November 2022 arXiv papers — page 146

Adrita Chanda, Adrija Aich, Arka Sanyal, Anantika Chandra

The severe acute respiratory syndrome coronavirus 2 outbreak in Chinas Hubei area in late 2019 has now created a global pandemic that has spread to over 150 countries. In most people, COVID 19 is a respiratory infection that produces fever, cough, and shortness of breath. Patients with severe COVID 19 may develop ARDS. MSCs can come from a number of places,

Mohamad Abed El Rahman Hammoud, Olivier LeMaitre, Edriss S. Titi, Ibrahim Hoteit

Obtaining accurate high-resolution representations of model outputs is essential to describe the system dynamics. In general, however, only spatially- and temporally-coarse observations of the system states are available. These observations can also be corrupted by noise. Downscaling is a process/scheme in which one uses coarse scale observations to reconstr

Masanori Hino

We discuss quantitative estimates of the local spectral dimension of the two-dimensional Sierpinski gasket. The present arguments were inspired by a previous study of the distribution of the Kusuoka measure by R. Bell, C.-W. Ho, and R. S. Strichartz [Energy measures of harmonic functions on the Sierpi\'nski gasket, Indiana Univ. Math. J. 63 (2014), 831-868].

Anushikha Ghosh, Arka Sanyal, Sameer Sharma

The Zika virus, is an emerging infectious disease causing severe complications such as microcephaly in infants and Guillain Barre syndrome in adults. There is no licensed vaccination or approved medicine to treat ZIKV infection. Therefore, extensive research is being carried out to find compounds that can be used effectively as therapeutic molecules to treat

H. B. Kim, D. H. Ha, E. J. Jeon, J. A. Jeon

AMoRE is an international project to search for the neutrinoless double beta decay of $^{100}$Mo using a detection technology consisting of magnetic microcalorimeters (MMCs) and molybdenum-based scintillating crystals. Data collection has begun for the current AMORE-I phase of the project, an upgrade from the previous pilot phase. AMoRE-I employs thirteen $^

Zhiding Liu, Mingyue Cheng, Zhi Li, Qi Liu

Deep learning has brought significant breakthroughs in sequential recommendation (SR) for capturing dynamic user interests. A series of recent research revealed that models with more parameters usually achieve optimal performance for SR tasks, inevitably resulting in great challenges for deploying them in real systems. Following the simple assumption that li

B. Ailawadhi, R. Dastidar, K. Misra, R. Roy

We present high-cadence photometric and spectroscopic observations of SN~2020jfo in ultraviolet and optical/near-infrared bands starting from $\sim 3$ to $\sim 434$ days after the explosion, including the earliest data with the 10.4\,m GTC. SN~2020jfo is a hydrogen-rich Type II SN with a relatively short plateau duration ($67.0 \pm 0.6$ days). When compared

Shin'ichi Nojiri, Sergei D. Odintsov, Tanmoy Paul

In the realm of the Bekenstein-Hawking entropy, the thermodynamics of apparent horizon bridges with the usual FLRW (Friedmann-Lema\^{i}tre-Robertson-Walker) equation only for a special case where the matter field is given by a perfect fluid having equation of state (EoS) parameter $= -1$, i.e $p = -\rho$ with $\rho$ and $p$ represent the energy density and t

Abdulla Rakhimov, Asliddin Khudoyberdiev

Using a theoretical field Gaussian approximation we have studied Rabi coupled binary Bose system at low temperatures. We have derived extended Hugenholtz - Pines relations taking into account one body interaction (e.g. Rabi coupling) and studied the critical temperature $T_c$ of Bose-Einstein condensate transition. We have shown that, the shift of $T_c$ due

Nanqing Dong, Jiahao Sun, Zhipeng Wang, Shuoying Zhang

Federated learning (FL) is a promising way to allow multiple data owners (clients) to collaboratively train machine learning models without compromising data privacy. Yet, existing FL solutions usually rely on a centralized aggregator for model weight aggregation, while assuming clients are honest. Even if data privacy can still be preserved, the problem of

Cam Le, Lam Pham, Nghia NVN, Truong Nguyen

In this paper, we present a robust and low complexity deep learning model for Remote Sensing Image Classification (RSIC), the task of identifying the scene of a remote sensing image. In particular, we firstly evaluate different low complexity and benchmark deep neural networks: MobileNetV1, MobileNetV2, NASNetMobile, and EfficientNetB0, which present the num

Chongyu Wang, Mingyu Yan, Kaiyuan Pang, Fushuan Wen

This paper proposes a post-disaster cyber-physical interdependent restoration scheduling (CPIRS) framework for active distribution networks (ADN) where the simultaneous damages on cyber and physical networks are considered. The ad hoc wireless device-to-device (D2D) communication is leveraged, for the first time, to establish cyber networks instantly after t

Daniel W. Cranston, Chun-Hung Liu

A proper coloring of a graph is \emph{conflict-free} if, for every non-isolated vertex, some color is used exactly once on its neighborhood. Caro, Petru\v{s}evski, and \v{S}krekovski proved that every graph $G$ has a proper conflict-free coloring with at most $5\Delta(G)/2$ colors and conjectured that $\Delta(G)+1$ colors suffice for every connected graph $G

Harsha Yelchuri, Rashmi R

In this current technological world, the application of machine learning is becoming ubiquitous. Incorporating machine learning algorithms on extremely low-power and inexpensive embedded devices at the edge level is now possible due to the combination of the Internet of Things (IoT) and edge computing. To estimate an outcome, traditional machine learning dem

Hanming Liu

In this expository article we present Rosenlicht's work on geometric class field theory, which classifies abelian coverings of smooth, projective, geometrically connected curves over perfect fields.

Xiaobin Tian, Zequn Sun, Guangyao Li, Wei Hu

Entity alignment is to find identical entities in different knowledge graphs (KGs) that refer to the same real-world object. Embedding-based entity alignment techniques have been drawing a lot of attention recently because they can help solve the issue of symbolic heterogeneity in different KGs. However, in this paper, we show that the progress made in the p

Zihui Gu, Ju Fan, Nan Tang, Preslav Nakov

Fact verification has attracted a lot of research attention recently, e.g., in journalism, marketing, and policymaking, as misinformation and disinformation online can sway one's opinion and affect one's actions. While fact-checking is a hard task in general, in many cases, false statements can be easily debunked based on analytics over tables with reliable

Be'eri Greenfeld, Efim Zelmanov

We construct finitely generated nil algebras with prescribed growth rate. In particular, any increasing submultiplicative function is realized as the growth function of a nil algebra up to a polynomial error term and an arbitrarily slow distortion. We then move on to examples of nil algebras and domains with strongly oscillating growth functions and construc

Huiyang Xu, Cece Li

In this paper, we study locally strongly convex affine hypersurfaces with vanishing Weyl curvature tensor and semi-parallel cubic form relative to the Levi-Civita connection of affine metric. As the main result, we classify such hypersurfaces being not of flat affine metric. In particular, $2, 3$-dimensional locally strongly convex affine hypersurfaces with

Shao-Long Chen, Yu-Qi Xiao

We study the systematic decomposition of the dimension nine neutron-antineutron oscillation operators at tree and one-loop levels. We discuss the topologies' generation and the assignment of the chiral quarks. The completed lists of the decompositions are provided. We furthermore show an example that the neutron-antineutron oscillation occurs at one-loop lev

Hannaneh B. Pasandi, Haniyeh B. Pasandi

Automatic speech recognition (ASR) meets more informal and free-form input data as voice user interfaces and conversational agents such as the voice assistants such as Alexa, Google Home, etc., gain popularity. Conversational speech is both the most difficult and environmentally relevant sort of data for speech recognition. In this paper, we take a linguisti

Shaojie Min, Ji Liu

Analytical explorations on complex networks and cubes (i.e., multi-dimensional datasets) are currently two separate research fields with different strategies. To gain more insights into cube dynamics via unique network-domain methodologies and to obtain abundant synthetic networks, we need a transformation approach from cubes into associated networks. To thi

Mobashir Sadat, Cornelia Caragea

Automatic topic classification has been studied extensively to assist managing and indexing scientific documents in a digital collection. With the large number of topics being available in recent years, it has become necessary to arrange them in a hierarchy. Therefore, the automatic classification systems need to be able to classify the documents hierarchica

Peidong Wang, Eric Sun, Jian Xue, Yu Wu

Automatic speech recognition (ASR) and speech translation (ST) can both use neural transducers as the model structure. It is thus possible to use a single transducer model to perform both tasks. In real-world applications, such joint ASR and ST models may need to be streaming and do not require source language identification (i.e. language-agnostic). In this

Farbod Shafiei, Massoud R. Masir, Tommaso Orzali, Alexey Vert

In disordered media light can be localized in the spaces between scattering sites which average to an optical mean free path (MFP). However the fundamental question of the smallest MFP that can support Anderson localization of light remains unanswered due to fabrication complexity of a scattering medium with controlled nano-scale gaps and lack of required re

Chenlei Lv, Weisi Lin, Baoquan Zhao

Point cloud registration is a popular topic which has been widely used in 3D model reconstruction, location, and retrieval. In this paper, we propose a new registration method, KSS-ICP, to address the rigid registration task in Kendall shape space (KSS) with Iterative Closest Point (ICP). The KSS is a quotient space that removes influences of translations, s

Jing Wang, Qiang Cai, Guiwu Wei, Ningna Liao

The Interval-valued intuitionistic fuzzy sets (IVIFSs) based on the intuitionistic fuzzy sets combines the classical decision method is in its research and application is attracting attention. After comparative analysis, there are multiple classical methods with IVIFSs information have been applied into many practical issues. In this paper, we extended the c

Mingxin Wang

This paper focus on the diffusive eco-epidemiological prey-predator model with infectious diseases in prey, and with the homogeneous Neumann and Dirichlet boundary conditions, respectively. When boundary conditions are homogeneous Neumann boundary conditions, we give a complete conclusion about the stabilities of nonnegative constant equilibrium solutions. T

Natanael Alpay, Peter Jipsen, Melissa Sugimoto

A distributive lattice-ordered magma ($d\ell$-magma) $(A,\wedge,\vee,\cdot)$ is a distributive lattice with a binary operation $\cdot$ that preserves joins in both arguments, and when $\cdot$ is associative then $(A,\vee,\cdot)$ is an idempotent semiring. A $d\ell$-magma with a top $\top$ is unary-determined if $x{\cdot} y=(x{\cdot}\!\top\wedge y)$ $\vee(x\w

Jong-hyoung Kim, Lishuai Jin, Benjamin C. Schafer, Quan Jiao

We introduce a class of ultra-light and ultra-stiff sandwich panels designed for use in photophoretic levitation applications and investigate their mechanical behavior using both computational analyses and micro-mechanical testing. The sandwich panels consist of two face sheets connected with a core that consists of hollow cylindrical ligaments arranged in a

Ningning Han, Juan Nie, Jian Lu, Michael K. Ng

We develop an efficient stochastic variance reduced gradient descent algorithm to solve the affine rank minimization problem consists of finding a matrix of minimum rank from linear measurements. The proposed algorithm as a stochastic gradient descent strategy enjoys a more favorable complexity than full gradients. It also reduces the variance of the stochas

Yun Tang, Lulu Cheng, Wanli Lyv, Zhaoxia Yin

Reversible data hiding in encrypted domain(RDH-ED) can not only protect the privacy of 3D mesh models and embed additional data, but also recover original models and extract additional data losslessly. However, due to the insufficient use of model topology, the existing methods have not achieved satisfactory results in terms of embedding capacity. To further

Andresa Campos, Simon Samuroff, Rachel Mandelbaum

In cosmology, we routinely choose between models to describe our data, and can incur biases due to insufficient models or lose constraining power with overly complex models. In this paper we propose an empirical approach to model selection that explicitly balances parameter bias against model complexity. Our method uses synthetic data to calibrate the relati

Saurav K. Aryal, Teanna Barrett, Gloria Washington

The human ear is generally universal, collectible, distinct, and permanent. Ear-based biometric recognition is a niche and recent approach that is being explored. For any ear-based biometric algorithm to perform well, ear detection and segmentation need to be accurately performed. While significant work has been done in existing literature for bounding boxes

Yu Yang, Wing Yin Cheung, Chang Liu, Xiangyang Ji

Multiview self-supervised representation learning roots in exploring semantic consistency across data of complex intra-class variation. Such variation is not directly accessible and therefore simulated by data augmentations. However, commonly adopted augmentations are handcrafted and limited to simple geometrical and color changes, which are unable to cover

X. Zhang, W. Lin, J. M. Yao, C. F. Jiao

The generator coordinate method (GCM) is an important tool of choice for modeling large-amplitude collective motion in atomic nuclei. The computational complexity of the GCM increases rapidly with the number of collective coordinates. It imposes a strong restriction on the applicability of the method. In this work, we propose a subspace-reduction algorithm t

Mario I. Molina

We study the spectral stability of a 2D discrete Schr\"{o}dinger equation on a square lattice, in the simultaneous presence of a fractional Laplacian and $\cal{PT}$ symmetry. For that purpose, we compute the plane-wave spectrum in closed form, as a function of the gain/loss parameter and the fractional exponent. Examination of the spectrum reveals that an in

Davar Khoshnevisan, Kunwoo Kim, Carl Mueller

We consider a generalization of the parabolic Anderson model driven by space-time white noise, also called the stochastic heat equation, on the real line. High peaks of solutions have been extensively studied under the name of intermittency, but less is known about spatial regions between peaks, which may loosely refer to as valleys. We present two results a

Hongkai Chen, Scott A. Smolka, Nicola Paoletti, Shan Lin

We present ResilienC, a framework for resilient control of Cyber-Physical Systems subject to STL-based requirements. ResilienC utilizes a recently developed formalism for specifying CPS resiliency in terms of sets of $(\mathit{rec},\mathit{dur})$ real-valued pairs, where $\mathit{rec}$ represents the system's capability to rapidly recover from a property vio

Nariya Kawazumi, Arthur Soulié

We compute the stable cohomology groups of the mapping class groups of compact orientable surfaces with one boundary, with twisted coefficients given by the homology of the unit tangent bundle of the surface. This stable twisted cohomology is not free as a module over the stable cohomology algebra with constant coefficients. In fact, it is out of the scope o

Danilo Amigo, Felipe Lepe, Gonzalo Rivera

In this paper we analyze a virtual element method for the two dimensional elasticity problem allowing small edges. With this approach, the classic assumptions on the geometrical features of the polygonal meshes can be relaxed. In particular, we consider only star-shaped polygons for the meshes. Suitable error estimates are presented, where a rigorous analysi

Haichao Zhang, Jiashi Li, Xin Xia, Kuangrong Hao

Recently, Neural architecture search has achieved great success on classification tasks for mobile devices. The backbone network for object detection is usually obtained on the image classification task. However, the architecture which is searched through the classification task is sub-optimal because of the gap between the task of image and object detection

Emer Lopera, Camila López, Raúl E. Vidal

In this paper we prove the existence of at least one positive solution for the nonlocal semipositone problem \[ \displaystyle \left\{\begin{array}{rcll} (-\Delta)_p^s(u) &=& \lambda f(u) \qquad & \text{in} \ \ \Omega \\u &=& 0 & \text{in} \ \ \mathbb{R}^N -\Omega , \end{array}\right. \] whenever $\lambda >0$ is a sufficiently small parameter. Here $\Omega \s

Amogh Subbakrishna Adishesha, Lily Jakielaszek, Fariha Azhar, Peixuan Zhang

The increasing reliance on online communities for healthcare information by patients and caregivers has led to the increase in the spread of misinformation, or subjective, anecdotal and inaccurate or non-specific recommendations, which, if acted on, could cause serious harm to the patients. Hence, there is an urgent need to connect users with accurate and ta

Evan J. Telford, Daniel G. Chica, Kaichen Xie, Nicholas S. Manganaro

The ability to control magnetic properties of materials is crucial for fundamental research and underpins many information technologies. In this context, two-dimensional materials are a particularly exciting platform due to their high degree of tunability and ease of implementation into nanoscale devices. Here we report two approaches for manipulating the A-

Evgeni Dimitrov, Anushka Murthy

We consider the asymmetric simple exclusion process (ASEP) with half-flat initial condition. We show that the one-point marginals of the ASEP height function are described by those of the $\mbox{Airy}_{2 \rightarrow 1}$ process, introduced by Borodin-Ferrari-Sasamoto in (Commun. Pure Appl. Math., 61, 1603-1629, 2008). This result was conjectured by Ortmann-Q

Jiawei Zhang

In this article, we plan to provide an introduction about some basics about robots for readers. Several key topics of classic robotics will be introduced, including robot representation, robot rotational motion, coordinates transformation and velocity transformation. By now, classic rigid-body robot analysis is still the main-stream approach in robot control

Marco Radici, Silvia Dalla Torre, Daria Sokhan

This document is submitted as input to the NuPECC Long Range Plan 2024 by three European members of the EIC Users Group Steering Committee (Vice Chair, one at-large member, and the EU Representative). We submit the document on behalf of the international EIC Users Group (EICUG) community, but we specifically represent 335 European members of the EICUG (25%)

Changwon Jang, Kiseung Bang, Minseok Chae, Byoungho Lee

We present a novel near-eye display concept which consists of a waveguide combiner, a spatial light modulator, and a laser light source. The proposed system can display true 3D holographic images through see-through pupil-replicating waveguide combiner as well as providing a large eye-box. By modeling the coherent light interaction inside of the waveguide co

Xin Zhang, Iván Vallés-Pérez, Andreas Stolcke, Chengzhu Yu

Stuttering is a speech disorder where the natural flow of speech is interrupted by blocks, repetitions or prolongations of syllables, words and phrases. The majority of existing automatic speech recognition (ASR) interfaces perform poorly on utterances with stutter, mainly due to lack of matched training data. Synthesis of speech with stutter thus presents a

Chanhyun Pak, Matthew J. Schlitters, Scott D. Bergeson

We report new frequency-comb-based measurements of Ca Rydberg energy levels. Counter-propagating laser beams at 390 nm and 423 nm excite Ca atoms from the $4s^2~^1\mbox{S}_0$ ground state to $4sns~^1\mbox{S}_0$ Rydberg levels with $n$ ranging from 40 to 110. Near-resonant two-photon two-color excitation of atoms in a thermal beam makes it possible to elimina

Asha Yadav, Carlos Mera Acosta, Gustavo M. Dalpian, Oleksandr I. Malyi

The successful exfoliation of graphene from graphite has brought significant attention to predicting new two-dimensional (2D) materials that can be realized experimentally. As a consequence, first-principles studies of novel 2D materials become a routine, with thousands of papers published every year. What makes these studies interesting is that they predict

Yuanxing Chen, Qingzhao Zhang, Shuangge Ma, Kuangnan Fang

In diverse fields ranging from finance to omics, it is increasingly common that data is distributed and with multiple individual sources (referred to as ``clients'' in some studies). Integrating raw data, although powerful, is often not feasible, for example, when there are considerations on privacy protection. Distributed learning techniques have been devel

Annika Fürnsinn, Christian Ebenbauer, Bahman Gharesifard

We present a novel nonlinear model predictive control (MPC) scheme with relaxed stability criteria, based on the idea of generalized discrete-time control Lyapunov functions. These functions need to satisfy an average descent over a finite window of time, rather than a descent at every time step. One feature of this scheme is that it allows for implementing

Oscar Jarrín

We consider two elliptic coupled systems of relevance in the fluid dynamics. These systems are posed on the whole three-dimensional space and they consider the action of external forces. The first system deals with the simplified Ericksen-Leslie (SEL) system, which describes the dynamics of liquid crystal flows. The second system is the time-independent magn

Taejoo Ahn, Licong Lin, Song Mei

In high dimensional variable selection problems, statisticians often seek to design multiple testing procedures that control the False Discovery Rate (FDR), while concurrently identifying a greater number of relevant variables. Model-X methods, such as Knockoffs and conditional randomization tests, achieve the primary goal of finite-sample FDR control, assum

Martin Borchert, Dieter Engel, Clemens von Korff Schmising, Bastian Pfau

Time-resolved x-ray magnetic circular dichroism (XMCD) enables a unique spectroscopic view on complex spin and charge dynamics in multi-elemental magnetic materials. So far, its application in the soft-x-ray range has been limited to synchrotron-radiation sources and free-electron lasers. By combining a laser-driven plasma source with a magnetic thin-film po

Pallav Kumar Bera, Vajendra Kumar, Samita Rani Pani, Vivek Bargate

This article presents differential protection of the distribution line connecting a wind farm in a microgrid. Machine Learning (ML) based models are built using differential features extracted from currents at both ends of the line to assist in relaying decisions. Wavelet coefficients obtained after feature selection from an extensive list of features are us

Bruno M. Braga, Ilijas Farah, Alessandro Vignati

The rigidity problem for uniform Roe algebras was recently positively solved. Before its solution was found, there were positive solutions under the assumption of certain technical geometric conditions. In this paper, we introduce weaker versions of the operator norm localization property (ONL) which turn out to characterize those technical geometric conditi

Jesse Campion Loth

We are interested in the distribution of the number of faces across all the $2-$cell embeddings of a graph, which is equivalent to the distribution of genus by Euler's formula. In order to study this distribution, we consider the local distribution of faces at a single vertex. We show an asymptotic uniformity on this local face distribution which holds for a

Sefik Emre Eskimez, Takuya Yoshioka, Alex Ju, Min Tang

Personalized speech enhancement (PSE) is a real-time SE approach utilizing a speaker embedding of a target person to remove background noise, reverberation, and interfering voices. To deploy a PSE model for full duplex communications, the model must be combined with acoustic echo cancellation (AEC), although such a combination has been less explored. This pa

Sumaia Mohammed AL-Ghuribi, Shahrul Azman Mohd Noah

The rapid growth of the internet has increased the number of online texts. This led to the rapid growth of the number of online texts in the Arabic language. The enormous amount of text must be organized into classes to make the analysis process and text retrieval easier. Text classification is, therefore, a key component of text mining. There are numerous s

Laura B. Balzer, Theodore Ruel, Diane V. Havlir, the SEARCH-Youth Study Team

This document provides the statistical analytic plan (SAP) for evaluating health outcomes in the SEARCH-Youth study, a cluster randomized trial designed to evaluate the effect of a combination intervention on HIV viral suppression among adolescents and young adults with HIV in rural Uganda and Kenya (Clinicaltrials.gov: NCT03848728). The SAP was locked prior

Vasyl Pihur

From the Publisher:Software is a commodity being sold across diverse language and cultural groups, whether in the commercial marketplace, or as customized applications. Developers must structure their applications so that they can be readily and cheaply localized for sale in this range of markets. Obvious differences such as scripts and languages must be und

Meng Han, Jia-bao Ji, Kiyoshi Ueda, Hans Jakob Wörner

Attosecond metrology with linearly polarized light pulses is the basis of a highly successful research area. An even broader impact can be expected from a generalized metrology that covers two-dimensional polarization states, enabling notably the study of chiroptical phenomena on the electronic time scale. Here, we introduce and demonstrate a comprehensive a

Beichen Zhang, Fatima K. Abu Salem, Michael J. Hayes, Tsegaye Tadesse

Under climate change, the increasing frequency, intensity, and spatial extent of drought events lead to higher socio-economic costs. However, the relationships between the hydro-meteorological indicators and drought impacts are not identified well yet because of the complexity and data scarcity. In this paper, we proposed a framework based on the extreme gra

Vasyl Pihur, Scott Thompson

About 50% of all queries on Snapchat app are targeted at finding the right friend to interact with. Since everyone has a unique list of friends and that list is not very large (maximum a few thousand), it makes sense to perform this search locally, on users' devices. In addition, the friend list is already available for other purposes, such as showing the ch

Okba Bekhelifi, Nasr-Eddine Berrached

Speeding up the spelling in event-related potentials (ERP) based Brain-Computer Interfaces (BCI) requires eliciting strong brain responses in a short span of time, as much as the accurate classification of such evoked potentials remains challenging and imposes hard constraints for signal processing and machine learning techniques. Recent advances in stimulus

I. Karafiátová, J. Møller, Z. Pawlas, J. Staněk

The description of distributions related to grain microstructure helps physicists to understand the processes in materials and their properties. This paper presents a general statistical methodology for the analysis of crystallographic orientations of grains in a 3D Laguerre tessellation dataset which represents the microstructure of a polycrystalline materi

Yiqian Wu, Jip Kim, James Anderson

Market power exercise in the electricity markets distorts market prices and diminishes social welfare. Many markets have implemented market power mitigation processes to eliminate the impact of such behavior. The design of mitigation mechanisms has a direct influence on investors' profitability and thus mid-/long-term resource adequacy. In order to evaluate

Ehsan Amid, Richard Nock, Manfred Warmuth

The link with exponential families has allowed $k$-means clustering to be generalized to a wide variety of data generating distributions in exponential families and clustering distortions among Bregman divergences. Getting the framework to work above exponential families is important to lift roadblocks like the lack of robustness of some population minimizer

Yiming Xing, Georgios Fellouris

A signal recovery problem is considered, where the same binary testing problem is posed over multiple, independent data streams. The goal is to identify all signals, i.e., streams where the alternative hypothesis is correct, and noises, i.e., streams where the null hypothesis is correct, subject to prescribed bounds on the classical or generalized familywise

Mizu Nishikawa-Toomey, Tristan Deleu, Jithendaraa Subramanian, Yoshua Bengio

Bayesian causal structure learning aims to learn a posterior distribution over directed acyclic graphs (DAGs), and the mechanisms that define the relationship between parent and child variables. By taking a Bayesian approach, it is possible to reason about the uncertainty of the causal model. The notion of modelling the uncertainty over models is particularl

Isaac Grosof, Ziv Scully, Mor Harchol-Balter, Alan Scheller-Wolf

Multiserver-job systems, where jobs require concurrent service at many servers, occur widely in practice. Essentially all of the theoretical work on multiserver-job systems focuses on maximizing utilization, with almost nothing known about mean response time. In simpler settings, such as various known-size single-server-job settings, minimizing mean response

Akash Jena

Let $G$ be a $p$-adic Lie group with reductive Lie algebra $\mathfrak{g}$. Denote by $D(G)$ the locally analytic distribution algebra of $G$. Orlik-Strauch and Agrawal-Strauch have studied certain exact functors defined on various categories of $\mathfrak{g}$-representations with image in the category of locally analytic $G$-representations or $D(G)$-modules

David Rapado Rincon, Eldert J. van Henten, Gert Kootstra

The ability to accurately represent and localise relevant objects is essential for robots to carry out tasks effectively. Traditional approaches, where robots simply capture an image, process that image to take an action, and then forget the information, have proven to struggle in the presence of occlusions. Methods using multi-view perception, which have th

Emily Halina, Matthew Guzdial

In fighting games, individual players of the same skill level often exhibit distinct strategies from one another through their gameplay. Despite this, the majority of AI agents for fighting games have only a single strategy for each "level" of difficulty. To make AI opponents more human-like, we'd ideally like to see multiple different strategies at each lev

Esteban Cárdenas, Nataša Pavlović, William Warner

In this work, we generalize M. Kac's original many-particle binary stochastic model to derive a space homogeneous Boltzmann equation that includes a linear combination of higher-order collisional terms. First, we prove an abstract theorem about convergence from a finite hierarchy to an infinite hierarchy of coupled equations. We apply this convergence theore

Liet Vo

In this paper, we propose a new approach for the time-discretization of the incompressible stochastic Stokes equations with multiplicative noise. Our new strategy is based on the classical Milstein method from stochastic differential equations. We use the energy method for its error analysis and show a strong convergence order of at most $1$ for both velocit

ChunJun Cao, Brad Lackey

We examine the use of weight enumerators for analyzing tensor network constructions, and specifically the quantum lego framework recently introduced. We extend the notion of quantum weight enumerators to so-called tensor enumerators, and prove that the trace operation on tensor networks is compatible with a trace operation on tensor enumerators. This allows

Simon Park

Whereas there are simple algorithms that are proven to be optimal for the Classical and the Multiple Choice Secretary Problem, the Matroid Secretary Problem is less thoroughly understood. This paper proposes the generalization of some simple algorithms from the Classical and Multiple Choice versions on the Matroid Secretary Problem. Out of two algorithms tha

Yushao Chen, Yin-Chen He, Aaron Szasz

We investigate the ground states of spin-$S$ Kitaev ladders using exact analytical solutions (for $S = 1/2$), perturbation theory, and the density matrix renormalization group (DMRG) method. We find an even-odd effect: in the case of half-integer $S$, we find phases with spontaneous symmetry breaking (SSB) and symmetry-protected topological (SPT) order; for

Apurva Gandhi, Yuki Asada, Victor Fu, Advitya Gemawat

Database engines have historically absorbed many of the innovations in data processing, adding features to process graph data, XML, object oriented, and text among many others. In this paper, we make the case that it is time to do the same for AI -- but with a twist! While existing approaches have tried to achieve this by integrating databases with external

Qiuting Chen

In this paper we study a class of discrete quantum walks, known as bipartite walks. These include the well-known Grover's walks. Any discrete quantum walk is given by the powers of a unitary matrix $U$ indexed by arcs or edges of the underlying graph. The walk is periodic if $U^k=I$ for some positive integer $k$. Kubota has given a characterization of period

B. A. R. Rocha, C. J. A. P. Martins

Mapping the expansion history of the universe is a compelling task of physical cosmology, especially in the context of the observational evidence for the recent acceleration of the universe, which demonstrates that canonical theories of cosmology and particle physics are incomplete and that there is new physics still to be discovered. Cosmography is a phenom

Brady Wu, Bryan VanSaders, Melody X. Lim, Heinrich M. Jaeger

The acoustic levitation of small particles provides a versatile platform to investigate the collective dynamical properties of self-assembled many-body systems in the presence of hydrodynamic coupling. However, acoustic scattering forces can only generate attractive interactions at close range in the levitation plane, limiting self-assembly to rafts where pa

Aldo V. Figallo, Aldo Figallo-Orellano, Martín Figallo

Baaz's operator $\Delta$ was introduced (by Baaz) in order to extend G\"odel logics, after that this operator was used to expand fuzzy logics by H\'ajek in his celebrated book. These logics were called $\Delta$-fuzzy logics. On the other hand, possibility operators were studied in the setting of \L ukasiewicz-Moisil algebras; curiously, one of these operator

Rui Yang, Samuel Bosch, Bobak Kiani, Seth Lloyd

Quantum machine learning has the potential to provide powerful algorithms for artificial intelligence. The pursuit of quantum advantage in quantum machine learning is an active area of research. For current noisy, intermediate-scale quantum (NISQ) computers, various quantum-classical hybrid algorithms have been proposed. One such previously proposed hybrid a

Jiayin Pan

The Grushin sphere is an almost-Riemannian manifold that degenerates along its equator. We construct a sequence of Riemannian metrics on a sphere $S^{m+n}$ with $Ric\ge 1$ such that its Gromov-Hausdorff limit is the $n$-dimensional Grushin hemisphere.

Pegah Azizi, Siddhartha Sarkar, Kai Sun, Stefano Gonella

Recent years have seen the discovery of systems featuring fragile topological states. These states of matter lack certain protection attributes typically associated with topology and are therefore characterized by weaker signatures that make them elusive to observe. Moreover, they are typically confined to special symmetry classes and, in general, rarely stu

Mahdi Mashkoori, Fariborz Parhizgar, Stephan Rachel, Annica M. Black-Schaffer

The robustness against local perturbations, as long as the symmetry of the system is preserved, is a distinctive feature of topological quantum states. Magnetic impurities and defects break time-reversal invariance and, consequently, time-reversal invariant (TRI) topological superconductors are fragile against this type of disorder. Non-magnetic impurities,

Jason Youn, Ilias Tagkopoulos

The ability of knowledge graphs to represent complex relationships at scale has led to their adoption for various needs including knowledge representation, question-answering, and recommendation systems. Knowledge graphs are often incomplete in the information they represent, necessitating the need for knowledge graph completion tasks. Pre-trained and fine-t

Eitan Sapiro-Gheiler

A principal and an agent face symmetric uncertainty about the value of two correlated projects for the agent. The principal chooses which project values to publicly discover and makes a proposal to the agent, who accepts if and only if the expected sum of values is positive. We characterize optimal discovery for various principal preferences: maximizing the

David Albrecht, Thomas Meissner

We develop an experimentally validated, short and easy-to-use survey module for measuring individual debt aversion. To this end, we first estimate debt aversion on an individual level, using choice data from Meissner and Albrecht (2022). This data also contains responses to a large set of debt aversion survey items, consisting of existing items from the lite

Michal Makowski, Jaroslaw Bomba, Antoni Frej, Mateusz Kolodziejczyk

Computer-generated holograms with their animated, three-dimensional appearance have long appealed to our imagination as the path towards truly immersive displays with bi-directional natural parallax. Impressive progress in updateable 3-D imagery has been achieved with liquid crystal modulators and high-resolution, but quasi-static holograms are being recorde

Valentin Churavy, William F Godoy, Carsten Bauer, Hendrik Ranocha

The Julia programming language has evolved into a modern alternative to fill existing gaps in scientific computing and data science applications. Julia leverages a unified and coordinated single-language and ecosystem paradigm and has a proven track record of achieving high performance without sacrificing user productivity. These aspects make Julia a viable

Mohamed-Ali Belabbas

We call a system super-linearizable if it admits finite-dimensional embedding as a linear system -- known as a finite-dimensional Koopman embedding; said otherwise, if its dynamics can be linearized by adding a finite set of observables. We introduce the notions of visible and hidden observables for such embeddings which, roughly speaking, are the observable

Kelechi Ogueji, Orevaoghene Ahia, Gbemileke Onilude, Sebastian Gehrmann

Multilingual models are often particularly dependent on scaling to generalize to a growing number of languages. Compression techniques are widely relied upon to reconcile the growth in model size with real world resource constraints, but compression can have a disparate effect on model performance for low-resource languages. It is thus crucial to understand

Kaustav Chakraborty, Somil Bansal

Machine learning driven image-based controllers allow robotic systems to take intelligent actions based on the visual feedback from their environment. Understanding when these controllers might lead to system safety violations is important for their integration in safety-critical applications and engineering corrective safety measures for the system. Existin

Nabaraj Pokhrel, Elizabeth A. Nowadnick

Several families of layered perovskite oxide ferroelectrics exhibit a coupling between polarization and structural order parameters, such as octahedral rotation distortions. This coupling provides opportunities for novel electric field-based manipulation of material properties, and also stabilizes complex domain patterns and domain wall vortices. Amongst lay