January 2022 arXiv papers — page 9

Hossein Hassani

Tagged corpora play a crucial role in a wide range of Natural Language Processing. The Part of Speech Tagging (POST) is essential in developing tagged corpora. It is time-and-effort-consuming and costly, and therefore, it could be more affordable if it is automated. The Kurdish language currently lacks publicly available tagged corpora of proper sizes. Taggi

Boyi Jiang, Yang Hong, Hujun Bao, Juyong Zhang

We propose SelfRecon, a clothed human body reconstruction method that combines implicit and explicit representations to recover space-time coherent geometries from a monocular self-rotating human video. Explicit methods require a predefined template mesh for a given sequence, while the template is hard to acquire for a specific subject. Meanwhile, the fixed

Serena Dipierro, Aleksandr Dzhugan, Enrico Valdinoci

We introduce a suitable notion of integral operators (comprising the fractional Laplacian as a particular case) acting on functions with minimal requirements at infinity. For these functions, the classical definition would lead to divergent expressions, thus we replace it with an appropriate framework obtained by a cut-off procedure. The notion obtained in t

Bin Sheng, Gregory Gutin

We introduce a novel approach of using important cuts which allowed us to design significantly faster fixed-parameter tractable (FPT) algorithms for the following routing problems: the Mixed Chinese Postman Problem parameterized by the number of directed edges (Gutin et al., JCSS 2017), the Minimum Shared Edges problem (MSE) parameterized by the number p of

Alexander Libanov, Andrey Sharofeev

The diffuse supernova neutrino background (DSNB) is a powerful future tool to constrain core-collapse explosion mechanisms without observation of a nearby event, and the corresponding signal has been calculated for a variety of collapse models. For Supernova (SN) 1987A, a peculiar double neutrino burst was detected, but models for the double collapse have ne

Waqas Ahmed, Athanasios Karozas, George K. Leontaris, Umer Zubair

We realize smooth hybrid inflation in the framework of supersymmetric $SU(5) \times U(1)_{\chi}\subset SO(10)$ model which provides a natural solution to the monopole problem appearing in the spontaneous symmetry breaking of $SU(5)$. The breaking of $U(1)_{\chi}$ symmetry leaves a residual discrete $Z_2$ symmetry, that serves as the MSSM matter parity, reali

William Borrelli, Sunra Mosconi, Marco Squassina

We prove that quasi-concave positive solutions to a class of quasi-linear elliptic equations driven by the $p$-Laplacian in convex bounded domains of the plane have only one critical point. As a consequence, we obtain strict concavity results for suitable transformations of these solutions.

Wonpyo Park, Woonggi Chang, Donggeon Lee, Juntae Kim

We propose a novel positional encoding for learning graph on Transformer architecture. Existing approaches either linearize a graph to encode absolute position in the sequence of nodes, or encode relative position with another node using bias terms. The former loses preciseness of relative position from linearization, while the latter loses a tight integrati

Misato Horiuchi, Yuya Sasaki, Chuan Xiao, Makoto Onizuka

Computational notebook software such as Jupyter Notebook is popular for data science tasks. Numerous computational notebooks are available on the Web and reusable; however, searching for computational notebooks manually is a tedious task, and so far, there are no tools to search for computational notebooks effectively and efficiently. In this paper, we propo

Jiangyun Li, Wenxuan Wang, Chen Chen, Tianxiang Zhang

Transformer, benefiting from global (long-range) information modeling using self-attention mechanism, has been successful in natural language processing and computer vision recently. Convolutional Neural Networks, capable of capturing local features, are difficult to model explicit long-distance dependencies from global feature space. However, both local and

Alessio Zaccone

A Comment by R. Blumenfeld on our recent analytical solution for the random close packing density [A. Zaccone, Phys. Rev. Lett. 128, 028002 (2022)] is shown to be plagued by important errors and to contain incorrect statements.

Yuchen Ding

Let $\mathcal{P}$ and $\mathbb{N}$ be the sets of all primes and natural numbers, respectively. In this article, it is proved that there has a positive lower density of the natural numbers which can be represented by the form $$p+2^{m_1^2}+2^{m_2^2},p\in \mathcal{P},m_1,m_2\in \mathbb{N}.$$ This solves a problem of Chen and Yang in 2014.

Piotr Zenczykowski

We discuss implications that result from the acceptance of MOND parameter $a_M$ as the third fundamental constant of nature in addition to $c$ and $h$. To this aim we use the concept of Newtonian triangle in the $(log(r),~ log(m))$ plane and show that excited states on hadronic Regge trajectories lead into the MOND regime beyond this triangle. The experiment

Tony Stillfjord, Måns Williamson

We introduce a family of stochastic optimization methods based on the Runge-Kutta-Chebyshev (RKC) schemes. The RKC methods are explicit methods originally designed for solving stiff ordinary differential equations by ensuring that their stability regions are of maximal size.In the optimization context, this allows for larger step sizes (learning rates) and b

Liqun Qi, David M. Alexander, Zhongming Chen, Chen Ling

Dual complex numbers can represent rigid body motion in 2D spaces. Dual complex matrices are linked with screw theory, and have potential applications in various areas. In this paper, we study low rank approximation of dual complex matrices. We define $2$-norm for dual complex vectors, and Frobenius norm for dual complex matrices. These norms are nonnegative

J. N. Iyer, R. Parimala

Let $C$ be a smooth projective curve of genus 2 over a number field $k$ with a rational point. We prove that the index and exponent coincide for elements in the 2-torsion of $\Sha(Br(C))$. In the appendix, an isomorphism of the moduli space of rank 2 stable vector bundles with odd determinant on a smooth projective hyperelliptic curve $C$ of genus $g$ with a

Ivan Limonchenko, Taras Panov

We give a correct statement and a complete proof of the criterion obtained by Grbi\'c, Panov, Theriault and Wu for the face ring $\Bbbk[K]$ of a simplicial complex $K$ to be Golod over a field $\Bbbk$. (The original argument depended on the main result of a paper by Berglund and J\"ollenbeck, which was shown to be false by Katth\"an.) We also construct an ex

Vishal P. Patil, Žiga Kos, Jörn Dunkel

We describe a general procedure for mapping arbitrary $n$-qubit states to two-dimensional (2D) vector fields. The mappings use complex rational function representations of individual qubits, producing classical vector field configurations that can be interpreted in terms of 2D inviscid fluid flows or electric fields. Elementary qubits are identified with loc

Benoît Collins, Razvan Gurau, Luca Lionni

We consider the recently introduced generalization of the Harish-Chandra--Itzykson--Zuber integral to tensors and discuss its asymptotic behavior when the characteristic size N of the tensors is taken to be large. This study requires us to make assumptions on the scaling with N of the external tensors. We analyze a two-parameter class of asymptotic scaling a

Wei Tang, Yue Zhou, Ferdinando Zullo

Lunardon and Polverino introduced in 2001 a new family of maximum scattered linear sets in $\mathrm{PG}(1,q^n)$ to construct linear minimal R\'edei blocking sets. This family has been extended first by Lavrauw, Marino, Trombetti and Polverino in 2015 and then by Sheekey in 2016 in two different contexts (semifields and rank metric codes). These linear sets a

Qi Liu, Zirui Li, Xueyuan Li, Jingda Wu

An efficient and reliable multi-agent decision-making system is highly demanded for the safe and efficient operation of connected autonomous vehicles in intelligent transportation systems. Current researches mainly focus on the Deep Reinforcement Learning (DRL) methods. However, utilizing DRL methods in interactive traffic scenarios is hard to represent the

Kevin C. Stitely, Andrus Giraldo, Bernd Krauskopf, Scott Parkins

We study the effect of spontaneous emission and incoherent atomic pumping on the nonlinear semiclassical dynamics of the unbalanced Dicke model -- a generalization of the Dicke model that features independent coupling strengths for the co- and counter-rotating interaction terms. As well as the ubiquitous superradiant behavior the Dicke model is well-known fo

Lei Fu, Shoichi Yamada

We investigate the gravitational waves (GWs) at low frequencies produced by neutrinos that are emitted anisotropically from the proto-neutron star (PNS) during its cooling phase that lasts about a minute. We first give a formulation based on the spherical-harmonic expansion of the neutrino luminosity to obtain the gravitational waveform as well as the charac

Saeed Ranjbar Alvar, Ivan V. Bajić

This document describes a noise generator that simulates realistic noise found in smartphone cameras. The generator simulates Poissonian-Gaussian noise whose parameters have been estimated on the Smartphone Image Denoising Dataset (SIDD). The generator is available online, and is currently being used in compressed-domain denoising exploration experiments in

Penghui Yao, Yitong Yin, Xinyuan Zhang

Zero-free based algorithm is a major technique for deterministic approximate counting. In Barvinok's original framework[Bar17], by calculating truncated Taylor expansions, a quasi-polynomial time algorithm was given for estimating zero-free partition functions. Patel and Regts[PR17] later gave a refinement of Barvinok's framework, which gave a polynomial-tim

Jannik Zürn, Wolfram Burgard

Robust detection of moving vehicles is a critical task for any autonomously operating outdoor robot or self-driving vehicle. Most modern approaches for solving this task rely on training image-based detectors using large-scale vehicle detection datasets such as nuScenes or the Waymo Open Dataset. Providing manual annotations is an expensive and laborious exe

Sreeraj Nair, Chandan Mondal, Xingbo Zhao, Asmita Mukherjee

We solve for the light-front wave functions (LFWFs) of the physical photon from the eigenvectors of the light-front quantum electrodynamics (QED) Hamiltonian with the aim to determine its bare photon and electron-positron Fock components. We then employ the resulting LFWFs to compute the transverse momentum dependent parton distributions (TMDs) and the gener

Chuanyu Luo, Xiaohan Li, Nuo Cheng, Han Li

Semantic segmentation of 3D point cloud is an essential task for autonomous driving environment perception. The pipeline of most pointwise point cloud semantic segmentation methods includes points sampling, neighbor searching, feature aggregation, and classification. Neighbor searching method like K-nearest neighbors algorithm, KNN, has been widely applied.

Di Li, Wenjie Zhang, Peng Suo, Jiaming Chen

Strong Coulomb interactions in two-dimensional systems, together with quantum confinement, make many-body processes particularly effective for carrier dynamics, which plays a crucial role in determining carrier lifetime, photoconductivity, and emission yield of the materials. Hereby, by using optical pump and terahertz probe spectroscopy, we have investigate

Haris Moazam Sheikh, Philip S. Marcus

Optimizing multiple, non-preferential objectives for mixed-variable, expensive black-box problems is important in many areas of engineering and science. The expensive, noisy, black-box nature of these problems makes them ideal candidates for Bayesian optimization (BO). Mixed-variable and multi-objective problems, however, are a challenge due to BO's underlyi

P. Klimov, M. Battisti, A. Belov, M. Bertaina

K-EUSO (KLYPVE-EUSO) is a planned orbital mission aimed at studying ultra-high energy cosmic rays (UHECRs) by detecting fluorescence and Cherenkov light emitted by extensive air showers in the nocturnal atmosphere of Earth in the ultraviolet (UV) range. The observatory is being developed within the JEM-EUSO collaboration and is planned to be deployed on the

Yong Guo, David Stutz, Bernt Schiele

Despite their success, deep networks have been shown to be highly susceptible to perturbations, often causing significant drops in accuracy. In this paper, we investigate model robustness on perturbed inputs by studying the performance of internal sub-networks (subnets). Interestingly, we observe that most subnets show particularly poor robustness against pe

Cheng Chen, Chun-Gui Duan, Zhi-Hui Guo

In this work, we perform a detailed study of the $\tau^-\to\pi^-\pi^0\gamma\nu$ decay process within the resonance chiral theory. We pay special attention to the triple-product asymmetry in the $\tau^-\to\pi^-\pi^0\gamma\nu$ process. The minimal resonance chiral Lagrangian and the odd-intrinsic parity resonance operators are simultaneously included to calcul

Chengjie Niu, Manyi Li, Kai Xu, Hao Zhang

We introduce RIM-Net, a neural network which learns recursive implicit fields for unsupervised inference of hierarchical shape structures. Our network recursively decomposes an input 3D shape into two parts, resulting in a binary tree hierarchy. Each level of the tree corresponds to an assembly of shape parts, represented as implicit functions, to reconstruc

Alexander Gelfgat

Effect of interfacial disturbances on instabilities of buoyant/thermocapillary convective flows in rectangular cavities is studied in a series of numerical experiments. The computations are carried out for several two-liquid two-layer systems taking into account properties of liquids used in previously published experiments. Relation between the interface de

Zhe Feng, Dongdong Wan, Bo-Fu Wang, Mengqi Zhang

This work studies the effects of a through-flow on two-dimensional electrohydrodynamic (EHD) flows of a dielectric liquid confined between two plane plates, as a model problem to further our understanding of the fluid mechanics in the presence of an electric field. The liquid is subjected to a strong unipolar charge injection from the bottom plate and a pres

Nadav Timor, Gal Vardi, Ohad Shamir

We study the conjectured relationship between the implicit regularization in neural networks, trained with gradient-based methods, and rank minimization of their weight matrices. Previously, it was proved that for linear networks (of depth 2 and vector-valued outputs), gradient flow (GF) w.r.t. the square loss acts as a rank minimization heuristic. However,

Manoj Bhardwaj, Alexander V. Osipov

In this paper, we defined two new games - the mildly Menger game and the compact-clopen game. In a zero-dimensional space, the Menger game is equivalent to the mildly Menger game and the compact-open game is equivalent to the compact-clopen game. An example is given for a space on which the mildly Menger game is undetermined. Also we introduced a new game na

Lu Wang, Uwe Niedermayer, Jingui Ma, Weihao Liu

Limited by the difficulty in acceleration synchronization, it has been a long-term challenge for on-chip dielectric laser-based accelerators (DLA) to bridge the gap between non-relativistic and relativistic regimes. Here, we propose a DLA based on a spatio-temporal coupling (STC) controlled laser pulse, which enables the acceleration of a non-relativistic el

F. Casaburo, N. Marcelli, M. Sorbara, M. Agostinelli

To establish a closer contact between school and experimental sciences, Sapienza Universit\`a di Roma and the Istituto Nazionale di Fisica Nucleare (INFN) launched the Lab2Go project. Lab2Go has the goal of spreading laboratory practice among students and teachers in high schools. In this article, it is presented a measurement, carried out in the framework o

H. W. Zhang, Z. W. Ma, T. Chen

The electron inertia term and the off-diagonal electron pressure terms are well-known for the frozen-in condition breakdown in collisionless magnetic reconnection, which are naturally kinetic and difficult to be employed in magnetohydrodynamic (MHD) simulations. After considering the shortcomings of MHD and Hall MHD in neglecting the important electron dynam

Tianrui Wang, Weibin Zhu, Yingying Gao, Junlan Feng

Mask processing in the time-frequency (T-F) domain through the neural network has been one of the mainstreams for single-channel speech enhancement. However, it is hard for most models to handle the situation when harmonics are partially masked by noise. To tackle this challenge, we propose a harmonic gated compensation network (HGCN). We design a high-resol

Huan Cao, Marc-Olivier Renou, Chao Zhang, Gaël Massé

Quantum theory predicts the existence of genuinely tripartite-entangled states, which cannot be obtained from local operations over any bipartite entangled states and unlimited shared randomness. Some of us recently proved that this feature is a fundamental signature of quantum theory. The state $\left|{GHZ}_3\right\rangle=(\left|000\right\rangle+\left|111\r

Jason Hanson

In a previous article, the exterior algebra bundle over spacetime was used as a common geometric framework for obtaining the Dirac and Einstein equations, with other forces incorporated using minimal coupling. Here the fundamental forces that are allowed within this framework are explicitly enumerated.

Ya-Li Mao, Zheng-Da Li, Sixia Yu, Jingyun Fan

While Bell nonlocality of a bipartite system is counter-intuitive, multipartite nonlocality in our many-body world turns out to be even more so. Recent theoretical study reveals in a theory-agnostic manner that genuine multipartite nonlocal correlations cannot be explained by any causal theory involving fewer-partite nonclassical resources and global shared

Bora Kim

Empirical researchers are often interested in not only whether a treatment affects an outcome of interest, but also how the treatment effect arises. Causal mediation analysis provides a formal framework to identify causal mechanisms through which a treatment affects an outcome. The most popular identification strategy relies on so-called sequential ignorabil

Tassilo Naujoks, Roshini Jayabalan, Christopher Kirsch, Fengshuo Zu

Surface-defect passivation is key to achieving high photoluminescence quantum yield in lead halide perovskite nanocrystals. However, in perovskite light-emitting diodes these surface ligands also have to enable balanced charge injection into the nanocrystals to yield high efficiency and operational lifetime. In this respect, alkaline halides have been report

Long Wang

Consider a cohomologically hyperbolic birational self-map defined over the algebraic numbers, for example, a birational self-map in dimension two with the first dynamical degree greater than one, or in dimension three with the first and the second dynamical degrees distinct. We give a boundedness result about heights of its periodic points. This is motivated

Richard Berkovits

In recent years it became clear that the metallic regime of systems that exhibit a many body localization (MBL) behavior show properties which are quite different than the vanilla metallic region of the single particle Anderson regime. Here we show that the large scale energy spectrum of a canonical microscopical model featuring MBL, displays a non-universal

Chris Kowall, Anna Marciniak-Czochra, Finn Münnich

Reaction-diffusion equations coupled to ordinary differential equations (ODEs) may exhibit spatially low-regular stationary solutions. This work provides a comprehensive theory of asymptotic stability of bounded, discontinuous or continuous, stationary solutions of reaction-diffusion-ODE systems. We characterize the spectrum of the linearized operator and re

Yuan-Chun Jing, Xuan Li, Fu-Zhong Yang

The number of rational points in toric data are given for two-parameter Calabi-Yau $n$-folds as toric hypersurfaces over finite fields $\mathbb F_p$ . We find that the fundamental period is equal to the number of rational points of the Calabi-Yau $n$-folds in zeroth order $p$-adic expansion. By analyzing the solution set of the GKZ-system given by the enhanc

Francisco Pernice, Ray Li, Mary Wootters

Given a probability distribution $\mathcal{D}$ over the non-negative integers, a $\mathcal{D}$-repeat channel acts on an input symbol by repeating it a number of times distributed as $\mathcal{D}$. For example, the binary deletion channel ($\mathcal{D}=Bernoulli$) and the Poisson repeat channel ($\mathcal{D}=Poisson$) are special cases. We say a $\mathcal{D}

Iurii S. Nagornov

Motivation: A branching processes model yields an unevenly stochastically distributed dataset that consists of sparse and dense regions. This work addresses the problem of precisely evaluating parameters for such a model. Applying a branching processes model to an area such as cancer cell evolution faces a number of obstacles, including high dimensionality a

Hoang-Son Do

In this paper, we show the existence and uniqueness of viscosity solution to the Cauchy-Dirichlet problem for a class of fully nonlinear parabolic equations. This extends recent results of Eyssidieux-Guedj-Zeriahi.

Yi Zhou, Liangcai Zhou, Di Shi, Xiaoying Zhao

With widespread deployment of renewables, the electric power grids are experiencing increasing dynamics and uncertainties, with its secure operation being threatened. Existing frequency control schemes based on day-ahead offline analysis and minute-level online sensitivity calculations are difficult to adapt to rapidly changing system states. In particular,

Sunao Oka, Susumu Goto

To investigate the attenuation of turbulence in a periodic cube due to the addition of spherical solid particles, we conduct direct numerical simulations using an immersed boundary method with resolving flow around each particle. Numerical results with systematically changing particle diameters and Stokes numbers for a fixed volume fraction $\Lambda$ show th

Tao Luo, Yan-Lin Wang, Huihui Zeng

We prove the nonlinear asymptotic stability of the gravitational hydrostatic equilibrium for the general equation of state of pressure-density relation in the framework of vacuum free boundary problem of spherically symmetric compressible Navier-Stokes-Poisson equations in three dimensions.The results apply to white dwarfs and polytropes with $\gamma\ge 2$,

Chenhui Deng, Xiuyu Li, Zhuo Feng, Zhiru Zhang

Graph neural networks (GNNs) have been increasingly deployed in various applications that involve learning on non-Euclidean data. However, recent studies show that GNNs are vulnerable to graph adversarial attacks. Although there are several defense methods to improve GNN robustness by eliminating adversarial components, they may also impair the underlying cl

Tian Zhou, Ziqing Ma, Qingsong Wen, Xue Wang

Although Transformer-based methods have significantly improved state-of-the-art results for long-term series forecasting, they are not only computationally expensive but more importantly, are unable to capture the global view of time series (e.g. overall trend). To address these problems, we propose to combine Transformer with the seasonal-trend decompositio

Yexiong Lin, Yu Yao, Yuxuan Du, Jun Yu

Algorithms which minimize the averaged loss have been widely designed for dealing with noisy labels. Intuitively, when there is a finite training sample, penalizing the variance of losses will improve the stability and generalization of the algorithms. Interestingly, we found that the variance should be increased for the problem of learning with noisy labels

Byunggook Na, Jisoo Mok, Seongsik Park, Dongjin Lee

Spiking neural networks (SNNs) that mimic information transmission in the brain can energy-efficiently process spatio-temporal information through discrete and sparse spikes, thereby receiving considerable attention. To improve accuracy and energy efficiency of SNNs, most previous studies have focused solely on training methods, and the effect of architectur

Fengdong Cheng, Dayun Yan, Jie Chen, Zi Wang

Cold atmospheric plasma (CAP) is a near room temperature ionized gas, generated under non-equilibrium discharge conditions. Here we show that a short exposure of rat peritoneal exudate macrophages and T-cells to CAP in vitro, triggered an inflammatory phenotype leading to better antigen-presenting and effector cell function respectively. Different from previ

Mengxiao Zhang, Peng Zhao, Haipeng Luo, Zhi-Hua Zhou

Learning from repeated play in a fixed two-player zero-sum game is a classic problem in game theory and online learning. We consider a variant of this problem where the game payoff matrix changes over time, possibly in an adversarial manner. We first present three performance measures to guide the algorithmic design for this problem: 1) the well-studied indi

Vladimir A. Sablikov, Bagun S. Shchamkhalova

Bound electron pairs formed due to the peculiarities of the band dispersion of electrons in crystals attract much interest because they can carry charge and spin even in the absence of band conductivity. However, such an important parameter of bound pairs as the effective mass is still poorly understood. We carry out this study for materials described by the

Suratno Basu, Sarbeswar Pal

Let $X$ be a smooth projective algebraic surface of Picard rank one with very ample canonical bundle $K_X$. We further assume that $q -1 \le \chi(\mathcal{O}_X$. In this article, we will study the existence of the Ulrich bundle and its stability property of it with respect to $K_X$.

Wenda Chu, Linyi Li, Bo Li

Point cloud models with neural network architectures have achieved great success and have been widely used in safety-critical applications, such as Lidar-based recognition systems in autonomous vehicles. However, such models are shown vulnerable to adversarial attacks which aim to apply stealthy semantic transformations such as rotation and tapering to misle

Daryll Ralph D'Costa, Robert Abbas

The world is moving into a new era with the deployment of 5G communication infrastructure. Many new developments are deployed centred around this technology. One such advancement is 5G Vehicle to Everything communication. This technology can be used for applications such as driverless delivery of goods, immediate response to emergencies and improving traffic

Yunjae Hwang, Laura, Kwong, Mohammad Saeed Munim

According to UNICEF, pneumonia is the leading cause of death in children under 5. 70% of worldwide pneumonia deaths occur in only 15 countries, including Bangladesh. Previous research has indicated a potential association between the incidence of pneumonia and the presence of cross-ventilation in slum housing in Dhaka, Bangladesh. The objective of this resea

Hong-Bin Chen, Jiaming Xia

We give a meaning to the Hamilton--Jacobi equation arising from mean-field spin glass models in the viscosity sense, and establish the corresponding well-posedness. Originally defined on the set of monotone probability measures, these equations can be interpreted, via an isometry, to be defined on an infinite-dimensional closed convex cone with an empty inte

Maxim Bichuch, Nils Detering

We consider a network of bank holdings, where every holding has two subsidiaries of different types. A subsidiary can trade with another holding's subsidiary of the same type. Holdings support their subsidiaries up to a certain level when they would otherwise fail to honor their financial obligations. We investigate the spread of contagion in this banking ne

Lev Gelimson

A general piecewise (including pointwise) probability distribution with space-saving notation and its hierarchical particular cases are considered. The explicit closed-form normalization, expectation, and variance formulas along with the median and mode formulas and algorithms for a general one-dimensional piecewise linear probability distribution are obtain

Shao-Wen Wei, Hui-Min Wang, Yu-Peng Zhang, Yu-Xiao Liu

Recent study shows that the magnetic reconnection can serve as an efficient mechanism to extract energy from rapidly spinning black holes. In this paper, we consider the effects of the tidal charge on the energy extraction via the magnetic reconnection in the backgrounds of a spinning braneworld black hole. With the increase of the tidal charge, we find that

Xianye Ben, Yi Ren, Junping Zhang, Su-Jing Wang

Unlike the conventional facial expressions, micro-expressions are involuntary and transient facial expressions capable of revealing the genuine emotions that people attempt to hide. Therefore, they can provide important information in a broad range of applications such as lie detection, criminal detection, etc. Since micro-expressions are transient and of lo

Ziaur Rahman, Xun Yi Ibrahim Khalil

Industry 4.0 is all about doing things in a concurrent, secure, and fine-grained manner. IoT edge-sensors and their associated data play a predominant role in today's industry ecosystem. Breaching data or forging source devices after injecting advanced persistent threats (APT) damages the industry owners' money and loss of operators' lives. The existing chal

Xinghe Chu, Zhaoming Lu, David Gesbert, Luhan Wang

This paper addresses high-resolution vehicle positioning and tracking. In recent work, it was shown that a fleet of independent but neighboring vehicles can cooperate for the task of localization by capitalizing on the existence of common surrounding reflectors, using the concept of Team Channel-SLAM. This approach exploits an initial (e.g. GPS-based) vehicl

Bicheng Guo, Tao Chen, Shibo He, Haoyu Liu

Neural Architecture Search (NAS) is a powerful tool for automating effective image processing DNN designing. The ranking has been advocated to design an efficient performance predictor for NAS. The previous contrastive method solves the ranking problem by comparing pairs of architectures and predicting their relative performance. However, it only focuses on

Liu Ziyin, Hanlin Zhang, Xiangming Meng, Yuting Lu

This work theoretically studies stochastic neural networks, a main type of neural network in use. We prove that as the width of an optimized stochastic neural network tends to infinity, its predictive variance on the training set decreases to zero. Our theory justifies the common intuition that adding stochasticity to the model can help regularize the model

Ziyang Luo, Yadong Xi, Rongsheng Zhang, Jing Ma

Image Captioning is a fundamental task to join vision and language, concerning about cross-modal understanding and text generation. Recent years witness the emerging attention on image captioning. Most of existing works follow a traditional two-stage training paradigm. Before training the captioning models, an extra object detector is utilized to recognize t

Kolluru Venkata Kiran, Anupam Gupta, Akhilesh Kumar Verma and, Rahul Pandit

We use the mean-bacterial-velocity model to investigate the \textit{irreversibility} of two-dimensional (2D) \textit{bacterial turbulence} and to compare it with its 2D fluid-turbulence counterpart. We carry out extensive direct numerical simulations of Lagrangian tracer particles that are advected by the velocity field in this model. Our work uncovers an im

T. Machida, Y. Yoshimura, T. Nakamura, Y. Kohsaka

Two-dimensional Rashba superconductor Si(111)-$\sqrt{3}\times\sqrt{3}$-(Tl,Pb) is a candidate platform of mixed spin-singlet and -triplet superconductivity. A recent scanning tunneling microscope (STM) experiment revealed a pseudogap at the vortex core, suggesting the finite triplet component [T. Nakamura $\textit{et al.}$, Phys. Rev. B $\bf{ 98}$, 134505 (2

Chung-Chuan Lai, Robert Boyd, Per-Olof Svensson, Carina Höglund

Amorphous boron carbide (B4C) thin films are by far the most popular form for the neutron converting layers in the 10B-based neutron detectors, which are a rising trend in detector technologies in response to the increasing scarcity and price of 3He, the standard material for neutron detection. The microstructure of the B4C films is closely related to the im

Tiancheng Qin, S. Rasoul Etesami, César A. Uribe

Modern machine learning architectures are often highly expressive. They are usually over-parameterized and can interpolate the data by driving the empirical loss close to zero. We analyze the convergence of Local SGD (or FedAvg) for such over-parameterized models in the heterogeneous data setting and improve upon the existing literature by establishing the f

Xing Xu, Rongpeng Li, Zhifeng Zhao, Honggang Zhang

The paper considers independent reinforcement learning (IRL) for multi-agent decision-making process in the paradigm of federated learning (FL). We show that FL can clearly improve the policy performance of IRL in terms of training efficiency and stability. However, since the policy parameters are trained locally and aggregated iteratively through a central

Glenn Bruda

Maclaurin Integration is a new series-based technique for solving infamously difficult integrals in terms of elementary functions. It has fairly liberal conditions for sound use, making it one of the most versatile integration techniques. Additionally, there is essentially zero human labor involved in calculating integrals using this technique, making it one

Bowen Wen, Wenzhao Lian, Kostas Bekris, Stefan Schaal

Promising results have been achieved recently in category-level manipulation that generalizes across object instances. Nevertheless, it often requires expensive real-world data collection and manual specification of semantic keypoints for each object category and task. Additionally, coarse keypoint predictions and ignoring intermediate action sequences hinde

Zi-Yue Bai, Yu-Shuai Li, Qi Huang, Xiang Liu

In this work, we investigate the $\Upsilon(10753)\to\Upsilon(nS)\pi^+\pi^-$ ($n=1,2,3$) processes by considering the hadronic loop mechanism, where $\Upsilon(10753)$ is assigned to a conventional bottomonium in the $4S$-$3D$ mixing scheme. Our results of the concerned processes own considerable branching ratios, which can reach up to the order of magnitude o

Zicheng Ye, Yuan Li, Huazi Zhang, Rong Li

Automorphism ensemble (AE) decoding for polar codes was proposed by decoding permuted codewords with successive cancellation (SC) decoders in parallel and hence has lower latency compared to that of successive cancellation list (SCL) decoding. However, some automorphisms are SC-invariant, thus are redundant in AE decoding. In this paper, we find a necessary

Johan Koskinen, Tom A. B. Snijders

Stochastic actor-oriented models (SAOM) are a broadly applied modelling framework for analysing network dynamics using network panel data. They have been extended to address co-evolution of multiple networks as well as networks and behaviour. This paper extends the SAOM to the analysis of multiple network panels through a random coefficient multilevel model,

Yuzhang Shang, Bin Duan, Ziliang Zong, Liqiang Nie

With the remarkable success of deep learning recently, efficient network compression algorithms are urgently demanded for releasing the potential computational power of edge devices, such as smartphones or tablets. However, optimal network pruning is a non-trivial task which mathematically is an NP-hard problem. Previous researchers explain training a pruned

Konstantinos Mamis

We extend Stein's lemma for averages that explicitly contain the Gaussian random variable at a power. We present two proofs for this extension of Stein's lemma, with the first being a rigorous proof by mathematical induction. The alternative, second proof is a constructive formal derivation in which we express the average not as an integral, but as the actio

Chern Chuang, Paul Brumer

We simulate the nonequilibrium steady state \textit{cis-trans} photoisomerization of retinal chromophore in rhodopsin based on a two-state-two-mode model coupled to a thermal environment. By analyzing the systematic trends within an inhomogeneously broadened ensemble of systems, we find that the steady state reaction quantum yield (QY) correlates strongly wi

Sepehr Assadi, Vihan Shah

We present an algorithm for the maximum matching problem in dynamic (insertion-deletions) streams with *asymptotically optimal* space complexity: for any $n$-vertex graph, our algorithm with high probability outputs an $\alpha$-approximate matching in a single pass using $O(n^2/\alpha^3)$ bits of space. A long line of work on the dynamic streaming matching p

Hongbing Zhang, Xinyi Liu, Hongtao Fan, Yajing Li

Low-rank tensor completion (LRTC) is an important problem in computer vision and machine learning. The minimax-concave penalty (MCP) function as a non-convex relaxation has achieved good results in the LRTC problem. To makes all the constant parameters of the MCP function as variables so that futherly improving the adaptability to the change of singular valu

Wei-Jian Li, Rui Xue, Guang-Bo Long, Ze-Rui Wang

Context. The intrinsic TeV emission of some BL Lacs are characterized by a hard spectrum (the hard-TeV spectrum) after correcting for the extragalactic background light. The hard-TeV spectra pose a challenge to conventional one-zone models, including the leptonic model, the photohadronic model, the proton synchrotron model, etc. Aims. In this work, we study

Daniel Suárez

We characterize the algebra $H^\infty \circ L_{m}$, where $m$ is a point of the maximal ideal space of $H^\infty$ with nontrivial Gleason part $P(m)$ and $L_{m} : \mathbb{D}\to P(m)$ is the coordinate Hoffman map. In particular, it is shown that for any continuous function $f: P(m) \to \mathbb{C}$ with $f\circ L_{m} \in H^\infty$ there exists $F\in H^\infty$

M. I. Naher, S. H. Naqib

Binary carbides demonstrate attractive set of physical properties that are suitable for numerous and diverse applications. In the present study, we have explored the structural properties, electronic structures, elastic constants, acoustic behaviors, phonon dispersions, optical properties, and various thermophysical properties of binary orthogonal and hexago

Nyle Siddiqui, Rushit Dave, Tyler Bauer, Thomas Reither

Facial emotion recognition is a vast and complex problem space within the domain of computer vision and thus requires a universally accepted baseline method with which to evaluate proposed models. While test datasets have served this purpose in the academic sphere real world application and testing of such models lacks any real comparison. Therefore we propo

Xuyang Yu, Xiao-Liang Qi

Measurement-induced entanglement phase transitions, caused by the competition between entangling unitary dynamics and disentangling projective measurements, have been studied in various random circuit models in recent years. In this paper, we study the dynamics of averaged purity for a simple $N$-qudit Brownian circuit model with all-to-all random interactio

Jonathan Lai, Yan Zhou

We show that the ring of regular functions of every smooth affine log Calabi-Yau surface with maximal boundary has a vector space basis parametrized by its set of integer tropical points and a $\mathbb{C}$-algebra structure with structure coefficients given by the geometric construction of Keel-Yu. To prove this result, we first give a canonical compactifica

Shuai Wang, Ruihua Han, Yuncong Hong, Qi Hao

Wireless energy transfer (WET) is a ground-breaking technology for cutting the last wire between mobile sensors and power grids in smart cities. Yet, WET only offers effective transmission of energy over a short distance. Robotic WET is an emerging paradigm that mounts the energy transmitter on a mobile robot and navigates the robot through different regions