereira

Let $G$ be a group, define an equivalence relation $\sim$ as below: $$\forall \ g, h \in G, \ g \sim h \Longleftrightarrow |g| = |h|$$ the set of sizes of equivalence classes with respect to this relation is called the same-order type of $G$ and denoted by $α(G)$. And $G$ is said a $α_n$-group if $|α(G)|=n$. Let $π(G)$ be the set of prime divisors of the ord

Jihyeon Lee, Sho Arora

Despite their importance in training artificial intelligence systems, large datasets remain challenging to acquire. For example, the ImageNet dataset required fourteen million labels of basic human knowledge, such as whether an image contains a chair. Unfortunately, this knowledge is so simple that it is tedious for human annotators but also tacit enough suc

Yongjun Li, Yue Hao, Kilean Hwang, Robert Rainer

A fast method for dynamic aperture (DA) optimization of storage rings has been developed through the use of reversal integration. While chaotic dynamical systems have exact time-reversal symmetry, numerical forward integration differs from its reversal due to scaled cumulative round-off errors. The difference, intrinsically associated with the Lyapunov expon

Ali Al-Aradi, Adolfo Correia, Danilo de Frietas Naiff, Gabriel Jardim

We extend the Deep Galerkin Method (DGM) introduced in Sirignano and Spiliopoulos (2018)} to solve a number of partial differential equations (PDEs) that arise in the context of optimal stochastic control and mean field games. First, we consider PDEs where the function is constrained to be positive and integrate to unity, as is the case with Fokker-Planck eq

Ali Ghanbari

In the context of test case based automated program repair (APR), the research community call the patches that pass all the test cases but fail to actually fix the bug test case overfitted patches. Currently, overfitted patches has to be manually inspected by the users. Being a labor intensive activity that hinders widespread adoption of APR tools, automatic

Ximena Fernández

We introduce a novel combinatorial method to study $Q^{**}$-transformations of group presentations or, equivalently, 3-deformations of CW-complexes of dimension 2. Our procedure is based on a refinement of discrete Morse theory that gives a Whitehead simple homotopy equivalence from a regular CW-complex to the simplified Morse CW-complex, with an explicit de

Jia Shi, Ruipeng Li, Yuanzhe Xi, Yousef Saad

A new approach is presented to compute the seismic normal modes of a fully heterogeneous, rotating planet. Special care is taken to separate out the essential spectrum in the presence of a fluid outer core. The relevant elastic-gravitational system of equations, including the Coriolis force, is subjected to a mixed finite-element method, while self-gravitati

Cecilia Balocchi, Sameer K. Deshpande, Edward I. George, Shane T. Jensen

Accurate estimation of the change in crime over time is a critical first step towards better understanding of public safety in large urban environments. Bayesian hierarchical modeling is a natural way to study spatial variation in urban crime dynamics at the neighborhood level, since it facilitates principled ``sharing of information'' between spatia

Carolyn A. Kierans, Steven E. Boggs, Andreas Zoglauer, Alex W. Lowell

The signature of positron annihilation, namely the 511 keV $γ$-ray line, was first detected coming from the direction of the Galactic center in the 1970's, but the source of Galactic positrons still remains a puzzle. The measured flux of the annihilation corresponds to an intense steady source of positron production, with an annihilation rate on the orde

Siming Ma, David Brooks, Gu-Yeon Wei

We propose a new algorithm for training neural networks with binary activations and multi-level weights, which enables efficient processing-in-memory circuits with embedded nonvolatile memories (eNVM). Binary activations obviate costly DACs and ADCs. Multi-level weights leverage multi-level eNVM cells. Compared to existing algorithms, our method not only wor

Mohammad Abdullah, Mykhailo Dalchenko, Teruki Kamon, Denis Rathjens

We explore the physics of a new neutral gauge boson, ($Z^\prime$), coupling to only third-generation particles with a mass near the electroweak gauge boson mass poles. A $Z^\prime$ boson produced by top quarks and decaying to tau leptons is considered. With a simple search strategy inspired by existing analyses of the standard model gauge boson production in

Heliudson Bernardo

In this letter we discuss the implications of the recently proposed TransPlanckian Censorship Conjecture (TCC) for Holographic Cosmology. For models of holographic inflation that are dual to inverse renormalization group (RG) flows, assuming the TCC to be true, we found a bound on the running of the field theory coupling and the corresponding maximum energy

Oskar Słowik, Martin Hebenstreit, Barbara Kraus, Adam Sawicki

Central in entanglement theory is the characterization of local transformations among pure multipartite states. As a first step towards such a characterization, one needs to identify those states which can be transformed into each other via local operations with a non-vanishing probability. The classes obtained in this way are called SLOCC classes. They can

Hideki Ochiai, Patrick Mitran, H. Vincent Poor

This paper focuses on an improved Gaussian approximation (GA) based construction of polar codes with successive cancellation (SC) decoding over an additive white Gaussian noise (AWGN) channel. Arikan has proven that polar codes with low-complexity SC decoder can approach the channel capacity of an arbitrary symmetric binary-input discrete memoryless channel,