July 2019 arXiv papers — page 23

Oksana Bezushchak, Bogdana Oliynyk

An $F$-algebra $A$ with unit $1$ is said to be a locally matrix algebra if an arbitrary finite collection of elements $a_1,$ $\ldots,$ $a_s $ from $ A$ lies in a subalgebra $B$ with $1$ of the algebra $A$, that is isomorphic to a matrix algebra $M_n(F),$ $n\geq 1.$ To an arbitrary unital locally matrix algebra $A$ we assign a Steinitz number $\mathbf{n}(A)$

José E. Chacón

The misclassification error distance and the adjusted Rand index are two of the most commonly used criteria to evaluate the performance of clustering algorithms. This paper provides an in-depth comparison of the two criteria, aimed to better understand exactly what they measure, their properties and their differences. Starting from their population origins,

Xinxing Wu, Guanrong Chen

This paper proves that a binary operation ${\star}$ on ${[0, 1]}$, ensuring that the binary operation ${\curlywedge}$ is a ${t}$-norm or ${\curlyvee}$ is a ${t}$-conorm, is a ${t}$-norm, where ${\curlywedge}$ and ${\curlyvee}$ are special convolution operations defined by $${(f\curlywedge g)(x)=\sup\left\{f(y)\star g(z): y\vartriangle z=x\right\},} $$ $${(f\

Gareth Boreland, Ivan G. Todorov, Andreas Winter

We define non-commutative versions of the vertex packing polytope, the theta convex body and the fractional vertex packing polytope of a graph, and establish a quantum version of the Sandwich Theorem of Gr\"{o}tschel, Lov\'{a}sz and Schrijver. We define new non-commutative versions of the Lov\'{a}sz number of a graph which lead to an upper bound of the zero-

Bulla Rajesh, Mohammed Javed, Ratnesh, Shubham Srivastava

The popularity of Convolutional Neural Network (CNN) in the field of Image Processing and Computer Vision has motivated researchers and industrialist experts across the globe to solve different challenges with high accuracy. The simplest way to train a CNN classifier is to directly feed the original RGB pixels images into the network. However, if we intend t

Tony J. Puthenpurakal

In this paper we determine the possible Hilbert functions of a Cohen-Macaulay local ring of dimension $d$, multiplicity $e$ and first Hilbert coefficient $e_1$ in the case $e_1 = e + 2$.

Alexander Steen, Christoph Benzmüller

Leo-III is an automated theorem prover for extensional type theory with Henkin semantics and choice. Reasoning with primitive equality is enabled by adapting paramodulation-based proof search to higher-order logic. The prover may cooperate with multiple external specialist reasoning systems such as first-order provers and SMT solvers. Leo-III is compatible w

Peng Xu

Let $p$ be a prime number. We show in this short note that mod-$p$ maximal compact inductions of a $p$-adic split reductive group do not have irreducible admissible subrepresentations.

Yumo Xu, Mirella Lapata

In this paper we introduce domain detection as a new natural language processing task. We argue that the ability to detect textual segments which are domain-heavy, i.e., sentences or phrases which are representative of and provide evidence for a given domain could enhance the robustness and portability of various text classification applications. We propose

Qunyi Bie, Qiru Wang, Zheng-an Yao

Danchin and He (Math. Ann. 64: 1-38, 2016) recently established the global existence in critical $L^p$-type regularity framework for the $N$-dimensional $(N\geq 3)$ non-isentropic compressible Navier-Stokes equations. The purpose of this paper is to further investigate the large time behavior of solutions constructed by them. More precisely, we prove that if

Mohammed Khwaja, Aleksandar Matic

Previous literature has explored automatic personality modelling using smartphone data for its potential to personalise mobile services. Although passive modelling of personality removes the burden of completing lengthy questionnaires, the fact that such models typically require a few weeks or months of personal data can negatively impact user's engagement.

Zhen-Yan Lu, Cheng-Jun Xia, Marco Ruggieri

We study the thermodynamics and the susceptibilities of quark matter in the framework of two-flavor Nambu-Jona-Lasinio model at finite isospin chemical potential and temperature. Isospin number density, normalized energy density and trace anomaly are shown to be in good agreement with the available lattice data as well as with the results from chiral perturb

Xin Wang, Bo Wu, Yun Ye, Yueqi Zhong

Existing works about fashion outfit compatibility focus on predicting the overall compatibility of a set of fashion items with their information from different modalities. However, there are few works explore how to explain the prediction, which limits the persuasiveness and effectiveness of the model. In this work, we propose an approach to not only predict

You Zhou

Entanglement is an essential resource in many quantum information tasks and entanglement witness is a widely used tool for its detection. In experiments the prepared state generally deviates from the target state due to some noise. Normally the white noise model is applied to quantifying such derivation and in the same time reveals the robustness of the witn

Hermann Schulz-Baldes, Liam Urban

This note considers Sturm oscillation theory for regular matrix Sturm-Liouville operators on finite intervals and for matrix Jacobi operators. The number of space oscillations of the eigenvalues of the matrix Pr\"ufer phases at a given energy, defined by a suitable lift in the Jacobi case, is shown to be equal to the number of eigenvalues below that energy.

Shengbin Jia, Yang Xiang

Open relation extraction (ORE) remains a challenge to obtain a semantic representation by discovering arbitrary relation tuples from the unstructured text. Conventional methods heavily depend on feature engineering or syntactic parsing, they are inefficient or error-cascading. Recently, leveraging supervised deep learning structures to address the ORE task i

Ben Van Calster, Maarten van Smeden, Ewout W. Steyerberg

When developing risk prediction models, shrinkage methods are recommended, especially when the sample size is limited. Several earlier studies have shown that the shrinkage of model coefficients can reduce overfitting of the prediction model and subsequently result in better predictive performance on average. In this simulation study, we aimed to investigate

Florian Dorsch, Hermann Schulz-Baldes

For one-dimensional random Schr\"odinger operators, the integrated density of states is known to be given in terms of the (averaged) rotation number of the Pr\"ufer phase dynamics. This paper develops a controlled perturbation theory for the rotation number around an energy, at which all the transfer matrices commute and are hyperbolic. Such a hyperbolic cri

B. M. Giuliano, A. A. Gavdush, B. Müller, K. I. Zaytsev

Context: Reliable, directly measured optical properties of astrophysical ice analogs in the infrared (IR) and terahertz (THz) range are missing. These parameters are of great importance to model the dust continuum radiative transfer in dense and cold regions, here thick ice mantles are present, and are necessary for the interpretation of future observations

Ehud Meir

We formulate the generation of finite dimensional pointed Hopf algebras by group-like elements and skew-primitives in geometric terms. This is done through a more general study of connected and coconnected Hopf algebras inside a braided fusion category $\mathcal{C}$. We describe such Hopf algebras as orbits for the action of a reductive group on an affine va

Paulo Luz, Sante Carloni

We generalize the Tolman-Oppenheimer-Volkoff equations for space-times endowed with a Weyssenhoff like torsion field in the Einstein-Cartan theory. The new set of structure equations clearly show how the presence of torsion affects the geometry of the space-time. We obtain new exact solutions for compact objects with non-null spin surrounded by vacuum, explo

R. M. Arkhipov, A. V. Pakhomov, M. V. Arkhipov, A. Demircan

We propose a novel scheme to generate single-cycle terahertz (THz) pulses via reflection of an optical femtosecond pulse train from a thin layer of nonlinear resonant medium. Our method is based on a coherent control of low-frequency oscillations and free induction decay in the medium. The specific single-cycle shape of generated THz pulses requires a plane

Will Hoffer, Adu Vengal, Vilas Winstein

In their paper entitled "Quantum Enhancements and Biquandle Brackets," Nelson, Orrison, and Rivera introduced biquandle brackets, which are customized skein invariants for biquandle-colored links. We prove herein that if a biquandle bracket is the pointwise product of another biquandle bracket with some function $\phi$, then $\phi$ is a a biquandle 2-cocycle

Audrey Repetti, Yves Wiaux

We present a forward-backward-based algorithm to minimize a sum of a differentiable function and a nonsmooth function, both being possibly nonconvex. The main contribution of this work is to consider the challenging case where the nonsmooth function corresponds to a sum of non-convex functions, resulting from composition between a strictly increasing, concav

E. Aprile, J. Aalbers, F. Agostini, M. Alfonsi

We report constraints on light dark matter (DM) models using ionization signals in the XENON1T experiment. We mitigate backgrounds with strong event selections, rather than requiring a scintillation signal, leaving an effective exposure of $(22 \pm 3)$ tonne-days. Above $\sim\!0.4\,\mathrm{keV}_\mathrm{ee}$, we observe $<1 \, \text{event}/(\text{tonne} \time

Rongchang Xie, Fei Yu, Jiachao Wang, Yizhou Wang

In recent years, object detection has shown impressive results using supervised deep learning, but it remains challenging in a cross-domain environment. The variations of illumination, style, scale, and appearance in different domains can seriously affect the performance of detection models. Previous works use adversarial training to align global features ac

Fei Yu, Jie Zhao, Yanjun Gong, Zhi Wang

Segmenting coronary arteries is challenging, as classic unsupervised methods fail to produce satisfactory results and modern supervised learning (deep learning) requires manual annotation which is often time-consuming and can some time be infeasible. To solve this problem, we propose a knowledge transfer based shape-consistent generative adversarial network

S. Akbari, E. R. van Dam, M. H. Fakharan

In this paper, we study the multiplicity of the Laplacian eigenvalues of trees. It is known that for trees, integer Laplacian eigenvalues larger than $1$ are simple and also the multiplicity of Laplacian eigenvalue $1$ has been well studied before. Here we consider the multiplicities of the other (non-integral) Laplacian eigenvalues. We give an upper bound a

Haris Mumtaz, Shahid Latif, Fabian Beck, Daniel Weiskopf

Good code quality is a prerequisite for efficiently developing maintainable software. In this paper, we present a novel approach to generate exploranative (explanatory and exploratory) data-driven documents that report code quality in an interactive, exploratory environment. We employ a template-based natural language generation method to create textual expl

Tomáš Brauner, Christoph P. Hofmann

We analyze the thermodynamic properties of antiferromagnetic solids subjected to a combination of mutually orthogonal uniform magnetic and staggered fields. Low-temperature series for the pressure, order parameter and magnetization up to two-loop order in the effective expansion are established. We evaluate the self-energy and the dispersion relation of the

Iker de las Heras, Marta Morigi

It is well known that the set of values of a lower central word in a group $G$ need not be a subgroup. For a fixed lower central word $\gamma_r$ and for $p\ge 5$, Guralnick showed that if $G$ is a finite $p$-group such that the verbal subgroup $\gamma_r(G)$ is abelian and 2-generator, then $\gamma_r(G)$ consists only of $\gamma_r$-values. In this paper we ex

Marco Caroccia, Matteo Focardi, Nicolas Van Goethem

Following the global method for relaxation we prove an integral representation result for a large class of variational functionals naturally defined on the space of functions with Bounded Deformation. Mild additional continuity assumptions are required on the functionals.

Farhan Khan

We analyze damage propagation modeling of turbo-engines in a data-driven approach. We investigate subspace tracking assuming a low dimensional manifold structure and a static behavior during the healthy state of the machines. Our damage propagation model is based on the deviation of the data from the static behavior and uses the notion of health index as a m

Ignacio Vergara

We give a new proof of a classical result which provides a one-to-one correspondence between positive definite radial kernels on a homogeneous tree and finite Borel measures on the interval $[-1,1]$. Our methods allow us to find a new characterisation in terms of positive trace-class operators on $\ell_2$. Furthermore, we extend both characterisations to fin

Josip Šarić, Marin Oršić, Tonći Antunović, Sacha Vražić

Future anticipation is of vital importance in autonomous driving and other decision-making systems. We present a method to anticipate semantic segmentation of future frames in driving scenarios based on feature-to-feature forecasting. Our method is based on a semantic segmentation model without lateral connections within the upsampling path. Such design ensu

Bin Jiang, Wenxuan Tu, Chao Yang, Junsong Yuan

Semantic segmentation for lightweight object parsing is a very challenging task, because both accuracy and efficiency (e.g., execution speed, memory footprint or computational complexity) should all be taken into account. However, most previous works pay too much attention to one-sided perspective, either accuracy or speed, and ignore others, which poses a g

Andrii Mironchenko, Christophe Prieur, Fabian Wirth

We derive a saturated feedback control, which locally stabilizes a linear reaction-diffusion equation. In contrast to most other works on this topic, we do not assume the Lyapunov stability of the uncontrolled system and consider general unstable systems. Using Lyapunov methods, we provide estimates for the region of attraction for the closed-loop system, gi

Natalia Chepiga, Frédéric Mila

We perform a systematic DMRG investigation of the two natural spin-1 generalizations of the spin-1/2 Majumdar-Ghosh chain, the spin-1 $J_1-J_2$ Heisenberg chain, where $J_2$ is a next-nearest neighbor Heisenberg coupling, and the spin-1 $J_1-J_3$ model, where $J_3$ refers to a three-site interaction defined by $J_3\left[({\bf S}_{i-1}\cdot {\bf S}_i)({\bf S}

Francisco J. Aragón Artacho, Rubén Campoy, Phan T. Vuong

The Difference of Convex functions Algorithm (DCA) is widely used for minimizing the difference of two convex functions. A recently proposed accelerated version, termed BDCA for Boosted DC Algorithm, incorporates a line search step to achieve a larger decrease of the objective value at each iteration. Thanks to this step, BDCA usually converges much faster t

Anjali Jaiswal, D. Bahuguna

In this paper we investigate fractional differential equations with Hilfer fractional derivative of order $1<\gamma<2$ and type $\delta \in [0,1]$ in a Banach space. We introduce a family of general fractional cosine operator functions of order $1<\gamma<2$ and type $\delta \in [0,1]$ and discuss their properties to give a suitable definition of mild solutio

Maria Chushnyakova, Igor Gontchar, Natalya Khmyrova

For the first time, the precise data on the above barrier fusion (capture) cross-sections for the reactions involving spherical colliding nuclei are quantitatively analyzed using the relativistic mean-field effective interaction. The parameter sets NL1, NL2, NL3, and HS are employed. The analysis is performed within the framework of the fluctuation-dissipati

Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Marco Maggini

Neural-symbolic approaches have recently gained popularity to inject prior knowledge into a learner without requiring it to induce this knowledge from data. These approaches can potentially learn competitive solutions with a significant reduction of the amount of supervised data. A large class of neural-symbolic approaches is based on First-Order Logic to re

Felicidad Aguado, Pedro Cabalar, Jorge Fandinno, David Pearce

A common feature in Answer Set Programming is the use of a second negation, stronger than default negation and sometimes called explicit, strong or classical negation. This explicit negation is normally used in front of atoms, rather than allowing its use as a regular operator. In this paper we consider the arbitrary combination of explicit negation with nes

Sara Moccia, Lucia Migliorelli, Rocco Pietrini, Emanuele Frontoni

Preterm infants' limb-pose estimation is a crucial but challenging task, which may improve patients' care and facilitate clinicians in infant's movements monitoring. Work in the literature either provides approaches to whole-body segmentation and tracking, which, however, has poor clinical value, or retrieve a posteriori limb pose from limb segmentation, inc

Simone Dussi, Justin Tauber, Jasper van der Gucht

By performing extensive simulations with unprecedentedly large system sizes, we unveil how rigidity influences the fracture of disordered materials. We observe the largest damage in networks with connectivity close to the isostatic point and when the rupture thresholds are small. However, regardless of network and spring properties, a more brittle fracture i

Gui-Jun Ding, Stephen F. King, Xiang-Gan Liu

We present a comprehensive analysis of neutrino mass and lepton mixing in theories with $A_4$ modular symmetry, where the only flavon field is the single modulus field $\tau$, and all masses and Yukawa couplings are modular forms. Similar to previous analyses, we discuss all the simplest neutrino sectors arising from both the Weinberg operator and the type I

Pedro García-López, Marc Sánchez-Artigas, Simon Shillaker, Peter Pietzuch

Serverless computing has become very popular today since it largely simplifies cloud programming. Developers do not need to longer worry about provisioning or operating servers, and they pay only for the compute resources used when their code is run. This new cloud paradigm suits well for many applications, and researchers have already begun investigating th

Masahiro Ibe, Shin Kobayashi, Ryo Nagai, Wakutaka Nakano

The asymmetric dark matter (ADM) scenario can solve the coincidence problem between the baryon and the dark matter (DM) abundance when the DM mass is of ${\cal O}(1)\,$GeV. In the ADM scenarios, composite dark matter is particularly motivated, as it can naturally provide the DM mass in the ${\cal O}(1)\,$GeV range and a large annihilation cross section simul

J. Álvarez-Márquez, D. Burgarella, V. Buat, O. Ilbert

This work explores from a statistical point of view the rest-frame Far-ultraviolet (FUV) to Far-infrared (FIR) emission of a population of Lyman break galaxies (LBGs) at $z\sim3$ that cannot be individually detected from current FIR observations. We perform a stacking analysis over a sample of $\sim$17000 LBGs at redshift $2.5<z<3.5$ in the COSMOS field. The

Lars Lund Thomsen, Jane Lixin Dai, Enrico Ramirez-Ruiz, Erin Kara

X-ray reverberation has proven to be a powerful tool capable of probing the innermost region of accretion disks around compact objects. Current theoretical effort generally assumes that the disk is geometrically thin, optically thick and orbiting with Keplerian speed. Thus, these models cannot be applied to systems where super-Eddington accretion happens bec

Weixun Wang, Tianpei Yang, Yong Liu, Jianye Hao

In multiagent systems (MASs), each agent makes individual decisions but all of them contribute globally to the system evolution. Learning in MASs is difficult since each agent's selection of actions must take place in the presence of other co-learning agents. Moreover, the environmental stochasticity and uncertainties increase exponentially with the increase

Carlos G. Velasco, Belén Paredes

Ladder architectures are fruitful systems to realize topological phases of matter. Here we present a classification of ladder models giving rise to topological insulators. We identify six different types of topological ladder models, three in the BDI symmetry class, and three in the AIII symmetry class. They correspond to six distinct configurations of Wilso

Zhiyu Cao, Jie Su, Huijun Jiang, Zhonghuai Hou

Understanding stochastic thermodynamics of active Brownian particles (ABPs) system has been an important topic in very recent years. In this article we study a general model of active Brownian particle systems by introducing a coarse-grained Fokker-Planck equation, which allows us to identify an effective entropy production along a stochastic trajectory, whe

Ruize Han, Yujun Zhang, Wei Feng, Chenxing Gong

Video surveillance can be significantly enhanced by using both top-view data, e.g., those from drone-mounted cameras in the air, and horizontal-view data, e.g., those from wearable cameras on the ground. Collaborative analysis of different-view data can facilitate various kinds of applications, such as human tracking, person identification, and human activit

Rocio Gonzalez-Diaz, Miguel A. Gutiérrez-Naranjo, Eduardo Paluzo-Hidalgo

It is well known that Artificial Neural Networks are universal approximators. The classical result proves that, given a continuous function on a compact set on an n-dimensional space, then there exists a one-hidden-layer feedforward network which approximates the function. Such result proves the existence, but it does not provide a method for finding it. In

David Beltran, Luis Vega

We prove certain $L^2(\mathbb{R}^n)$ bilinear estimates for Fourier extension operators associated to spheres and hyperboloids under the action of the $k$-plane transform. As the estimates are $L^2$-based, they follow from bilinear identities: in particular, these are the analogues of a known identity for paraboloids, and may be seen as higher-dimensional ve

Bartosz Bieganowski, Simone Secchi

We show that ground state solutions to the nonlinear, fractional problem \begin{align*} \left\{ \begin{array}{ll} (-\Delta)^{s} u + V(x) u = f(x,u) &\quad \mathrm{in} \ \Omega, \newline u = 0 &\quad \mathrm{in} \ \mathbb{R}^N \setminus \Omega, \end{array} \right. \end{align*} on a bounded domain $\Omega \subset \mathbb{R}^N$, converge (along a subsequence) i

Isabel Funke, Sebastian Bodenstedt, Florian Oehme, Felix von Bechtolsheim

Automatically recognizing surgical gestures is a crucial step towards a thorough understanding of surgical skill. Possible areas of application include automatic skill assessment, intra-operative monitoring of critical surgical steps, and semi-automation of surgical tasks. Solutions that rely only on the laparoscopic video and do not require additional senso

Shangzhi Chen, Evan S. H. Kang, Mina S. Chaharsoughi, Vallery Stanishev

Metal nanostructures are key elements in nanooptics owing to their strong resonant interaction with light through local plasmonic charge oscillations. Their ability to shape light at the nanoscale have made them important across a multitude of areas, including biosensing, energy conversion and ultrathin flat metaoptics. Yet another dimension of avenues is fo

Heinke Hihn, Sebastian Gottwald, Daniel A. Braun

Information-theoretic bounded rationality describes utility-optimizing decision-makers whose limited information-processing capabilities are formalized by information constraints. One of the consequences of bounded rationality is that resource-limited decision-makers can join together to solve decision-making problems that are beyond the capabilities of each

A. C. Souza-Feliciano, M. De Prá, N. Pinilla-Alonso, A. Alvarez-Candal

Jupiter Trojan asteroids are minor bodies that share Jupiter's orbit around the Sun. Although not yet well understood in origin and composition, they have surface properties that, besides being comparable with other populations of small bodies in the Solar System, hold information that may restrict models of planetary formation. Due their importance, there h

Andrea Papenmeier, Gwenn Englebienne, Christin Seifert

Machine learning systems have become popular in fields such as marketing, financing, or data mining. While they are highly accurate, complex machine learning systems pose challenges for engineers and users. Their inherent complexity makes it impossible to easily judge their fairness and the correctness of statistically learned relations between variables and

Chuan Chen, A. H. Castro Neto, Vitor M. Pereira

We explore in detail the electronic phases of a system consisting of three non-colinear arrays of coupled quantum wires, each rotated 120 degrees with respect to the next. A perturbative renormalization-group analysis reveals that multiple correlated states can be stabilized: a $s$-wave or $d \pm id$ superconductor, a charge density wave insulator, a two-dim

Nicolas Boizot, Ludovic Sacchelli

We propose an approach to the problem of global reconstruction of an orientation field. The method is based on a geometric model called "bisector line fields", which maps a pair of vector fields to an orientation field, effectively generalizing the notion of doubling phase vector fields. Endowed with a well chosen energy minimization problem, we provide a po

Hrachya Khachatryan

We consider the $\mathbb{C}\mathbb{P}^{(N_f-1)}$ Non-Linear-Sigma-Model in the dimension $4<d<6$. The critical behaviour of this model in the large $N_f$ limit is reviewed. We propose a Higher Derivative Gauge (HDG) theory as an ultraviolet completion of the $\mathbb{C}\mathbb{P}^{(N_f-1)}$ NLSM. Tuning mass operators to zero, the HDG in the IR limit reaches

Mark Livingston, Francesca Pannullo, Adrian Bowman, Marian Scott

Reviews of official statistics for UK housing have noted that developments have not kept pace with real-world change, particularly the rapid growth of private renting. This paper examines the potential value of big data in this context. We report on the construction of a dataset from the on-line adverts of one national lettings agency, describing the content

Andrea Geraldi, Alessandro Laneve, Luis Diego Bonavena, Linda Sansoni

Many disordered systems show a superdiffusive dynamics, intermediate between the diffusive one, typical of a classical stochastic process, and the so called ballistic behaviour, which is generally expected for the spreading in a quantum process. We have experimentally investigated the superdiffusive behaviour of a quantum walk (QW), whose dynamics can be rel

Pierre Chevalier, Bartlomiej Kaminski, Fraser Hutchison, Qi Ma

In this paper we present an open source, fully asynchronous, leaderless algorithm for reaching consensus in the presence of Byzantine faults in an asynchronous network. We prove the algorithm's correctness provided that less than a third of participating nodes are faulty. We also present a way of applying the algorithm to a network with dynamic membership, i

Mateusz Kwaśnicki

We identify a class of non-local integro-differential operators $K$ in $\mathbb{R}$ with Dirichlet-to-Neumann maps in the half-plane $\mathbb{R} \times (0, \infty)$ for appropriate elliptic operators $L$. More precisely, we prove a bijective correspondence between L\'evy operators $K$ with non-local kernels of the form $\nu(y - x)$, where $\nu(x)$ and $\nu(-

K. K. Singh, P. J. Meintjes, N. Bhatt, B. van Soelen

Extremely High Synchrotron Peak (EHSP) blazars are observed to form a small population of sources with high energy hump peaking at TeV energies in their broad-band spectral energy distributions. The observed gamma-ray emission from these sources at GeV-TeV energies is described by unusual hard spectral indices. The observed spectral and temporal characterist

Franz Lehner, Kamil Szpojankowski

We study subordination of free convolutions. We prove that for free random variables $X,Y$ and a Borel function $f$ the conditional expectation $E_\varphi\left[ (z-X-f(X)Yf^*(X))^{-1}| X\right]$, is a resolvent again. This result allows explicit calculation of the distribution of $X+f(X)Yf^*(X)$. The main tool is a formula for conditional expectations in ter

Bumsig Kim, Alexander Polishchuk

We define the Atiyah class for global matrix factorizations and use it to give a formula for the categorical Chern character and the boundary-bulk map for matrix factorizations, generalizing the formula in the local case obtained in arXiv:1002.2116. Our approach is based on developing the Lie algebra analogies observed by Kapranov alg-geom/9704009 and Markar

Junhyuk Hyun, Hongje Seong, Euntai Kim

Pooling is one of the main elements in convolutional neural networks. The pooling reduces the size of the feature map, enabling training and testing with a limited amount of computation. This paper proposes a new pooling method named universal pooling. Unlike the existing pooling methods such as average pooling, max pooling, and stride pooling with fixed poo

Olivier Adjoua, Stéphanie Pitre-Champagnat, Didier Lucor

We propose a hemodynamic reduced-order model bridging macroscopic and meso-scopic blood flow circulation scales from arteries to capillaries. In silico tree like vascular geometries, mathematically described by graphs, are synthetically generated by means of stochastic growth algorithms constrained by statistical morphological and topological principles. Sca

Mo Deng, Shuai Li, Alexandre Goy, Iksung Kang

The quality of inverse problem solutions obtained through deep learning [Barbastathis et al, 2019] is limited by the nature of the priors learned from examples presented during the training phase. In the case of quantitative phase retrieval [Sinha et al, 2017, Goy et al, 2019], in particular, spatial frequencies that are underrepresented in the training data

Yacine Chitour, Swann Marx, Christophe Prieur

This paper is concerned with the asymptotic stability analysis of a one dimensional wave equation with Dirichlet boundary conditions subject to a nonlinear distributed damping with an L p functional framework, p $\in$ [2, $\infty$]. Some well-posedness results are provided together with exponential decay to zero of trajectories, with an estimation of the dec

Max Eichler, Gözde Gül Şahin, Iryna Gurevych

We present LINSPECTOR WEB, an open source multilingual inspector to analyze word representations. Our system provides researchers working in low-resource settings with an easily accessible web based probing tool to gain quick insights into their word embeddings especially outside of the English language. To do this we employ 16 simple linguistic probing task

Ruben Zakine, Jean-Baptiste Fournier, Frédéric van Wijland

We consider a system of independent point-like particles performing a Brownian motion while interacting with a Gaussian fluctuating background. These particles are in addition endowed with a discrete two-state internal degree of freedom that is subjected to a nonequilibrium source of noise, which affects their coupling with the background field. We explore t

Sebastian P. Kleinschmidt, Bernardo Wagner

Under difficult environmental conditions, the view of RGB cameras may be restricted by fog, dust or difficult lighting situations. Because thermal cameras visualize thermal radiation, they are not subject to the same limitations as RGB cameras. However, because RGB and thermal imaging differ significantly in appearance, common, state-of-the-art feature descr

Remy Cazabet, Giulio Rossetti

Community discovery is one of the most studied problems in network science. In recent years, many works have focused on discovering communities in temporal networks, thus identifying dynamic communities. Interestingly, dynamic communities are not mere sequences of static ones; new challenges arise from their dynamic nature. In this chapter, we will discuss s

Łukasz Płociniczak, Mateusz Świtała

We are concerned with the asymptotics and perturbation analysis of a singular second-order nonlinear ODE that models capillary rise of a fluid inside a narrow vertical tube. We prove the convergence of the exact solution to a unperturbed solution when a nondimensional parameter decrease to zero. Furthermore, we provide an accurate method of approximating the

Cai-Xia Zhang, Shi-Guo Peng, Kaijun Jiang

We present a comprehensive derivation of a set of universal relations for spin-orbit-coupled Fermi gases in three or two dimension, which follow from the short-range behavior of the two-body physics. Besides the adiabatic energy relations, the large-momentum distribution, the grand canonical potential and pressure relation derived in our previous work for th

Kumara Kahatapitiya, Ranga Rodrigo

Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance in many computer vision tasks over the years. However, this comes at the cost of heavy computation and memory intensive network designs, suggesting potential improvements in efficiency. Convolutional layers of CNNs partly account for such an inefficiency, as they are known to lea

Grzegorz Wiktorowicz, Łukasz Wyrzykowski, Martyna Chruslinska, Jakub Klencki

In large and complicated stellar systems like galaxies it is difficult to predict the number and characteristics of a black hole population. Such populations may be modelled as an aggregation of homogeneous (i.e. having uniform star formation history and the same initial chemical composition) stellar populations. Using realistic evolutionary models we predic

Raghavendra S., Vanamali C. Shastry, Nilakanthan V. K., Vijaya Kumar K. B

The effect of Confined One Gluon Exchange Potential and Instanton Induced Interaction potential in the singlet ($^1S_0$) and triplet ($^3S_1$) channels for Nucleon-Nucleon interaction has been investigated in the framework of Relativistic Harmonic Model using Resonating Group Method in the adiabatic limit with Born - Oppenheimer approximation. The contributi

Marthe Bonamy, Pierre Charbit, Oscar Defrain, Gwenaël Joret

We give a short proof of the following theorem due to Jon H. Folkman (1969): The chromatic number of any graph is at most $2$ plus the maximum over all subgraphs of the difference between half the number of vertices and the independence number.

Yueke Hu, Jie Shu, Hongbo Yin

In this paper we discuss Waldspurger's local period integral for newforms in new cases. The main ingredient is the work \cite{HN18} on Waldspurger's period integral using the minimal vectors, and the explicit relation between the newforms and the minimal vectors. We use a representation theoretical trick to simplify computations for newforms. As an example,

Ngo Viet Trung

These notes are an introduction to some basic aspects of the Castelnuovo-Mumford regularity and related topics such as weak regularity, a*-invariant and partial regularities.

Luke Jew, Richard Grumitt

We present an estimate of the polarized spectral index between the Planck 30 and 44 GHz surveys in $3.7^\circ$ pixels across the entire sky. We use an objective reference prior that maximises the impact of the data on the posterior and multiply this by a maximum entropy prior that includes information from observations in total intensity by assuming a polari

Enzo De Sena, Zoran Cvetkovic, Huseyin Hacihabiboglu, Marc Moonen

This article studies the effects of inter-channel time and level differences in stereophonic reproduction on perceived localization uncertainty, which is defined as how difficult it is for a listener to tell where a sound source is located. Towards this end, a computational model of localization uncertainty is proposed first. The model calculates inter-aural

David M. Kreps, Walter Schachermayer

We examine Kreps' (2019) conjecture that optimal expected utility in the classic Black--Scholes--Merton (BSM) economy is the limit of optimal expected utility for a sequence of discrete-time economies that "approach" the BSM economy in a natural sense: The $n$th discrete-time economy is generated by a scaled $n$-step random walk, based on an unscaled random

R Parthasarathy

In this invited talk, I discuss four important contributions of E.C.G. Sudarshan, among many. They are the V-A theory of weak interaction, Sudarshan - Glauber representation, tachyons and the quantum zeno effect.

S. Hamidreza Kasaei

Service robots are expected to operate effectively in human-centric environments for long periods of time. In such realistic scenarios, fine-grained object categorization is as important as basic-level object categorization. We tackle this problem by proposing an open-ended object recognition approach which concurrently learns both the object categories and

Michael Elkin, Yuval Gitlitz, Ofer Neiman

Let $G=(V,E,w)$ be a weighted undirected graph with $n$ vertices and $m$ edges, and fix a set of $s$ sources $S\subseteq V$. We study the problem of computing {\em almost shortest paths} (ASP) for all pairs in $S \times V$ in both classical centralized and parallel (PRAM) models of computation. Consider the regime of multiplicative approximation of $1+\epsil

Dong Liang, Jing Cheng, Ziwen Ke, Leslie Ying

Image reconstruction from undersampled k-space data has been playing an important role for fast MRI. Recently, deep learning has demonstrated tremendous success in various fields and also shown potential to significantly speed up MR reconstruction with reduced measurements. This article gives an overview of deep learning-based image reconstruction methods fo

Wolfgang Ebeling, Sabir M. Gusein-Zade

P. Berglund, T. H\"ubsch, and M. Henningson proposed a method to construct mirror symmetric Calabi-Yau manifolds. They considered a pair consisting of an invertible polynomial and of a finite (abelian) group of its diagonal symmetries together with a dual pair. A. Takahashi suggested a method to generalize this construction to symmetry groups generated by so

Houssam Abdul-Rahman, Christoph Fischbacher, Günter Stolz

We consider the XXZ spin chain, characterized by an anisotropy parameter $\Delta>1$, and normalized such that the ground state energy is $0$ and the ground state given by the all spins up state. The energies $E_K = K(1-1/\Delta)$, $K=1,2,\ldots$, can be interpreted as $K$-cluster break-up thresholds for down spin configurations. We show that, for every $K$,

Promod Sharma, M. K. Vemuri

Each irreducible representation of the affine group of a finite field has a unique maximal inductive algebra, and it is self adjoint.

Defa Zhu, Si Liu, Wentao Jiang, Chen Gao

The multi-domain image-to-image translation is a challenging task where the goal is to translate an image into multiple different domains. The target-only characteristics are desired for translated images, while the source-only characteristics should be erased. However, recent methods often suffer from retaining the characteristics of the source domain, whic

Alexander Mang, Moritz Weber

Compact quantum groups can be studied by investigating their co-representation categories in analogy to the Schur-Weyl/Tannaka-Krein approach. For the special class of (unitary) "easy" quantum groups these categories arise from a combinatorial structure: Rows of two-colored points form the objects, partitions of two such rows the morphisms; vertical/horizont