November 2018 arXiv papers — page 14

Andreas Banlaki, Abhishek Chowdhury, Abhiram Kidambi, Maria Schimpf

We show that a large number of $CY_3$ manifolds are involved in an intricate way in Mathieu moonshine viz. their Gromov--Witten invariants are related to the expansion coefficients of the twined/ twisted--twined elliptic genera of $K3$. We use the string duality between CHL orbifolds of heterotic string theory on $K3 \times T^2$ and type IIA string theory on

Eric Benhamou

In this paper, we revisit the Kalman filter theory. After giving the intuition on a simplified financial markets example, we revisit the maths underlying it. We then show that Kalman filter can be presented in a very different fashion using graphical models. This enables us to establish the connection between Kalman filter and Hidden Markov Models. We then l

Gabriel Hartmann, Zvi Shiller, Amos Azaria

Autonomous navigation has recently gained great interest in the field of reinforcement learning. However, little attention was given to the time optimal velocity control problem, i.e. controlling a vehicle such that it travels at the maximal speed without becoming dynamically unstable (roll-over or sliding). Time optimal velocity control can be solved numeri

Joakim Johnander, Martin Danelljan, Emil Brissman, Fahad Shahbaz Khan

One of the fundamental challenges in video object segmentation is to find an effective representation of the target and background appearance. The best performing approaches resort to extensive fine-tuning of a convolutional neural network for this purpose. Besides being prohibitively expensive, this strategy cannot be truly trained end-to-end since the onli

Yannick Sire, Christopher D. Sogge, Chengbo Wang

This paper is devoted to several small data existence results for semi-linear wave equations on negatively curved Riemannian manifolds. We provide a simple and geometric proof of small data global existence for any power $p\in (1, 1+\frac{4}{n-1}]$ for the shifted wave equation on hyperbolic space ${\mathbb H}^n$ involving nonlinearities of the form $\pm |u|

Philipp Henzler, Niloy Mitra, Tobias Ritschel

We introduce PlatonicGAN to discover the 3D structure of an object class from an unstructured collection of 2D images, i.e., where no relation between photos is known, except that they are showing instances of the same category. The key idea is to train a deep neural network to generate 3D shapes which, when rendered to images, are indistinguishable from gro

Tadhg M. Garton, Sophie A. Murray, Peter T. Gallagher

Coronal holes (CHs) are regions of open magnetic flux which are the source of high speed solar wind (HSSW) streams. To date, it is not clear which aspects of CHs are of most influence on the properties of the solar wind as it expands through the Heliosphere. Here, we study the relationship between CH properties extracted from AIA (Atmospheric Imaging Assembl

Victor Chernozhukov, Iván Fernández-Val, Siyi Luo

We develop a distribution regression model under endogenous sample selection. This model is a semi-parametric generalization of the Heckman selection model. It accommodates much richer effects of the covariates on outcome distribution and patterns of heterogeneity in the selection process, and allows for drastic departures from the Gaussian error structure,

Hendrik Ranocha

Explicit Runge-Kutta methods are classical and widespread techniques in the numerical solution of ordinary differential equations (ODEs). Considering partial differential equations, spatial semidiscretisations can be used to obtain systems of ODEs that are solved subsequently, resulting in fully discrete schemes. However, certain stability investigations of

L. Dello Schiavo

We construct a recurrent diffusion process with values in the space of probability measures over an arbitrary closed Riemannian manifold of dimension $d\ge 2$. The process is associated with the Dirichlet form defined by integration of the Wasserstein gradient w.r.t. the Dirichlet-Ferguson measure, and is the counterpart on multi-dimensional base spaces to t

Neil J. Y. Fan, Peter L. Guo

Buch and Rimányi proved a formula for specializations of double Grothendieck polynomials based on the Yang-Baxter equation related to the degenerate Hecke algebra. A geometric proof was found by Yong and Woo by constructing a Gröbner basis for the Kazhdan-Lusztig ideals. In this note, we give an elementary proof for this formula by using only divided differe

Wei Hu, Gusi Te, Ju He, Dong Chen

Face anti-spoofing plays a crucial role in protecting face recognition systems from various attacks. Previous model-based and deep learning approaches achieve satisfactory performance for 2D face spoofs, but remain limited for more advanced 3D attacks such as vivid masks. In this paper, we address 3D face anti-spoofing via the proposed Hypergraph Convolution

Shawulienu Kezilebieke, Rok Žitko, Marc Dvorak, Teemu Ojanen

We investigate the spectral evolution in different metal phthalocyanine molecules on NbSe$_2$ surface using scanning tunnelling microscopy (STM) as a function of the coupling with the substrate. For manganese phthalocyanine (MnPc), we demonstrate a smooth spectral crossover from Yu-Shiba-Rusinov (YSR) bound states to spin-flip excitations. This has not been

D. Russell Luke, Anna-Lena Martins

Motivated by nonconvex, inconsistent feasibility problems in imaging, the relaxed alternating averaged reflections algorithm, or relaxed Douglas-Rachford algorithm (DR$λ$), was first proposed over a decade ago. Convergence results for this algorithm are limited either to convex feasibility or consistent nonconvex feasibility with strong assumptions on the re

S. K. Roushon

We observe an inductive structure in a large class of Artin groups and exploit this information to deduce the Farrell-Jones isomorphism conjecture for several classes of Artin groups of finite real, complex and affine types.

Tanner Kaptanoglu, Meng Luo, Josh Klein

Linear alkyl benzene (LAB) has in recent years been used as a solvent for PPO in large-scale scintillation detectors, like Daya Bay and SNO+. The combination has several nice properties, including high light yield, good materials compatibility, and excellent pulse shape discrimination. As charged particles move through the LAB+PPO, both Cherenkov and scintil

Darsh Kodwani, David Alonso, Pedro Ferreira

Cosmological large-scale structure analyses based on two-point correlation functions often assume a Gaussian likelihood function with a fixed covariance matrix. We study the impact on cosmological parameter estimation of ignoring the parameter dependence of this covariance matrix, focusing on the particular case of joint weak-lensing and galaxy clustering an

Andres Sarrazola Alzate

Let us suppose that $\mathbb{Q}_p$ is the field of $p$-adic numbers and $\mathbb{G}$ is a split connected reductive group scheme over $\mathbb{Z}_p$. In this work we will introduce a sheaf of twisted arithmetic differential operators on the formal flag variety of $\mathbb{G}$, associated to a general character. We will generalize the arguments of C. Huyghe a

Przemysław Ohrysko, Maria Roginskaya

In this short note we first extend the validity of the spectral radius formula obtained in \cite{ag} to Fourier--Stieltjes algebras. The second part is devoted to showing that for the measure algebra on any locally compact non-discrete Abelian group there are no non-trivial constraints between three quantities: the norm, the spectral radius and the supremum

Xiling Zhang

This article presents a coupling approach for the approximation of iterated stochastic integrals of length three. The generation of such integrals is the central problem of higher-order pathwise approximations for SDEs, which still lacks a satisfactory answer due to the restriction of dimensionality and computational load. Here we start from the Fourier repr

Lucas Frérot, Marc Bonnet, Jean-François Molinari, Guillaume Anciaux

The contact of solids with rough surfaces plays a fundamental role in physical phenomena such as friction, wear, sealing, and thermal transfer. However, its simulation is a challenging problem due to surface asperities covering a wide range of length-scales. In addition, non-linear local processes, such as plasticity, are expected to occur even at the lighte

Fabio Deelan Cunden, Satya N. Majumdar, Neil O'Connell

The $α$-determinant is a one-parameter generalisation of the standard determinant, with $α=-1$ corresponding to the determinant, and $α=1$ corresponding to the permanent. In this paper a simple limit procedure to construct $α$-determinantal point processes out of fermionic processes is examined. The procedure is illustrated for a model of $N$ free fermions i

Ramandeep Gill, Jonathan Granot, Pawan Kumar

Despite being hard to measure, GRB prompt $γ$-ray emission polarization is a valuable probe of the dominant emission mechanism and the outflow's composition and angular structure. During the prompt emission the outflow is ultra-relativistic with Lorentz factors $Γ\gg1$. We describe in detail the linear polarization properties of various emission mechanis

Mauricio Caicedo, Ángel del Río

Hans Zassenhaus conjectured that every torsion unit of the integral group ring of a finite group $G$ is conjugate within the rational group algebra to an element of the form $\pm g$ with $g\in G$. This conjecture has been disproved recently for metabelian groups, by Eisele and Margolis. However it is known to be true for many classes of solvable groups, as f

Michael A. Alcorn, Qi Li, Zhitao Gong, Chengfei Wang

Despite excellent performance on stationary test sets, deep neural networks (DNNs) can fail to generalize to out-of-distribution (OoD) inputs, including natural, non-adversarial ones, which are common in real-world settings. In this paper, we present a framework for discovering DNN failures that harnesses 3D renderers and 3D models. That is, we estimate the

Étienne Jussiau, Masahiro Hasegawa, Robert S. Whitney

We study a quantum dot coupled to two semiconducting reservoirs, when the dot level and the electrochemical potential are both close to a band edge in the reservoirs. This is modelled with an exactly solvable Hamiltonian without interactions (the Fano-Anderson model). The model is known to show an abrupt transition as the dot-reservoir coupling is increased

P. M. Marychev, D. Yu. Vodolazov

Temperature induced transition of thin superconductor-ferromagnet-normal (S/F/N) metal hybrid structure to in-plane Fulde-Ferrel-Larkin-Ovchinnikov (FFLO) state is accompanied by vanishing of effective inverse magnetic field penetration depth $Λ^{-1}$ (Phys. Rev. Lett. 121, 077002 (2018)). Here we show that $Λ^{-1}$ goes to zero only in limit of zero magneti

Han Yu

In this paper we study the following set\[A=\{p(n)+2^nd \mod 1: n\geq 1\}\subset [0.1],\] where $p$ is a polynomial with at least one irrational coefficient on non constant terms, $d$ is any real number and for $a\in [0,\infty)$, $a \mod 1$ is the fractional part of $a$. By a Bernoulli decomposition method, we show that the closure of $A$ must have full Haus

Austin R. Benson, Jon Kleinberg

Data collection often involves the partial measurement of a larger system. A common example arises in collecting network data: we often obtain network datasets by recording all of the interactions among a small set of core nodes, so that we end up with a measurement of the network consisting of these core nodes along with a potentially much larger set of fri

Ronen Eldan

The analysis of various models in statistical physics relies on the existence of decompositions of measures into mixtures of product-like components, where the goal is to attain a decomposition into measures whose entropy is close to that of the original measure, yet with small correlations between coordinates. We prove a related general result: For every is

William Cottrell, Ben Freivogel, Diego M. Hofman, Sagar F. Lokhande

Given two copies of any quantum mechanical system, one may want to prepare them in the thermofield double state for the purpose of studying thermal physics or black holes. However, the thermofield double is a unique entangled pure state and may be difficult to prepare. We propose a local interacting Hamiltonian for the combined system whose ground state is a

Yukihide Tadano

We consider a long-range scattering theory for discrete Schrödinger operators on the hexagonal lattice, which describe tight-binding Hamiltonians on the graphene sheet. We construct Isozaki-Kitada modifiers for a pair of the difference Laplacian on the hexagonal lattice and perturbed operators with long-range potentials. We prove that these modified wave ope

Marcos Dajczer, Theodoros Vlachos

We present several local and global results on isometric immersions of Kaehler manifolds $M^{2n}$ into hyperbolic space $\Hy^{2n+p}$. For instance, a classification is given in the case of dimension $n\geq 4$ and codimension $p=2$. Moreover, as corollaries of general results, we conclude that there are no isometric immersion in codimension $p\leq n-2$ if the

Muhammed ElTahan, Mohammed Magooda

The sulfur pollutants are the source of a sizeable portion of the air pollution. In this work, the spatial distribution and temporal trend of the mass concentration of two of the critical sulfur pollutants, SO2 and SO4, in addition to the aerosol optical properties (AOD) were analyzed over the region of the Middle East and North Africa (MENA) from multiple s

Emel Altas, Bayram Tekin

Starting from a divergence-free rank-4 tensor of which the trace is the cosmological Einstein tensor, we give a construction of conserved charges in Einstein's gravity and its higher derivative extensions for asymptotically anti-de Sitter spacetimes. The current yielding the charge is explicitly gauge-invariant, and the charge expression involves the lin

Yuan Liu, Lin Ma, Yifeng Zhang, Wei Liu

Temporal action proposal generation is an important task, aiming to localize the video segments containing human actions in an untrimmed video. In this paper, we propose a multi-granularity generator (MGG) to perform the temporal action proposal from different granularity perspectives, relying on the video visual features equipped with the position embedding

Elena Tutubalina, Zulfat Miftahutdinov, Sergey Nikolenko, Valentin Malykh

In this work, we consider the medical concept normalization problem, i.e., the problem of mapping a disease mention in free-form text to a concept in a controlled vocabulary, usually to the standard thesaurus in the Unified Medical Language System (UMLS). This task is challenging since medical terminology is very different when coming from health care profes

Muhammad Rizwan, Muhammad Zubair Ali, Ali Övgün

In this paper, we study the tunneling of charged fermions from the stationary axially symmetric black holes using the generalized uncertainty principle (GUP) via Wentzel, Kramers, and Brillouin (WKB) method. The emission rate of the charged fermions and corresponding modified Hawking temperature of Ker-Newman black hole, Einstein-Maxwell-Dilaton-Axion (EMDA)

Bo Shen, Wei Zhang, Haiyan Zhao, Zhi Jin

The pictorial jigsaw (PJ) puzzle is a well-known leisure game for humans. Usually, a PJ puzzle game is played by one or several human players face-to-face in the physical space. In this paper, we focus on how to solve PJ puzzles in the cyberspace by a group of physically distributed human players. We propose an approach to solving PJ puzzle by stigmergy-insp

Janusz Dybizbański, Andrzej Szepietowski

We consider hypercubes with pairwise disjoint faulty edges. An $n$-dimensional hypercube $Q_n$ is an undirected graph with $2^n$ nodes, each labeled with a distinct binary strings of length $n$. The parity of the vertex is 0 if the number of ones in its labels is even, and is 1 if the number of ones is odd. Two vertices $a$ and $b$ are connected by the edge

Bernhard Bodmann, Emily J. King

We consider sets of trace-normalized non-negative operators in Hilbert-Schmidt balls that maximize their mutual Hilbert-Schmidt distance; these are optimal arrangements in the sets of purity-limited classical or quantum states on a finite-dimensional Hilbert space. Classical states are understood to be represented by diagonal matrices, with the diagonal entr

Matias D. Cattaneo, Michael Jansson, Xinwei Ma

This paper introduces an intuitive and easy-to-implement nonparametric density estimator based on local polynomial techniques. The estimator is fully boundary adaptive and automatic, but does not require pre-binning or any other transformation of the data. We study the main asymptotic properties of the estimator, and use these results to provide principled e

Benoît Commerçon, Alexandre Marcowith, Yohan Dubois

Cosmic rays (CR) propagate through the galactic scales down to the smaller scales at which stars form. CRs are close to energy equipartition with the other components of the interstellar medium and can provide a support against gravity if pressure gradients develop. We study CRs propagation within a turbulent and magnetised bi-stable interstellar gas and ide

Cornel Marius Murea, Dan Tiba

We consider general shape optimization problems governed by Dirichlet boundary value problems. The proposed approach may be extended to other boundary conditions as well. It is based on a recent representation result for implicitly defined manifolds, due to the authors, and it is formulated as an optimal control problem. The discretized approximating problem

Claudio Michaelis, Ivan Ustyuzhaninov, Matthias Bethge, Alexander S. Ecker

We tackle the problem of one-shot instance segmentation: Given an example image of a novel, previously unknown object category, find and segment all objects of this category within a complex scene. To address this challenging new task, we propose Siamese Mask R-CNN. It extends Mask R-CNN by a Siamese backbone encoding both reference image and scene, allowing

Bohui Chen, Cheng-Yong Du, Tiyao Li

In this paper, motivated by Chen--Ruan's stringy orbifold theory on almost complex orbifolds, we construct a new cohomology ring $\mathscr H^\ast_{G,cs}(X)$ for an equivariant almost complex pair $(X,G)$, where $X$ is a compact connected almost complex manifold, $G$ is a connected compact Lie group which acts on $X$ and preserves the almost complex struc

Paula Castro, Juan Carlos De los Reyes

In this paper we propose a bilevel optimization approach for the placement of space and time observations in variational data assimilation problems. Within the framework of supervised learning, we consider a bilevel problem where the lower-level task is the variational reconstruction of the initial condition of a semilinear system, and the upper-level proble

Chun-Xiao Liu, Jay D. Sau, Tudor D. Stanescu, S. Das Sarma

In a recent high-quality experimental work on normal metal--superconducting nanowire junctions arXiv:1807.01940 (2018), strong anisotropic suppression of induced superconductivity has been observed in tunnel conductance measurements in the presence of applied magnetic field with variable orientation. Following this finding, we investigate theoretically the d

Vishwanath Shukla, Bérengère Dubrulle, Sergey Nazarenko, Giorgio Krstulovic

We present a comprehensive study of the statistical features of a three-dimensional time-reversible Navier-Stokes (RNS) system, wherein the standard viscosity $ν$ is replaced by a fluctuating thermostat that dynamically compensates for fluctuations in the total energy. We analyze the statistical features of the RNS steady states in terms of a non-negative di

Rafael Bailo, Jose A. Carrillo, Jingwei Hu

We propose fully discrete, implicit-in-time finite-volume schemes for a general family of non-linear and non-local Fokker-Planck equations with a gradient-flow structure, usually known as aggregation-diffusion equations, in any dimension. The schemes enjoy the positivity-preservation and energy-dissipation properties, essential for their practical use. The f

Huijie Zheng, Jingyan Xu, Geoffrey Iwata, Till Lenz

Ensembles of nitrogen-vacancy (NV) centers in diamonds are widely utilized for magnetometry, magnetic-field imaging and magnetic-resonance detection. They have not been used for magnetometry at zero ambient field because Zeeman sublevels lose first-order sensitivity to magnetic fields as they are mixed due to crystal strain or electric fields. In this work,

Zhen Li, Chao Luo, Tengteng Lu, Jun Xu

Cryogenic characterization and modeling of 0.18um CMOS technology (1.8V and 5V) are presented in this paper. Several PMOS and NMOS transistors with different width to length ratios(W/L) were extensively characterized under various bias conditions at temperatures ranging from 300K down to 4.2K. We extracted their fundamental physical parameters and developed

G. P. Lamb, J. D. Lyman, A. J. Levan, N. R. Tanvir

We present observations of the optical afterglow of GRB\,170817A, made by the {\it Hubble Space Telescope}, between February and August 2018, up to one year after the neutron star merger, GW170817. The afterglow shows a rapid decline beyond $170$~days, and confirms the jet origin for the observed outflow, in contrast to more slowly declining expectations for

Giao Ky Duong, Hatem Zaag

In this paper, we are interested in the mathematical model of MEMS devices which is presented by the following equation on $(0,T) \times Ω:$ \begin{eqnarray*} \partial_t u = Δu +\displaystyle \frac{λ}{ (1-u)^2 \left( 1 +\displaystyle γ\int_Ω \frac{1}{1-u} dx \right)^2}, \quad 0 \leq u <1, \end{eqnarray*} where $Ω$ is a bounded domain in $\mathbb{R}^n$ and $λ

Eunjeong Jeong, Seungeun Oh, Hyesung Kim, Jihong Park

On-device machine learning (ML) enables the training process to exploit a massive amount of user-generated private data samples. To enjoy this benefit, inter-device communication overhead should be minimized. With this end, we propose federated distillation (FD), a distributed model training algorithm whose communication payload size is much smaller than a b

Timon Elmer, Krishna Chaitanya, Prateek Purwar, Christoph Stadtfeld

Face-to-face interactions are important for a variety of individual behaviors and outcomes. In recent years a number of human sensor technologies have been proposed to incorporate direct observations in behavioral studies of face-to-face interactions. One of the most promising emerging technologies are active Radio Frequency Identification (RFID) badges. The

Naoyuki Yonemaru, Keitaro Takahashi, Hiroki Kumamoto, Shi Dai

Pulsar search with time-domain observation is very computationally expensive and data volume will be enormous with the next generation telescopes such as the Square Kilometre Array. We apply artificial neural networks (ANNs), a machine learning method, for efficient selection of pulsar candidates from radio continuum surveys, which are much cheaper than time

Jakub Prüher, Toni Karvonen, Chris J. Oates, Ondřej Straka

The sigma-point filters, such as the UKF, which exploit numerical quadrature to obtain an additional order of accuracy in the moment transformation step, are popular alternatives to the ubiquitous EKF. The classical quadrature rules used in the sigma-point filters are motivated via polynomial approximation of the integrand, however in the applied context the

Guobin Mou, Dongze Sun, Fuguo Xie

There are two spectacular structures in our Milky Way: the {\it Fermi} bubbles in gamma-ray observations and the North Polar Spur (NPS) structure in X-ray observations. Because of their morphological similarities, they may share the same origin, i.e., related to the past activity of Galactic center (GC). Besides, those structures show significant bending fea

M. Reza Mohammadi Mozaffar, Ali Mollabashi

We study propagation of entanglement after a mass quench in free scalar Lifshitz theories. We show that entanglement entropy goes across three distinct growth regimes before relaxing to a generalized Gibbs ensemble, namely &#39;initial rapid growth&#39;, &#39;main linear growth&#39; and &#39;tortoise saturation&#39;. We show that although a wide spectrum of

Joakim Beck, Ben Mansour Dia, Luis F. R. Espath, Raul Tempone

An optimal experimental set-up maximizes the value of data for statistical inferences and predictions. The efficiency of strategies for finding optimal experimental set-ups is particularly important for experiments that are time-consuming or expensive to perform. For instance, in the situation when the experiments are modeled by Partial Differential Equation

Amina Fellan, Christian Schellenberger, Marc Zimmermann, Hans D. Schotten

Within the context of Industry 4.0, mobile robot systems such as automated guided vehicles (AGVs) and unmanned aerial vehicles (UAVs) are one of the major areas challenging current communication and localization technologies. Due to stringent requirements on latency and reliability, several of the existing solutions are not capable of meeting the performance

Laszlo M. Feher, Richard Rimanyi, Andrzej Weber

Consider a complex algebraic group $G$ acting on a smooth variety $M$ with finitely many orbits, and let $Ω$ be an orbit. The following three invariants of $Ω\subset M$ can be characterized axiomatically: (1) the equivariant fundamental class $[\overlineΩ, M]\in H^*_G(M)$, (2) the equivariant Chern-Schwartz-MacPherson class $c(Ω, M)\in H^*_G(M)$, and (3) the

Fearghal O&#39;Donncha, Yushan Zhang, Bei Chen, Scott c. James

This study investigated an approach to improve the accuracy of computationally lightweight surrogate models by updating forecasts based on historical accuracy relative to sparse observation data. Using a lightweight, ocean-wave forecasting model, we created a large number of model ensembles, with perturbed inputs, for a two-year study period. Forecasts were

Luca Cosmo, Mikhail Panine, Arianna Rampini, Maks Ovsjanikov

The question whether one can recover the shape of a geometric object from its Laplacian spectrum (&#39;hear the shape of the drum&#39;) is a classical problem in spectral geometry with a broad range of implications and applications. While theoretically the answer to this question is negative (there exist examples of iso-spectral but non-isometric manifolds),

Yanis Amirou

We study a characteristic subgroup of finitely generated groups, consisting of elements with uniform upper bound for word-lengths. For a group $G$, we denote this subgroup by $G_{bound}$. We give sufficient criteria for triviality and finiteness of $G_{bound}$. We prove that if $G$ is virtually abelian then $G_{bound}$ is finite. In contrast with numerous ex

Prabal Banerjee, Sushmita Ruj

Data is of unprecedented importance today. The most valuable companies of today treat data as a commodity, which they trade and earn revenues. To facilitate such trading, data marketplaces have emerged. Present data marketplaces are inadequate as they fail to satisfy all the desirable properties - fairness, efficiency, security, privacy and adherence to regu

Artur Grigorev, Artem Sevastopolsky, Alexander Vakhitov, Victor Lempitsky

We present a new deep learning approach to pose-guided resynthesis of human photographs. At the heart of the new approach is the estimation of the complete body surface texture based on a single photograph. Since the input photograph always observes only a part of the surface, we suggest a new inpainting method that completes the texture of the human body. R

Dietmar Silke Klemm, Lucrezia Ravera

Manifolds endowed with torsion and nonmetricity are interesting both from the physical and the mathematical points of view. In this paper, we generalize some results presented in the literature. We study Einstein manifolds (i.e., manifolds whose symmetrized Ricci tensor is proportional to the metric) in d dimensions with nonvanishing torsion that has both a

Divam Gupta, Tanmoy Chakraborty, Soumen Chakrabarti

In several natural language tasks, labeled sequences are available in separate domains (say, languages), but the goal is to label sequences with mixed domain (such as code-switched text). Or, we may have available models for labeling whole passages (say, with sentiments), which we would like to exploit toward better position-specific label inference (say, ta

Nir Zarrabi, Shai Avidan, Yael Moses

We consider the problem of segmenting dynamic regions in CrowdCam images, where a dynamic region is the projection of a moving 3D object on the image plane. Quite often, these regions are the most interesting parts of an image. CrowdCam images is a set of images of the same dynamic event, captured by a group of non-collaborating users. Almost every event of

Bai Xue, Naijun Zhan

In this paper we study the robust invariant sets generation problem for discrete-time switched polynomial systems subject to disturbance inputs within the optimal control framework. A robust invariant set of interest is a set of states such that every possible trajectory starting from it never leaves a specified safe set, regardless of actual disturbances. T

Weijing Li

In this paper we formulate a kind of new geometric measure of quantum correlations. This new measure is in terms of the quantum Tsallis relative entropy and can be viewed as a one-parameter extension quantum discordlike measure that satisfies all requirements of a good measure of quantum correlations. It is of an elegant analytic expression and contains seve

S. Amrith, J. M. Butterworth, F. F. Deppisch, W. Liu

The large and growing library of measurements from the Large Hadron Collider has significant power to constrain extensions of the Standard Model. We consider such constraints on a well-motivated model involving a gauged and spontaneously-broken $B-L$ symmetry, within the Contur framework. The model contains an extra Higgs boson, a gauge boson, and right-hand

Daria Satco, Ahmad R. T. Nugraha, M. Shoufie Ukhtary, Daria Kopylova

We theoretically investigate intersubband plasmon excitations in doped single wall carbon nanotubes (SWNTs) by examining the dependence of plasmon frequency on the nanotube diameter, chirality, and Fermi energy. The intersubband plasmons can be excited by light with polarization perpendicular to the nanotube axis and thus the plasmon excitations corresponds

I. Basile, J. Mourad, A. Sagnotti

We study the perturbative stability of four settings that arise in String Theory, when dilaton potentials accompany the breaking of Supersymmetry, in the USp(32) and U(32) orientifold models, and also in the heterotic SO(16)xSO(16) model. The first two settings are a family of AdS3xS7 orientifold vacua and a family of AdS7xS3 heterotic vacua, supported by fo

Chethan N Gowdigere, Jagannath Santara, Sumedha

We study the tricritical Ising universality class using conformal bootstrap techniques. By studying bootstrap constraints originating from multiple correlators on the CFT data of multiple OPEs, we are able to determine the scaling dimension of the spin field $Δ_σ$ in various non-integer dimensions $2 \le d \le 3$. $Δ_σ$ is connected to the critical exponent

Sujoy Paul, Jeroen van Baar

Deep Reinforcement Learning has shown tremendous success in solving several games and tasks in robotics. However, unlike humans, it generally requires a lot of training instances. Trajectories imitating to solve the task at hand can help to increase sample-efficiency of deep RL methods. In this paper, we present a simple approach to use such trajectories, ap

M. Baak, R. Koopman, H. Snoek, S. Klous

A prescription is presented for a new and practical correlation coefficient, $ϕ_K$, based on several refinements to Pearson&#39;s hypothesis test of independence of two variables. The combined features of $ϕ_K$ form an advantage over existing coefficients. First, it works consistently between categorical, ordinal and interval variables. Second, it captures n

Peng-Lu Zhao, An-Min Wang

We investigate the mutual influence of tilt, disorder, and Coulomb interaction in a type-I Dirac semimetal (DSM) with $x$-direction tilt by performing a renormalization group analysis. The interplay between disorder and ordinary tilt generates an effective tilt along the $x$-direction, which is the physically observable one. There exist two types of disorder

Sang-Ki Ko, Chang Jo Kim, Hyedong Jung, Choongsang Cho

We propose a sign language translation system based on human keypoint estimation. It is well-known that many problems in the field of computer vision require a massive amount of dataset to train deep neural network models. The situation is even worse when it comes to the sign language translation problem as it is far more difficult to collect high-quality tr

Sachin Mehta, Mohammad Rastegari, Linda Shapiro, Hannaneh Hajishirzi

We introduce a light-weight, power efficient, and general purpose convolutional neural network, ESPNetv2, for modeling visual and sequential data. Our network uses group point-wise and depth-wise dilated separable convolutions to learn representations from a large effective receptive field with fewer FLOPs and parameters. The performance of our network is ev

Mohammad Naseri Tehrani, Shahrokh Farahmand

Recently, non-orthogonal codes have been advocated for IoT massive access. Activity detection has been demonstrated to entail common support recovery in a jointly sparse multiple measurement vector (MMV) problem and MMV algorithms have been successfully applied offering various degrees of complexity-performance trade-off. Targeting the small measurement per

Ragunathan Mariappan, Vaibhav Rajan

Learning by integrating multiple heterogeneous data sources is a common requirement in many tasks. Collective Matrix Factorization (CMF) is a technique to learn shared latent representations from arbitrary collections of matrices. It can be used to simultaneously complete one or more matrices, for predicting the unknown entries. Classical CMF methods assume

Antônio H. Ribeiro, Manoel Horta Ribeiro, Gabriela Paixão, Derick Oliveira

We present a model for predicting electrocardiogram (ECG) abnormalities in short-duration 12-lead ECG signals which outperformed medical doctors on the 4th year of their cardiology residency. Such exams can provide a full evaluation of heart activity and have not been studied in previous end-to-end machine learning papers. Using the database of a large teleh

Emilie Kaufmann, Wouter Koolen

This paper presents new deviation inequalities that are valid uniformly in time under adaptive sampling in a multi-armed bandit model. The deviations are measured using the Kullback-Leibler divergence in a given one-dimensional exponential family, and may take into account several arms at a time. They are obtained by constructing for each arm a mixture marti

Manoj Kumar Singh, Lakhwinder Singh, Mehmet Agartioglu, Vivek Sharma

We report results from searches of pseudoscalar and vector bosonic super-weakly interacting massive particles (super-WIMP) in the TEXONO experiment at the Kuo-Sheng Nuclear Power Station, using 314.15 kg days of data from $n$-type Point-Contact Germanium detector. The super-WIMPs are absorbed and deposit total energy in the detector, such that the experiment

Ola Amara-Omari, Mary Schaps

We show that a vertex in the reduced crystal is i-external for a residue i if the defect is less than the absolute value of the i-component of the hub. We demonstrate the existence of a bound on the degree after which all vertices of a given defect d are external in at least one i-string. Combining this with the Chuang-Rouquier categorification for the simpl

Dinesh Pandey, Kamal Lochan Patra

For a graph $G,$ we denote the number of connected subgraphs of $G$ by $F(G)$. For a tree $T$, $F(T)$ has been studied extensively and it has been observed that $F(T)$ has a reverse correlation with Wiener index of $T$. Based on that, we call $F(G),$ the core index of $G$. In this paper, we characterize the graphs which extremize the core index among all gra

Kui Hou, Jizi Lin, Chengjie Zhu, Yaping Yang

Manipulating photons is an essential technique in quantum communication and computation. Combining the Raman electromagnetically induced transparency technology, we show that the photon blockade behavior can be actively controlled by using an external control field in a two atoms cavity-QED system. As a result, a versatile photon gateway can be achieved in t

James A. D. Diacoumis, Yvonne. Y. Y. Wong

We explore the issue of prior dependence in the context of one-sided constraints on the dark matter-photon and dark matter-neutrino elastic scattering cross-sections derived from cosmic microwave background (CMB) anisotropies measurements. Testing in particular the linear flat, Jeffreys, and logarithmic flat priors, we find that the former two yield upper li

Pascal Baseilhac, Satoshi Tsujimoto, Luc Vinet, Alexei Zhedanov

The Heun-Askey-Wilson algebra is introduced through generators $\{\boX,\boW\}$ and relations. These relations can be understood as an extension of the usual Askey-Wilson ones. A central element is given, and a canonical form of the Heun-Askey-Wilson algebra is presented. A homomorphism from the Heun-Askey-Wilson algebra to the Askey-Wilson one is identified.

Kathleen Campbell Garwood, Ph. D., Arpit Arun Dhobale

When considering answering important questions with data, unsupervised data offers extensive insight opportunity and unique challenges. This study considers student survey data with a specific goal of clustering students into like groups with underlying concept of identifying different poverty levels. Fuzzy logic is considered during the data cleaning and or

Jizi Lin, Kui Hou, Chengjie Zhu, Yaping Yang

We present a study of manipulating the multiphoton blockade phenomenon in a single mode cavity with two ladder-type three-level atoms. Combining the cavity QED with electromagnetically induced transparency technique, we show that it is possible to actively manipulate the photon blockade when two atoms are in phase radiations. As a result, the two-photon bloc

Siddique Latif, Rajib Rana, Junaid Qadir

Deep learning has undoubtedly offered tremendous improvements in the performance of state-of-the-art speech emotion recognition (SER) systems. However, recent research on adversarial examples poses enormous challenges on the robustness of SER systems by showing the susceptibility of deep neural networks to adversarial examples as they rely only on small and

Dianbo Liu, Timothy Miller, Raheel Sayeed, Kenneth D. Mandl

Electronic health record (EHR) data is collected by individual institutions and often stored across locations in silos. Getting access to these data is difficult and slow due to security, privacy, regulatory, and operational issues. We show, using ICU data from 58 different hospitals, that machine learning models to predict patient mortality can be trained e

Cindy Tsang

Let $L/K$ be a finite Galois extension whose Galois group $G$ is non-abelian and characteristically simple. Using tools from graph theory, we shall give a closed formula for the number of Hopf-Galois structures on $L/K$ with associated group isomorphic to $G$.

Li Ding, Chen Feng

We propose DeepMapping, a novel registration framework using deep neural networks (DNNs) as auxiliary functions to align multiple point clouds from scratch to a globally consistent frame. We use DNNs to model the highly non-convex mapping process that traditionally involves hand-crafted data association, sensor pose initialization, and global refinement. Our

Ippei Nagamachi

Consider a morphism between connected locally Noetherian normal schemes. In this paper, we discuss when the sequence of the etale fundamental groups associated to the morphism is exact. Moreover, we give a characterization of when the kernel of the induced homomorphism between their fundamental groups is topologically finitely generated, for the morphism fro

Baoyi Chen

This work studies the thermal production of $J/ψ$ and $ψ(2S)$ with Boltzmann transport model in the Quark Gluon Plasma (QGP) produced in $\sqrt{s_{NN}}=5.02$ TeV Pb-Pb collisions. $J/ψ$ nuclear modification factors are studied in details with the mechanisms of primordial production and the recombination of charm and anti-charm quarks in the thermal medium. $