August 2022 arXiv papers — page 39

Sergei A. Avdonin, Sergei A. Ivanov

B.\,Ya.\,Levin has proved that zero set of a sine type function can be presented as a union of a finite number of separated sets, that is an important result in the theory of exponential Riesz bases. In the present paper we extend Levin's result to a more general class of entire functions $F(z)$ with zeros in a strip $0<q \leq \Im z \leq Q,$ such that $|F(x)

Zijian Gao, YiYing Li, Kele Xu, Yuanzhao Zhai

The sparsity of extrinsic rewards poses a serious challenge for reinforcement learning (RL). Currently, many efforts have been made on curiosity which can provide a representative intrinsic reward for effective exploration. However, the challenge is still far from being solved. In this paper, we present a novel curiosity for RL, named DyMeCu, which stands fo

Feng Fan

Measurements of charged-particle production in pp and p-Pb collisions at $\sqrt{s}_{\rm NN}=5.02$ TeV in the toward, away and transverse regions are discussed. These three regions are defined event by event relative to the track with the largest transverse momentum ($p_{\rm T}^{\rm trig}$). The transverse region is sensitive to the underlying event (UE), but

Junda Chen

Formation control problem is one of the most concerned topics within the realm of swarm intelligence, which is usually solved by conventional mathematical approaches. In this paper, however, we presents a metaheuristic approach that leverages a natural co-evolutionary strategy to solve the formation control problem for a swarm of missiles. The missile swarm

Xuecheng Wu, Mengmeng Tian, Lanhang Zhai

With the fast development of artificial intelligence and short videos, emotion recognition in short videos has become one of the most important research topics in human-computer interaction. At present, most emotion recognition methods still stay in a single modality. However, in daily life, human beings will usually disguise their real emotions, which leads

Elena G. Kupriyanova, Tatyana I. Kaltman, Alexey A. Kuznetsov

The modulation of the microwave emission intensity from a flaring loop by a standing linear sausage fast magnetoacoustic wave is considered in terms of a straight plasma slab with the perpendicular Epstein profile of the plasma density, penetrated by a magnetic field. The emission is of the gyrosynchrotron (GS) nature, and is caused by mildly relativistic el

Alexander Genser, Michail A. Makridis, Kaidi Yang, Lukas Ambühl

Recently, efforts have been made to standardize signal phase and timing (SPaT) messages. These messages contain signal phase timings of all signalized intersection approaches. This information can thus be used for efficient motion planning, resulting in more homogeneous traffic flows and uniform speed profiles. Despite efforts to provide robust predictions f

Yijin Pan, Cunhua Pan, Shi Jin, Jiangzhou Wang

The low hardware cost makes ultra-large (XL) reconfigurable intelligent surface (RIS) an attractive solution for the performance enhancement of localization and communication systems, but it results in near-field propagation channels, especially for the high-frequency communication systems, e.g. mmWave and sub-terahertz (subTHz) systems. This makes localizat

Keshigeyan Chandrasegaran, Ngoc-Trung Tran, Alexander Binder, Ngai-Man Cheung

Visual counterfeits are increasingly causing an existential conundrum in mainstream media with rapid evolution in neural image synthesis methods. Though detection of such counterfeits has been a taxing problem in the image forensics community, a recent class of forensic detectors -- universal detectors -- are able to surprisingly spot counterfeit images rega

Andreas Sauer, Andreas Schweizer

We determine all entire functions $f$ such that for nonzero complex values $a\neq b$ the implications $f=a \Rightarrow f' =a$ and $f' =b \Rightarrow f=b$ hold. This solves an open problem in uniqueness theory. In this context we give a normality criterion, which might be interesting in its own right.

Markus Hecher

Computer programs, so-called solvers, for solving the well-known Boolean satisfiability problem (Sat) have been improving for decades. Among the reasons, why these solvers are so fast, is the implicit usage of the formula's structural properties during solving. One of such structural indicators is the so-called treewidth, which tries to measure how close a f

Marco Avvenuti, Marco Bongiovanni, Luca Ciampi, Fabrizio Falchi

Automatic people counting from images has recently drawn attention for urban monitoring in modern Smart Cities due to the ubiquity of surveillance camera networks. Current computer vision techniques rely on deep learning-based algorithms that estimate pedestrian densities in still, individual images. Only a bunch of works take advantage of temporal consisten

Veta Ghenescu

The LUXE experiment aims at studying high-field QED in electron-laser and photon-laser interactions, with the 16.5 GeV electron beam of the European XFEL and a laser beam with power of up to 350 TW. The experiment will measure the spectra of electrons, positrons and photons in the expected range of ${10}^{-3}$ to ${10}^9$ per 1 Hz bunch crossing, depending o

Anthony Fillion, Thibaut Kulak, François Blayo

We propose organisation conditions that yield a method for training SOM with adaptative neighborhood radius in a variational Bayesian framework. This method is validated on a non-stationary setting and compared in an high-dimensional setting with an other adaptative method.

Chengcheng Han, Sihui Huang, Zhanhong Lei

Recently it has been found that introducing a triplet Higgs to the standard model could provide a feasible leptogenesis to generate the baryon asymmetry of our universe, providing that the inflation is driven by the mixing state of the triplet Higgs and SM Higgs. In this work, we survey the viable parameter space satisfying the vacuum stability and perturbat

Djibrilla Amadou Kountche, Fatma Raissi, Mandimby Ranaivo Rakotondravelona, Edoardo Bonetto

Today's vehicles are increasingly embedded with computers and sensors which produce huge amount of data. The data are exploited for internal purposes and with the development of connected infrastructures and smart cities, the vehicles interact with each other as well as with road users generating other types of data. The access to these data and in-vehicle r

Martin Korth

The tremendous advances of research into artificial intelligence as well as neuroscience made over the last two to three decades have given further support to a renewed interest into philosophical discussions of the mind-body problem. Especially the last decade has seen a revival of panpsychist and idealist considerations, often focused on solving philosophi

Henri Arno, Klaas Mulier, Joke Baeck, Thomas Demeester

Models for bankruptcy prediction are useful in several real-world scenarios, and multiple research contributions have been devoted to the task, based on structured (numerical) as well as unstructured (textual) data. However, the lack of a common benchmark dataset and evaluation strategy impedes the objective comparison between models. This paper introduces s

Sijie Ji, Mo Li

CSI feedback is an important problem of Massive multiple-input multiple-output (MIMO) technology because the feedback overhead is proportional to the number of sub-channels and the number of antennas, both of which scale with the size of the Massive MIMO system. Deep learning-based CSI feedback methods have been widely adopted recently owing to their superio

Tomohiro Suzuki, Kazuya Takeda, Keisuke Fujii

Automatic fault detection is a major challenge in many sports. In race walking, referees visually judge faults according to the rules. Hence, ensuring objectivity and fairness while judging is important. To address this issue, some studies have attempted to use sensors and machine learning to automatically detect faults. However, there are problems associate

Ross Street

This work results from a study of Nicholas Kuhn's paper entitled "Generic representation theory of finite fields in nondescribing characteristic". Our goal is to abstract the categorical structure required to obtain an equivalence between functor categories $[\mathscr{F},\mathscr{V}]$ and $[\mathscr{G},\mathscr{V}]$ where $\mathscr{G}$ is the core groupoid o

Lorenzo Rimella, Simon Alderton, Melodie Sammarro, Barry Rowlingson

We propose a novel stochastic model for the spread of antimicrobial-resistant bacteria in a population, together with an efficient algorithm for fitting such a model to sample data. We introduce an individual-based model for the epidemic, with the state of the model determining which individuals are colonised by the bacteria. The transmission rate of the epi

Yohei Fujishima, Norisuke Ioku

This paper concerns the global in time existence of solutions for a semilinear heat equation \begin{equation} \tag{P} \label{eq:P} \begin{cases} \partial_t u = \Delta u + f(u), &x\in \mathbb{R}^N, \,\,\, t>0, \\[3pt] u(x,0) = u_0(x) \ge 0, &x\in \mathbb{R}^N, \end{cases} \end{equation} where $N\ge 1$, $u_0$ is a nonnegative initial function and $f\in C^1([0,

Gang Long, Hanfeng Song, Georges Meynet, Andre Maeder

Type IIb supernovae are believed to originate from core-collapse progenitors having kept only a very thin hydrogen envelope. We aim to explore how some physical factors, such as rotation, metallicity, overshooting, and the initial orbital period in binaries, significantly affect the Roche lobe overflow and the formation of type IIb supernovae. It is found th

Weixi Zhao, Weiqiang Wang

We propose a novel attention-based 2D-to-3D pose estimation network for graph-structured data, named KOG-Transformer, and a 3D pose-to-shape estimation network for hand data, named GASE-Net. Previous 3D pose estimation methods have focused on various modifications to the graph convolution kernel, such as abandoning weight sharing or increasing the receptive

Yugeng Huang, Haitao Liu, Tian Huang

As an efficient algorithm to solve the multi-view registration problem,the motion averaging (MA) algorithm has been extensively studied and many MA-based algorithms have been introduced. They aim at recovering global motions from relative motions and exploiting information redundancy to average accumulative errors. However, one property of these methods is t

Linus Kramer, Markus J. Stroppel

We study groups of isometries on non-alternating symmetric bilinear forms on vector spaces of characteristic two, and actions of these groups on exterior powers of the space, viewed as modules over algebras generated by Hodge operators.

Kohei Morita, Shinya Shiroshita, Yutaro Yamaguchi, Yu Yokoi

We consider a dynamic situation in the weighted bipartite matching problem: edge weights in the input graph are repeatedly updated and we are asked to maintain an optimal matching at any moment. A trivial approach is to compute an optimal matching from scratch each time an update occurs. In this paper, we show that if each update occurs locally around a sing

Manuel Hahmann, Efren Fernandez-Grande

Spatial sound field interpolation relies on suitable models to both conform to available measurements and predict the sound field in the domain of interest. A suitable model can be difficult to determine when the spatial domain of interest is large compared to the wavelength or when spherical and planar wavefronts are present or the sound field is complex, a

Wanying Zhang, Yong Zhang, Jingyu Li

Let $\{u(t,x)\}_{t>0,x\in{{\mathbb R}^{d}}}$ denote the solution to a $d$-dimensional parabolic Anderson model with delta initial condition and driven by a multiplicative noise that is white in time and has a spatially homogeneous covariance given by a nonnegative-definite measure $f$. Let $S_{N,t}:=N^{-d}\int_{{[0,N]}^d}{[U(t,x)-1]}{\rm d}x$ denote the spat

Tarakanta Nayak, Soumen Pal

The set of all holomorphic Euclidean isometries preserving the Julia set of a rational map $R$ is denoted by $\Sigma R$. It is shown in this article that if a root-finding method $F$ satisfies the Scaling theorem, i.e., for a polynomial $p$, $F_p$ is affine conjugate to $F_{\lambda p \circ T}$ for every nonzero complex number $\lambda $ and every affine map

Mengdi Zhang, Jun Sun, Jingyi Wang, Bing Sun

Discrimination has been shown in many machine learning applications, which calls for sufficient fairness testing before their deployment in ethic-relevant domains such as face recognition, medical diagnosis and criminal sentence. Existing fairness testing approaches are mostly designed for identifying individual discrimination, i.e., discrimination against i

Rustem Khasanov

Pressure, together with temperature, electric and magnetic fields, alters the system and allows to investigate the fundamental properties of the matter. Under applied pressure the interatomic distances shrink, which modify interactions between atoms and may lead to appearance of a new (sometime exotic) physical properties as, e.g., pressure induced phase tra

Malte Breuer, Pascal Hein, Leonardo Pompe, Ben Temme

The kidney exchange problem (KEP) is to find a constellation of exchanges that maximizes the number of transplants that can be carried out for a set of pairs of patients with kidney disease and their incompatible donors. Recently, this problem has been tackled from a privacy perspective in order to protect the sensitive medical data of patients and donors an

Jie Xu

In this article, we first show that for all compact Riemannian manifolds with non-empty smooth boundary and dimension at least 3, there exists a metric, pointwise conformal to the original metric, with constant scalar curvature in the interior, and constant scalar curvature on the boundary by considering the boundary as a manifold of its own with dimension a

Mohammad Torabi Shahbaz, Hossein Ahmadvand, Hadi Papi, Saeideh Mokhtari

The structural, dielectric, magnetic, and magnetoelectric (ME) properties of particulate composites containing lead-iron niobate and lead titanate piezoelectric 0.94[PbFe$_{0.5}$Nb$_{0.5}$O$_3$]-0.06[PbTi$_{0.5}$O$_3$] (PFN-PT) and Zn-substituted cobalt ferrite magnetostrictive CoFe$_{2-x}$Zn$_{x}$O$_4$ (CF$_{2-x}$Z$_{x}$O); 0.6(PFN-PT)/0.4(CF$_{2-x}$Z$_{x}$

Yuchen Ding

Let $\mathcal{P}$ be the set of all primes and $\pi(x)$ be the number of primes up to $x$. For any $n\ge 2$, let $P^+(n)$ be the largest prime factor of $n$. For $0<c<1$, let $$T_c(x)=\#\{p\le x:p\in \mathcal{P},P^+(p-1)\ge p^c\}.$$ In this note, we proved that there exists some $c<1$ such that $$\limsup_{x\rightarrow\infty}\frac{T_c(x)}{\pi(x)}<\frac12,$$ w

Martinus Grady Naftali, Jason Sebastian Sulistyawan, Kelvin Julian

Object detection for street-level objects can be applied to various use cases, from car and traffic detection to the self-driving car system. Therefore, finding the best object detection algorithm is essential to apply it effectively. Many object detection algorithms have been released, and many have compared object detection algorithms, but few have compare

Sumin Lee, Sangmin Woo, Yeonju Park, Muhammad Adi Nugroho

In multi-modal action recognition, it is important to consider not only the complementary nature of different modalities but also global action content. In this paper, we propose a novel network, named Modality Mixer (M-Mixer) network, to leverage complementary information across modalities and temporal context of an action for multi-modal action recognition

Jun-Sang Yoo, Dong-Wook Kim, Yucheng Lu, Seung-Won Jung

Recent methods for single image super-resolution (SISR) have demonstrated outstanding performance in generating high-resolution (HR) images from low-resolution (LR) images. However, most of these methods show their superiority using synthetically generated LR images, and their generalizability to real-world images is often not satisfactory. In this paper, we

V. K. B. Kota

Embedded random matrix ensembles with $k$-body interactions are well established to be appropriate for many quantum systems. For these ensemble the two point correlation function is not yet derived though these ensembles are introduced 50 years back. Two-point correlation function in eigenvalues of a random matrix ensemble is the ensemble average of the prod

Rui Song, Dai Liu, Dave Zhenyu Chen, Andreas Festag

In federated learning, all networked clients contribute to the model training cooperatively. However, with model sizes increasing, even sharing the trained partial models often leads to severe communication bottlenecks in underlying networks, especially when communicated iteratively. In this paper, we introduce a federated learning framework FedD3 requiring

Pak Tung Ho, Jinwoo Shin, Zetian Yan

We introduce a Yamabe-type flow \begin{align*} \left\{ \begin{array}{ll} \frac{\partial g}{\partial t} &=(r^m_{\phi}-R^m_{\phi})g \\ \frac{\partial \phi}{\partial t} &=\frac{m}{2}(R^m_{\phi}-r^m_{\phi}) \end{array} \right. ~~\mbox{ in }M ~~\mbox{ and }~~ H^m_{\phi}=0 ~~\mbox{ on }\partial M \end{align*} on a smooth metric measure space with boundary $(M,g, v

Ren Chunying, Wu Zijun, Xu Dachuan, Yang Xiaoguang

This paper concerns computing approximate pure Nash equilibria in weighted congestion games, which has been shown to be PLS-complete. With the help of $\hat{\Psi}$-game and approximate potential functions, we propose two algorithms based on best response dynamics, and prove that they efficiently compute $\frac{\rho}{1-\epsilon}$-approximate pure Nash equilib

Evgenii Indenbom, Nicolae-Cătălin Ristea, Ando Saabas, Tanel Pärnamaa

With recent research advances, deep learning models have become an attractive choice for acoustic echo cancellation (AEC) in real-time teleconferencing applications. Since acoustic echo is one of the major sources of poor audio quality, a wide variety of deep models have been proposed. However, an important but often omitted requirement for good echo cancell

Attila Egri-Nagy, Antti Törmänen

AI engines utilizing deep learning neural networks provide excellent tools for analyzing traditional board games. Here we are interested in gaining new insights into the ancient game of Go. For that purpose, we need to define new numerical measures based on the raw output of the engines. In this paper, we develop a numerical tool for automated move-by-move p

Qi Lv, Ziqiang Cao, Wenrui Xie, Derui Wang

With the tremendously increasing number of videos, there is a great demand for techniques that help people quickly navigate to the video segments they are interested in. However, current works on video understanding mainly focus on video content summarization, while little effort has been made to explore the structure of a video. Inspired by textual outline

André Beauducel, Norbert Hilger

Mean plausible values can be computed when Bayesian structural equation modeling (BSEM) is performed. As mean plausible values do not preserve the inter-factor correlations, they yield path coefficients that are different from the estimated path coefficients of the model. As it might be of interest to perform exactly the same prediction on the level of plaus

Kazuo Misue

Morphing edge drawing (MED), a graph drawing technique, is a dynamic extension of partial edge drawing (PED), where partially drawn edges (stubs) are repeatedly stretched and shrunk by morphing. Previous experimental evaluations have shown that the reading time with MED may be shorter than that with PED. The morphing scheduling method limits visual clutter b

Hyang-Sook Lee, Seongan Lim, Ikkwon Yie, Aaram Yun

The notion of aggregator oblivious (AO) security for privacy preserving data aggregation was formalized with a specific construction of AO-secure blinding technique over a cyclic group by Shi et al. Some of proposals of data aggregation protocols use the blinding technique of Shi et al. for BGN cryptosystem, an additive homomorphic encryption. Previously, th

Chenhao Cui, Xinnian Liang, Shuangzhi Wu, Zhoujun Li

Most current multi-modal summarization methods follow a cascaded manner, where an off-the-shelf object detector is first used to extract visual features, then these features are fused with language representations to generate the summary with an encoder-decoder model. The cascaded way cannot capture the semantic alignments between images and paragraphs, whic

Steven Stetzler, Michael Grosskopf, Earl Lawrence

Fitting a theoretical model to experimental data in a Bayesian manner using Markov chain Monte Carlo typically requires one to evaluate the model thousands (or millions) of times. When the model is a slow-to-compute physics simulation, Bayesian model fitting becomes infeasible. To remedy this, a second statistical model that predicts the simulation output --

Hanzhi Wang, Yosuke Hasegawa

Drop-on-demand (DOD) inkjet printing has been considered as one of promising technologies for the fabrication of advanced functional materials. For a DOD printer, high-precision dispensing techniques for achieving satellite-free smaller droplets, have long been desired for patterning thin-film structures. The present study considers the inlet velocity of a l

Simon Klenk, Lukas Koestler, Davide Scaramuzza, Daniel Cremers

Estimating neural radiance fields (NeRFs) from "ideal" images has been extensively studied in the computer vision community. Most approaches assume optimal illumination and slow camera motion. These assumptions are often violated in robotic applications, where images may contain motion blur, and the scene may not have suitable illumination. This can cause si

Qian Qin, Guanyang Wang

Random-scan Gibbs samplers possess a natural hierarchical structure. The structure connects Gibbs samplers targeting higher dimensional distributions to those targeting lower dimensional ones. This leads to a quasi-telescoping property of their spectral gaps. Based on this property, we derive three new bounds on the spectral gaps and convergence rates of Gib

Haiyu Meng, Lingling Wang, Ching Hua Lee, Yee Sin Ang

Topological Dirac semimetals (TDSM), such as Cd$_3$As$_2$ and Na$_3$Bi, exhibits strong optical dichroism with contrasting dielectric permittivity along different crystal axes. However, such optical dichroism is often overlooked in the study of TDSM-based optoelectronic devices, and whether such optical dichroism can lead to unique functionalities not found

Katsunori Fujie, Yuki Ueda

We provide the law of large numbers for roots of finite free multiplicative convolution of polynomials which have only non-negative real roots. Moreover, we study the empirical root distributions of limit polynomials obtained through the law of large numbers of finite free multiplicative convolution when their degree tends to infinity.

Yanbei Chen, Massimiliano Mancini, Xiatian Zhu, Zeynep Akata

State-of-the-art deep learning models are often trained with a large amount of costly labeled training data. However, requiring exhaustive manual annotations may degrade the model's generalizability in the limited-label regime. Semi-supervised learning and unsupervised learning offer promising paradigms to learn from an abundance of unlabeled visual data. Re

Devabrat Mahanta, Debasish Borah

We study the possibility of generating baryon asymmetry of the universe from dark matter (DM) annihilations during non-standard cosmological epochs. Considering the DM to be of weakly interacting massive particle (WIMP) type, the generation of baryon asymmetry via leptogenesis route is studied where WIMP DM annihilation produces a non-zero lepton asymmetry.

Ziming Li, Yiming Luo, Jialin Wang, Yushan Pan

Virtual reality (VR) technology is commonly used in entertainment applications; however, it has also been deployed in practical applications in more serious aspects of our lives, such as safety. To support people working in dangerous industries, VR can ensure operators manipulate standardized tasks and work collaboratively to deal with potential risks. Surpr

Dexuan Xie

The Goldman-Hodgkin-Katz (GHK) equations have been widely applied to ion channel studies, simulations, and model developments. However, they are constructed under a constant electric field, causing them to have a low degree of approximation in the prediction of ionic fluxes, electric currents, and membrane potentials. In this paper, the equations are extende

Yan Yu, Yan-Yang Zhang, Si-Si Wang, Ji-Huan Guan

We theoretically investigate quantum transport properties of quantum anomalous Hall bilayers, with arbitrary ratio of lattice constants, i.e., with lattice mismatch. In the simplest case of ratio 1 (but with different model parameters in two layers), the inter-layer coupling results in resonant traversing between forward propagating waves in two layers. In t

Andrew J. Christlieb, William A. Sands, Stephen White

This paper formulates a new particle-in-cell method for the Vlasov-Maxwell system. Under the Lorenz gauge condition, Maxwell's equations for the electromagnetic fields can be written as a collection of scalar and vector wave equations. The use of potentials for the fields motivates the adoption of a Hamiltonian formulation for particles that employs the gene

Yue Zhao, Guoqing Zheng, Subhabrata Mukherjee, Robert McCann

Existing works on anomaly detection (AD) rely on clean labels from human annotators that are expensive to acquire in practice. In this work, we propose a method to leverage weak/noisy labels (e.g., risk scores generated by machine rules for detecting malware) that are cheaper to obtain for anomaly detection. Specifically, we propose ADMoE, the first framewor

Hugo Zhou

We construct a filtered mapping cone formula that computes the knot Floer complex of the $(n,1)$--cable of the knot meridian in any rational surgery, generalizing Truong's result about the $(n,1)$--cable of the knot meridian in large surgery and Hedden-Levine's filtered mapping cone formula. As an application, we show that there exist knots in integer homolo

Håkon Hoel, Sankarasubramanian Ragunathan

We construct a higher-order adaptive method for strong approximations of exit times of It\^o stochastic differential equations (SDE). The method employs a strong It\^o--Taylor scheme for simulating SDE paths, and adaptively decreases the step-size in the numerical integration as the solution approaches the boundary of the domain. These techniques turn out to

Xiao Zang, Miao Yin, Lingyi Huang, Jingjin Yu

Neural network (NN)-based methods have emerged as an attractive approach for robot motion planning due to strong learning capabilities of NN models and their inherently high parallelism. Despite the current development in this direction, the efficient capture and processing of important sequential and spatial information, in a direct and simultaneous way, is

Nikhil Bansal, Haotian Jiang, Raghu Meka

We give a simple proof of the matrix Spencer conjecture up to poly-logarithmic rank: given symmetric $d \times d$ matrices $A_1,\ldots,A_n$ each with $\|A_i\|_{\mathsf{op}} \leq 1$ and rank at most $n/\log^3 n$, one can efficiently find $\pm 1$ signs $x_1,\ldots,x_n$ such that their signed sum has spectral norm $\|\sum_{i=1}^n x_i A_i\|_{\mathsf{op}} = O(\sq

Satoshi Kondo, Satoshi Kasai

To promote the development of medical image segmentation technology, AMOS, a large-scale abdominal multi-organ dataset for versatile medical image segmentation, is provided and AMOS 2022 challenge is held by using the dataset. In this report, we present our solution for the AMOS 2022 challenge. We employ residual U-Net with deep super vision as our base mode

Michael Bishop, Joey Contreras, Peter Martin, Douglas Singleton

The existence of a small, non-zero cosmological constant is one of the major puzzles in fundamental physics. Naively, quantum field theory arguments would imply a cosmological constant which is up to 10$^{120}$ times larger than the observed one. It is believed a comprehensive theory of quantum gravity would resolve this enormous mismatch between theory and

Si-Si Wang, Yan Yu, Ji-Huan Guan, Yi-Ming Dai

The real space formalism of orbital magnetization (OM) is an average of the local OM over some appropriate region of the system. Previous studies prefer a bulk average (i.e., without including boundaries). Based on a bilayer model with an adjustable Chern number at half filling, we numerically investigate the effects from boundaries on the real space express

Nithin Gopalakrishnan Nair, Kangfu Mei, Vishal M. Patel

Although many long-range imaging systems are designed to support extended vision applications, a natural obstacle to their operation is degradation due to atmospheric turbulence. Atmospheric turbulence causes significant degradation to image quality by introducing blur and geometric distortion. In recent years, various deep learning-based single image atmosp

Wei Chen, Jinglong Du, Zhao Zhang, Fuzhen Zhuang

Recently, some span-based methods have achieved encouraging performances for joint aspect-sentiment analysis, which first extract aspects (aspect extraction) by detecting aspect boundaries and then classify the span-level sentiments (sentiment classification). However, most existing approaches either sequentially extract task-specific features, leading to in

Joseph Aylett-Bullock, Miguel Luengo-Oroz

AI is being increasingly used to aid response efforts to humanitarian emergencies at multiple levels of decision-making. Such AI systems are generally understood to be stand-alone tools for decision support, with ethical assessments, guidelines and frameworks applied to them through this lens. However, as the prevalence of AI increases in this domain, such s

Shuowen Chen, Hiroaki Kaido

Economic models may exhibit incompleteness depending on whether or not they admit certain policy-relevant features such as strategic interaction, self-selection, or state dependence. We develop a novel test of model incompleteness and analyze its asymptotic properties. A key observation is that one can identify the least-favorable parametric model that repre

Setu Kumar Basak, Lorenzo Neil, Bradley Reaves, Laurie Williams

Throughout 2021, GitGuardian's monitoring of public GitHub repositories revealed a two-fold increase in the number of secrets (database credentials, API keys, and other credentials) exposed compared to 2020, accumulating more than six million secrets. A systematic derivation of practices for managing secrets can help practitioners in secure development. The

Mark Sellke

We consider a random Hamiltonian $H:\Sigma\to\mathbb R$ defined on a compact space $\Sigma$ that admits a transitive action by a compact group $\mathcal G$. When the law of $H$ is $\mathcal G$-invariant, we show its expected free energy relative to the unique $\mathcal G$-invariant probability measure on $\Sigma$ obeys a subadditivity property in the law of

Yawen Wu, Dewen Zeng, Zhepeng Wang, Yi Sheng

In dermatological disease diagnosis, the private data collected by mobile dermatology assistants exist on distributed mobile devices of patients. Federated learning (FL) can use decentralized data to train models while keeping data local. Existing FL methods assume all the data have labels. However, medical data often comes without full labels due to high la

Kiran S. Kedlaya

We complete the solution of the relative class number one problem for function fields of curves over finite fields. Using work from two earlier papers, this reduces to finding all function fields of genus 6 or 7 over $\mathbb{F}_2$ with one of 40 prescribed Weil polynomials; one may then verify directly that three of these fields admit an everywhere unramifi

Yushan Li, Jianping He, Cailian Chen, Xinping Guan

Topology inference for networked dynamical systems (NDSs) has received considerable attention in recent years. The majority of pioneering works have dealt with inferring the topology from abundant observations of NDSs, so as to approximate the real one asymptotically. Leveraging the characteristic that NDSs will react to various disturbances and the disturba

Sariel Har-Peled, Da Wei Zheng

$\newcommand{\Arr}{\mathcal{A}} \newcommand{\numS}{k} \newcommand{\ArrX}[1]{\Arr(#1)} \newcommand{\eps}{\varepsilon} \newcommand{\opt}{\mathsf{o}}$ For point sets $P_1, \ldots, P_\numS$, a set of lines $L$ is halving if any face of the arrangement $\ArrX{L}$ contains at most $|P_i|/2$ points of $P_i$, for all $i$. We study the problem of computing a halving

Fan Hu, Yanlin Wang, Lun Du, Xirong Li

With a good code search engine, developers can reuse existing code snippets and accelerate software development process. Current code search methods can be divided into two categories: traditional information retrieval (IR) based and deep learning (DL) based approaches. DL-based approaches include the cross-encoder paradigm and the bi-encoder paradigm. Howev

Minduli C. Wijayatunga, Roberto Armellin, Laura Pirovano

This note develops easily applicable techniques that improve the convergence and reduce the computational time of indirect low thrust trajectory optimization when solving fuel- and time-optimal problems. For solving fuel optimal (FO) problems, a positive scaling factor -- $\Gamma_{TR}$ -- is introduced based on the energy optimal (EO) solution to establish a

Naoyuki Kamiyama

We consider a many-to-one variant of the stable matching problem. More concretely, we consider the variant of the stable matching problem where one side has a matroid constraint. Furthermore, we consider the situation where the preference of each agent may contain ties. In this setting, we consider the problem of checking the existence of a strongly stable m

Fan Hu, Yanlin Wang, Lun Du, Hongyu Zhang

Code search with natural language helps us reuse existing code snippets. Thanks to the Transformer-based pretraining models, the performance of code search has been improved significantly. However, due to the quadratic complexity of multi-head self-attention, there is a limit on the input token length. For efficient training on standard GPUs like V100, exist

Rakpong Kaewpuang, Minrui Xu, Dusit Niyato, Han Yu

Increasing privacy and security concerns in intelligence-native 6G networks require quantum key distribution-secured federated learning (QKD-FL), in which data owners connected via quantum channels can train an FL global model collaboratively without exposing their local datasets. To facilitate QKD-FL, the architectural design and routing management framewor

Yuanlong Liang, Xianjun Huang, Jisheng Pan, Wencong Liu

While functional materials with both light transmitting and electromagnetic shielding are highly desirable, only very few of them meet the stringent electromagnetic interference (EMI) shielding criteria for optoelectronic systems. Here, a design strategy of shorted micro-waveguides (SMWs) array to decouple the light transmission and EMI shielding is proposed

Ehab ElSalamouny, Catuscia Palamidessi

The local privacy mechanisms, such as k-RR, RAPPOR, and the geo-indistinguishability ones, have become quite popular thanks to the fact that the obfuscation can be effectuated at the users end, thus avoiding the need of a trusted third party. Another important advantage is that each data point is sanitized independently from the others, and therefore differe

Xinyu Zhu, Yongliang Shen, Weiming Lu

Concomitant administration of drugs can cause drug-drug interactions (DDIs). Some drug combinations are beneficial, but other ones may cause negative effects which are previously unrecorded. Previous works on DDI prediction usually rely on hand-engineered domain knowledge, which is laborious to obtain. In this work, we propose a novel model, Molecular Substr

Xiaofan Yu, Yunhui Guo, Sicun Gao, Tajana Rosing

Unsupervised lifelong learning refers to the ability to learn over time while memorizing previous patterns without supervision. Although great progress has been made in this direction, existing work often assumes strong prior knowledge about the incoming data (e.g., knowing the class boundaries), which can be impossible to obtain in complex and unpredictable

Pietro Zanin, Nestor Caticha

We study the interaction of agents, where each one consists of an associative memory neural network trained with the same memory patterns and possibly different reinforcement-unlearning dreaming periods. Using replica methods, we obtain the rich equilibrium phase diagram of the coupled agents. It shows phases such as the student-professor phase, where only o

Shahroz Tariq, Binh M. Le, Simon S. Woo

Time series anomaly detection is extensively studied in statistics, economics, and computer science. Over the years, numerous methods have been proposed for time series anomaly detection using deep learning-based methods. Many of these methods demonstrate state-of-the-art performance on benchmark datasets, giving the false impression that these systems are r

Jieru Feng, Jianliang Wu, Fan Yang

For a planar graph $G$, Borodin stated that $G$ is $(\Delta+1)$-edge-choosable if $\Delta \geq9$ and later Bonamy showed that $G$ is $9$-edge-choosable if $\Delta=8$. At the same time, Borodin et al. proved that $G$ is $\Delta$-edge-choosable if $\Delta\geq12$. In the paper, we extend these results to $K_5$-minor free graphs.

Lyuyang Tong

Optimal experimental design is an essential subfield of statistics that maximizes the chances of experimental success. The D- and A-optimal design is a very challenging problem in the field of optimal design, namely minimizing the determinant and trace of the inverse Fisher information matrix. Due to the flexibility and ease of implementation, traditional ev

Subhayan Roychoudhury, David Prendergast

X-ray absorption spectroscopy (XAS) is an explicit probe of the unoccupied electronic structure of materials and an invaluable tool for fingerprinting various electronic properties and phenomena. Computational methods capable of simulating and analysing such spectra are therefore in high demand for complementing the experimental results and for extracting va

Lucas Braune, Taro Yoshino

We obtain a lower bound of the degree of irrationality of very general complete intersections over the complex field from the recent results of the first author and Chen--Stapleton. For combining these results, we make a minor adjustment of Chen--Stapleton's method using the trace map of differential modules.

Takahiro Murotani

Although the analogue of the theorem of Neukirch-Uchida for $p$-adic local fields fails to hold as it is, Mochizuki proved a certain analogue of this theorem for the absolute Galois groups with ramification filtrations of $p$-adic local fields. Moreover, Mochizuki and Hoshi gave various (necessary and) sufficient conditions for homomorphisms between the abso

Wonhui Park, Dongkwon Jin, Chang-Su Kim

Eigencontours are the first data-driven contour descriptors based on singular value decomposition. Based on the implementation of ESE-Seg, eigencontours were applied to the instance segmentation task successfully. In this report, we incorporate eigencontours into the PolarMask network for instance segmentation. Experimental results demonstrate that the propo

Yuchen Liu, Zhixin Shu, Yijun Li, Zhe Lin

3D-controllable portrait synthesis has significantly advanced, thanks to breakthroughs in generative adversarial networks (GANs). However, it is still challenging to manipulate existing face images with precise 3D control. While concatenating GAN inversion and a 3D-aware, noise-to-image GAN is a straight-forward solution, it is inefficient and may lead to no

Yuri Nikolayevsky, Joseph A. Wolf

The geodesic orbit property is useful and interesting in Riemannian geometry. It implies homogeneity and has important classes of Riemannian manifolds as special cases. Those classes include weakly symmetric Riemannian manifolds and naturally reductive Riemannian manifolds. The corresponding results for indefinite metric manifolds are much more delicate than