October 2022 arXiv papers — page 55

Julia Maddox

The standard definition of the dimension of a vector space or rank of a module states that dimension or rank is equal to the cardinality of any basis, which requires an understanding of the concepts of basis, generating set, and linear independence. We pose new definitions for the dimension of a vector space, called the isomorphic dimension, and for the rank

Zhixun Li, Dingshuo Chen, Qiang Liu, Shu Wu

Graph-based fraud detection has heretofore received considerable attention. Owning to the great success of Graph Neural Networks (GNNs), many approaches adopting GNNs for fraud detection has been gaining momentum. However, most existing methods are based on the strong inductive bias of homophily, which indicates that the context neighbors tend to have same l

Dilek Küçük, Fazli Can

This tutorial aims to cover the state-of-the-art on stance detection and address open research avenues for interested researchers and practitioners. Stance detection is a recent research topic where the stance towards a given target or target set is determined based on the given content and there are significant application opportunities of stance detection

Yixin Han, Xu Guo, Changliang Zou

Addressing the simultaneous identification of contributory variables while controlling the false discovery rate (FDR) in high-dimensional data is a crucial statistical challenge. In this paper, we propose a novel model-free variable selection procedure in sufficient dimension reduction framework via a data splitting technique. The variable selection problem

Chiyu Zhang, Xiaogang Xu, Lei Wang, Zaiyan Dai

Transformer's recent integration into style transfer leverages its proficiency in establishing long-range dependencies, albeit at the expense of attenuated local modeling. This paper introduces Strips Window Attention Transformer (S2WAT), a novel hierarchical vision transformer designed for style transfer. S2WAT employs attention computation in diverse windo

Ulrich J. Mohrhoff

In a recent note David Mermin attributed the idea that wave function collapse is a physical process to a misunderstanding of probability and the role it plays in quantum mechanics. There are, however, further misconceptions at play, some of which are shared by Mermin himself and more generally by QBists. The main objective of the present comment on his note

G. Pascoli

The existence of the flat rotation curves of galaxies is still perplexing. The dark matter paradigm was proposed long ago to solve this conundrum; however, this proposal is still under debate. In this paper, we search for universal relationships solely involving the baryonic density that incorporate both galactic dynamics and gravitational lensing in galaxy

David P. Jelenfi, Anita Schneiker, Attila Tajti, Gabor Magyarfalvi

Although H$_{2}$ is the simplest and the most abundant molecule in the Universe, its formation in the interstellar medium, especially in the photodissociation regions is far from being fully understood. According to suggestions, the formation of H$_{2}$ is catalyzed by polyaromatic hydrocarbons (PAHs) on the surface of interstellar grains. In the present stu

Vidhisha Balachandran, Hannaneh Hajishirzi, William W. Cohen, Yulia Tsvetkov

Abstractive summarization models often generate inconsistent summaries containing factual errors or hallucinated content. Recent works focus on correcting factual errors in generated summaries via post-editing. Such correction models are trained using adversarial non-factual summaries constructed using heuristic rules for injecting errors. However, generatin

Irshaad Ahmed, Alberto Fiorenza, Amiran Gogatishvili

We consider $K$-interpolation spaces involving slowly varying functions, and derive necessary and sufficient conditions for a Holmstedt-type formula to be held in the limiting case $\theta_0=\theta_1\in\{0,1\}.$ We also study the case $\theta_0=\theta_1\in (0,1).$ Applications are given to Lorentz-Karamata spaces, generalized gamma spaces and Besov spaces.

Rong Chen, Yidong Zhou

We say that a graph $G$ has an {\em odd $K_4$-subdivision} if some subgraph of $G$ is isomorphic to a $K_4$-subdivision and whose faces are all odd holes of $G$. For a number $\ell\geq 2$, let $\mathcal{G}_{\ell}$ denote the family of graphs which have girth $2\ell+1$ and have no odd hole with length greater than $2\ell+1$. Wu, Xu and Xu conjectured that eve

Marten Lienen, Stephan Günnemann

We introduce an ODE solver for the PyTorch ecosystem that can solve multiple ODEs in parallel independently from each other while achieving significant performance gains. Our implementation tracks each ODE's progress separately and is carefully optimized for GPUs and compatibility with PyTorch's JIT compiler. Its design lets researchers easily augment any as

Yilun Zhao, Linyong Nan, Zhenting Qi, Rui Zhang

Reasoning over tabular data requires both table structure understanding and a broad set of table reasoning skills. Current models with table-specific architectures and pre-training methods perform well on understanding table structures, but they still struggle with tasks that require various table reasoning skills. In this work, we develop ReasTAP to show th

Caesar Wu, Kotagiri Ramamohanarao, Rui Zhang, Pascal Bouvry

Strategic Decision-Making is always challenging because it is inherently uncertain, ambiguous, risky, and complex. It is the art of possibility. We develop a systematic taxonomy of decision-making frames that consists of 6 bases, 18 categorical, and 54 frames. We aim to lay out the computational foundation that is possible to capture a comprehensive landscap

Jose Luis Cercos-Pita, Pablo Eleazar Merino-Alonso, Javier Calderon-Sanchez, Daniel Duque

The choice of a time integration scheme is a crucial aspect of any transient fluid simulation, and Smoothed-Particle Hydrodynamics (SPH) is no exception. The influence of the time integration scheme on energy balance is here addressed. To do so, explicit expressions allowing to compute the deviations from the energy balance, induced by the time integration s

Matt Burnham

A tournament is a directed graph resulting from an orientation of the complete graph; so, if $M$ is a tournament's adjacency matrix, then $M + M^T$ is a matrix with $0$s on its diagonal and all other entries equal to $1$. An outstanding question in tournament theory asks to classify the adjacency matrices of tournaments which are singular (or nonsingular). W

Shai M. Chester, Éric Dupuis, William Witczak-Krempa

We give evidence for 3d bosonization in Conformal Field Theories (CFTs) by computing monopole operator scaling dimensions in 2+1 dimensional quantum electrodynamics (QED3) with Chern-Simons level $k$ and $N$ complex bosons in a large $N,k$ expansion. We first consider the $k=0$ case, where we show that scaling dimensions previously computed to subleading ord

Carlos Mougan, Klaus Broelemann, Gjergji Kasneci, Thanassis Tiropanis

As input data distributions evolve, the predictive performance of machine learning models tends to deteriorate. In the past, predictive performance was considered the key indicator to monitor. However, explanation aspects have come to attention within the last years. In this work, we investigate how model predictive performance and model explanation characte

Abbavaram Gowtham Reddy, Saloni Dash, Amit Sharma, Vineeth N Balasubramanian

A machine learning model, under the influence of observed or unobserved confounders in the training data, can learn spurious correlations and fail to generalize when deployed. For image classifiers, augmenting a training dataset using counterfactual examples has been empirically shown to break spurious correlations. However, the counterfactual generation tas

Wenhao Wu, Wei Li, Jiachen Liu, Xinyan Xiao

Though model robustness has been extensively studied in language understanding, the robustness of Seq2Seq generation remains understudied. In this paper, we conduct the first quantitative analysis on the robustness of pre-trained Seq2Seq models. We find that even current SOTA pre-trained Seq2Seq model (BART) is still vulnerable, which leads to significant de

Nicolas Valade, Simon Thalabard, Jeremie Bec

Surface quasi geostrophy (SQG) describes the two-dimensional active transport of a temperature field in a strongly stratified and rotating environment. Besides its relevance to geophysics, SQG bears formal resemblance with various flows of interest for turbulence studies, from passive scalar and Burgers to incompressible fluids in two and three dimensions. T

Phillip Howard, Gadi Singer, Vasudev Lal, Yejin Choi

While counterfactual data augmentation offers a promising step towards robust generalization in natural language processing, producing a set of counterfactuals that offer valuable inductive bias for models remains a challenge. Most existing approaches for producing counterfactuals, manual or automated, rely on small perturbations via minimal edits, resulting

Lvxiaowei Xu, Jianwang Wu, Jiawei Peng, Jiayu Fu

Grammatical Error Correction (GEC) has been broadly applied in automatic correction and proofreading system recently. However, it is still immature in Chinese GEC due to limited high-quality data from native speakers in terms of category and scale. In this paper, we present FCGEC, a fine-grained corpus to detect, identify and correct the grammatical errors.

Yohan Jung, Jinkyoo Park

Convolutional deep sets are the architecture of a deep neural network (DNN) that can model stationary stochastic process. This architecture uses the kernel smoother and the DNN to construct the translation equivariant functional representations, and thus reflects the inductive bias of the stationarity into DNN. However, since this architecture employs the ke

Guangxuan Xu, Ruibo Liu, Fabrice Harel-Canada, Nischal Reddy Chandra

We propose EnDex, the first human-reaction based model to evaluate dialogue engagingness. EnDex is trained on 80k Reddit-based Engagement Dataset (RED) curated using a novel distant-supervision framework. Engagingness is a key measure that captures high-level quality of AI dialogue systems and closely reflects actual user experience. However, data shortage,

Xiaoyu Pan, Huazheng Zhu, Jinglong Du, Guangtao Hu

The Coronavirus Disease 2019 (COVID-19) pandemic has increased the public health burden and brought profound disaster to humans. For the particularity of the COVID-19 medical images with blurred boundaries, low contrast and different infection sites, some researchers have improved the accuracy by adding more complexity. Also, they overlook the complexity of

Lifu Tu, Caiming Xiong, Yingbo Zhou

Pre-trained multilingual language models show significant performance gains for zero-shot cross-lingual model transfer on a wide range of natural language understanding (NLU) tasks. Previously, for zero-shot cross-lingual evaluation, pre-trained models are only fine-tuned on English data and tested on a variety of target languages. In this paper, we do cross

Steve McKeever

In scientific and engineering applications, physical quantities embodied as units of measurement (UoM) are frequently used. The loss of the Mars climate orbiter, attributed to a confusion between the metric and imperial unit systems, popularised the disastrous consequences of incorrectly handling measurement values. Dimensional analysis can be used to ensure

Yinghong Guo, Cheng Li, Chaoxian Zhang, Yao Yao

This paper aims to explore the feasibility of the spectrum sharing between the communication and radar system. We investigate the full-duplex (FD) joint radar and communication multi-antenna system in which a node labeled ComRad with a dual communication and radar capability is communicating with a downlink and an uplink users, as well as detecting the targe

Shaolei Zhang, Yang Feng

Simultaneous translation (ST) outputs translation while receiving the source inputs, and hence requires a policy to determine whether to translate a target token or wait for the next source token. The major challenge of ST is that each target token can only be translated based on the current received source tokens, where the received source information will

M. Asadolah Salmanpour, M. Mosleh, S. M. Hamidi

Considering efforts for hot atom vapor-nanophotonic integration as a new paradigm in quantum optics in this paper we introduce 1D photonic crystal-Rb vapor cell as structure with miniaturized interaction volume. The Bloch surface wave excited on surface of a photonic crystal as electromagnetic hosting photonic mode, and altered the optical response of Rb ato

Arijit Sehanobish, Kawshik Kannan, Nabila Abraham, Anasuya Das

Large pretrained Transformer-based language models like BERT and GPT have changed the landscape of Natural Language Processing (NLP). However, fine tuning such models still requires a large number of training examples for each target task, thus annotating multiple datasets and training these models on various downstream tasks becomes time consuming and expen

T. Tsuchikawa, H. Kaneda, S. Oyabu, T. Kokusho

Mid-Infrared (IR) silicate dust bands observed in heavily obscured active galactic nuclei (AGNs) include information on the mineralogical properties of silicate dust. We aim to investigate the mineralogical picture of the circumnuclear region of heavily obscured AGNs to reveal obscured AGN activities through the picture. In our previous study Tsuchikawa et a

Ravi Dwivedi, Reshma Sanjhira

The main objective of the present paper is to introduce and study the function $_pR_q(A, B; z)$ with matrix parameters and investigate the convergence of this matrix function. The contiguous matrix function relations, differential formulas and the integral representation for the matrix function $_pR_q(A, B; z)$ are derived. Certain properties of the matrix f

Joshua Robinson, Christopher Michael Rytting, David Wingate

While large language models (LLMs) like GPT-3 have achieved impressive results on multiple choice question answering (MCQA) tasks in the zero, one, and few-shot settings, they generally lag behind the MCQA state of the art (SOTA). MCQA tasks have traditionally been presented to LLMs like cloze tasks. An LLM is conditioned on a question (without the associate

Yi-Ling Qiao, Alexander Gao, Ming C. Lin

We present a method for learning 3D geometry and physics parameters of a dynamic scene from only a monocular RGB video input. To decouple the learning of underlying scene geometry from dynamic motion, we represent the scene as a time-invariant signed distance function (SDF) which serves as a reference frame, along with a time-conditioned deformation field. W

Haicheng Zhang

Let $\mathcal {A}$ be a finitary hereditary abelian category. We define a Hall algebra for the root category of $\mathcal {A}$ by applying the derived Hall numbers of the bounded derived category $D^b(\mathcal {A})$, which is proved to be isomorphic to the Drinfeld double Hall algebra of $\mathcal {A}$. In the appendix, we also define the 1-periodic derived

Jinoh Cho, Minguk Kang, Vibhav Vineet, Jaesik Park

Image completion is a task that aims to fill in the missing region of a masked image with plausible contents. However, existing image completion methods tend to fill in the missing region with the surrounding texture instead of hallucinating a visual instance that is suitable in accordance with the context of the scene. In this work, we propose a novel image

Rabin Banerjee, Anwesha Chakraborty

Using a generalised Noether prescription we are able to extract all the currents and their conservation laws in space dependent shift symmetric theories. Various identities among the currents in the matter sector are found that form the basis for revealing a dual picture when the full interacting theory is considered by coupling to gauge fields. The coupling

Yan Qi, Han Sun, Ningzhong Liu, Huiyu Zhou

The goal of fine-grained few-shot learning is to recognize sub-categories under the same super-category by learning few labeled samples. Most of the recent approaches adopt a single similarity measure, that is, global or local measure alone. However, for fine-grained images with high intra-class variance and low inter-class variance, exploring global invaria

Pretom Roy Ovi, Emon Dey, Nirmalya Roy, Aryya Gangopadhyay

Federated Learning (FL) enables collaborative model building among a large number of participants without the need for explicit data sharing. But this approach shows vulnerabilities when privacy inference attacks are applied to it. In particular, in the event of a gradient leakage attack, which has a higher success rate in retrieving sensitive data from the

Stephen Casey

The best way to model, understand, and quantify the information contained in complex systems is an open question in physics, mathematics, and computer science. The uncertain relationship between entropy and complexity further complicates this question. With ideas drawn from the object-relations theory of psychology, this paper develops an object-relations mo

Sicong Shao, Saleem Alharir, Salim Hariri, Pratik Satam

In the past decade, we have observed a growing interest in using technologies such as artificial intelligence (AI), machine learning, and chatbots to provide assistance to language learners, especially in second language learning. By using AI and natural language processing (NLP) and chatbots, we can create an intelligent self-learning environment that goes

Qiuqiang Kong, Shilei Liu, Junjie Shi, Xuzhou Ye

Sound field decomposition predicts waveforms in arbitrary directions using signals from a limited number of microphones as inputs. Sound field decomposition is fundamental to downstream tasks, including source localization, source separation, and spatial audio reproduction. Conventional sound field decomposition methods such as Ambisonics have limited spatia

Weicheng Zang, Youn Kil Jung, Hongjing Yang, Xiangyu Zhang

We present the analysis of seven microlensing planetary events with planet/host mass ratios $q < 10^{-4}$: KMT-2017-BLG-1194, KMT-2017-BLG-0428, KMT-2019-BLG-1806, KMT-2017-BLG-1003, KMT-2019-BLG-1367, OGLE-2017-BLG-1806, and KMT-2016-BLG-1105. They were identified by applying the Korea Microlensing Telescope Network (KMTNet) AnomalyFinder algorithm to 2016-

Rakpong Kaewpuang, Minrui Xu, Dusit Niyato, Han Yu

Quantum cloud computing is a promising paradigm for efficiently provisioning quantum resources (i.e., qubits) to users. In quantum cloud computing, quantum cloud providers provision quantum resources in reservation and on-demand plans for users. Literally, the cost of quantum resources in the reservation plan is expected to be cheaper than the cost of quantu

E. Sarhrouni, A. Hammouch, D. Aboutajdine

Hyperspectral images (HSI) classification is a high technical remote sensing tool. The main goal is to classify the point of a region. The HIS contains more than a hundred bidirectional measures, called bands (or simply images), of the same region called Ground Truth Map (GT). Unfortunately, some bands contain redundant information, others are affected by th

Mehmet Tahir Huyut, Andrei Velichko, Maksim Belyaev

Early evaluation of patients who require special care and who have high death-expectancy in COVID-19, and the effective determination of relevant biomarkers on large sample-groups are important to reduce mortality. This study aimed to reveal the routine blood-value predictors of COVID-19 mortality and to determine the lethal-risk levels of these predictors d

Guangyi Jia, Jinxuan Luo, Huaiwen Wang, Qiaoyun Ma

Natural hyperbolic materials (HMs) in two dimensions (2D) have an extraordinarily high anisotropy and a hyperbolic dispersion relation. Some of them can even sustain hyperbolic polaritons with great directional propagation and light compression to deeply sub-wavelength scales due to their inherent anisotropy. Herein, the anisotropic optical features of 2D na

Renjun Duan, Shuangqian Liu

The motion of rarefied gases for uniform shear flow at the kinetic level is governed by the spatially homogeneous Boltzmann equation with a deformation force. In the paper we study the corresponding Cauchy problem with initial data of finite mass and energy for the collision kernel in case of hard potentials $0<\gamma\leq 1$ under the cutoff assumption. We p

Junwei Bao, Yifan Wang, Jiangyong Ying, Yeyun Gong

Conventional autoregressive left-to-right (L2R) sequence generation faces two issues during decoding: limited to unidirectional target sequence modeling, and constrained on strong local dependencies. To address the aforementioned problem, we propose P$^3$LM, a probabilistically permuted prophet language model, which strengthens the modeling of bidirectional

Federico Tartarini, Mario Frei, Stefano Schiavon, Yun Xuan Chua

Collecting feedback from people in indoor and outdoor environments is traditionally challenging and complex in a reliable, longitudinal, and non-intrusive way. This paper introduces Cozie Apple, an open-source mobile and smartwatch application for iOS devices. This platform allows people to complete a watch-based micro-survey and provide real-time feedback a

Kaixin Ma, Hao Cheng, Xiaodong Liu, Eric Nyberg

We propose a novel open-domain question answering (ODQA) framework for answering single/multi-hop questions across heterogeneous knowledge sources. The key novelty of our method is the introduction of the intermediary modules into the current retriever-reader pipeline. Unlike previous methods that solely rely on the retriever for gathering all evidence in is

Elkebir Sarhrouni, Ahmed Hammouch, Driss Aboutajdine

In the feature classification domain, the choice of data affects widely the results. The Hyperspectral image (HSI), is a set of more than a hundred bidirectional measures (called bands), of the same region (called ground truth map: GT). The HSI is modelized at a set of N vectors. So we have N features (or attributes) expressing N vectors of measures for C su

Xianjing Zhou, Xinhao Li, Qianfan Chen, Gerwin Koolstra

Electron charge qubits are compelling candidates for solid-state quantum computing because of their inherent simplicity in qubit design, fabrication, control, and readout. However, all existing electron charge qubits, built upon conventional semiconductors and superconductors, suffer from severe charge noise that limits the coherence time to the order of 1 m

GuangChen Sun, Yougang Wang, Chao Liu, Richard J. Long

We combine the kinematics of 159 globular clusters (GCs) provided by the Gaia Early Data Release 3 (EDR3) with other observational data to classify the GCs, and to estimate the mass of the Milky Way (MW). We use the age-metallicity relation, integrals of motion, action space and the GC orbits to identify the GCs as either formed in-situ (Bulge and Disk) or e

Aparna Khare, Minhua Wu, Saurabhchand Bhati, Jasha Droppo

Contrastive Predictive Coding (CPC) is a representation learning method that maximizes the mutual information between intermediate latent representations and the output of a given model. It can be used to effectively initialize the encoder of an Automatic Speech Recognition (ASR) model. We present a novel modification of CPC called Guided Contrastive Predict

Henry Lam, Kaizheng Wang, Yuhang Wu, Yichen Zhang

We study the problem of multi-task non-smooth optimization that arises ubiquitously in statistical learning, decision-making and risk management. We develop a data fusion approach that adaptively leverages commonalities among a large number of objectives to improve sample efficiency while tackling their unknown heterogeneities. We provide sharp statistical g

Xiangyu Chen, Qinghao Hu, Kaidong Li, Cuncong Zhong

Vision Transformers has demonstrated competitive performance on computer vision tasks benefiting from their ability to capture long-range dependencies with multi-head self-attention modules and multi-layer perceptron. However, calculating global attention brings another disadvantage compared with convolutional neural networks, i.e. requiring much more data a

Jae-Woo Lee

We present new large field-of-view ($\sim$1\deg$\times$1\deg) Ca-CN photometry of the prototypical metal-rich globular cluster 47 Tucanae (NGC 104). Our results are the following. (1) The populational number ratios of the red giant branch (RGB) and red horizontal branch (RHB) are in excellent agreement: n(CN-w):n(CN-s) = 30:70 ($\pm$1--2), where the CN-w and

Paul K. Mandal, Rakesh Mahto

Alzheimer's disease (AD) is a neuro-degenerative disease that can cause dementia and result severe reduction in brain function inhibiting simple tasks especially if no preventative care is taken. Over 1 in 9 Americans suffer from AD induced dementia and unpaid care for people with AD related dementia is valued at $271.6 billion. Hence, various approaches hav

Fei Wang, Kaiqiang Song, Hongming Zhang, Lifeng Jin

Abstractive summarization models typically learn to capture the salient information from scratch implicitly. Recent literature adds extractive summaries as guidance for abstractive summarization models to provide hints of salient content and achieves better performance. However, extractive summaries as guidance could be over strict, leading to information lo

Jiacheng Ye, Jiahui Gao, Jiangtao Feng, Zhiyong Wu

Recently, dataset-generation-based zero-shot learning has shown promising results by training a task-specific model with a dataset synthesized from large pre-trained language models (PLMs). The final task-specific model often achieves compatible or even better performance than PLMs under the zero-shot setting, with orders of magnitude fewer parameters. Howev

Hao Wang, Yixin Cao, Yangguang Li, Zhen Huang

Document-level natural language inference (DOCNLI) is a new challenging task in natural language processing, aiming at judging the entailment relationship between a pair of hypothesis and premise documents. Current datasets and baselines largely follow sentence-level settings, but fail to address the issues raised by longer documents. In this paper, we estab

Muhammad Enayetur Rahman, Marwan Abdelatti, Manbir Singh Sodhi, Kunal Mankodiya

Near Field Communication (NFC) is a perfect example of ubiquitous computing that is secured, short-ranged, low-powered contactless communication. High demand is predicted for NFC, especially with wearables, and the variety of applications may require that this technology be fabricated onto different materials. In this research, we first designed flexible NFC

Huihui Yang

In human dialogue, a single query may elicit numerous appropriate responses. The Transformer-based dialogue model produces frequently occurring sentences in the corpus since it is a one-to-one mapping function. CVAE is a technique for reducing generic replies. In this paper, we create a new dialogue model (CVAE-T) based on the Transformer with CVAE structure

William Y. C. Chen, Amy M. Fu

We develop a nonstandard approach to exploring polynomials associated with peaks and runs of permutations. With the aid of a context-free grammar, or a set of substitution rules, one can perform a symbolic calculus, and the computation often becomes rather simple. From a grammar it follows at once a system of ordinary differential equations for the generatin

Shawn Diaz

In this experiment, three different search algorithms are implemented for the purpose of extracting a task tree from a large knowledge graph, known as the Functional Object-Oriented Network (FOON). Using a universal FOON, which contains knowledge extracted by annotating online cooking videos, and a desired goal, a task tree can be retrieved. The process of s

Hisashi Kashima, Satoshi Oyama, Hiromi Arai, Junichiro Mori

Human computation is an approach to solving problems that prove difficult using AI only, and involves the cooperation of many humans. Because human computation requires close engagement with both "human populations as users" and "human populations as driving forces," establishing mutual trust between AI and humans is an important issue to further the develop

Soumya Ganguly, Shubham Sinha

We show that the Bergman metric of the ball quotients $\mathbb{B}^2/\Gamma$, where $\Gamma$ is a finite and fixed point free group, is K\"ahler-Einstein if and only if $\Gamma$ is trivial. As a consequence, we characterize the unit ball $\mathbb{B}^2$, among 2 dimensional Stein spaces with isolated normal singularities, proving an algebraic version of Cheng'

Fernando López-García, Ignacio Ojea

We study certain inequalities and a related result on weighted Sobolev spaces on bounded John domains in $\mathbb{R}^n$. Namely, we prove the existence of a right inverse for the divergence operator, along with the corresponding a priori estimate, the improved and the fractional Poincar\'e inequalities, the Korn inequality and the local Fefferman-Stein inequ

Adam Wiemerslage, Shiran Dudy, Katharina Kann

Neural networks have long been at the center of a debate around the cognitive mechanism by which humans process inflectional morphology. This debate has gravitated into NLP by way of the question: Are neural networks a feasible account for human behavior in morphological inflection? We address that question by measuring the correlation between human judgment

Yiheng Lin, James A. Preiss, Emile Anand, Yingying Li

We study online adaptive policy selection in systems with time-varying costs and dynamics. We develop the Gradient-based Adaptive Policy Selection (GAPS) algorithm together with a general analytical framework for online policy selection via online optimization. Under our proposed notion of contractive policy classes, we show that GAPS approximates the behavi

Ilya L. Shapiro

The purpose of this Chapter is to give a general introduction and status review on the perturbative approach to quantum gravity (QG). This text is a modified version of the corresponding chapters of Part II of the recent textbook on quantum field theory (QFT) and QG, co-authored with I.L. Buchbinder and published in Oxford University Press. We discuss the ch

Junsu Jang, Florian Meyer, Eric R. Snyder, Sean M. Wiggins

Localizing and tracking of marine mammals can reveal key insights into behaviors underwater that otherwise would remain unexplored. A promising nonintrusive approach to obtaining location information of marine mammals is based on recordings of bio-acoustic signals by volumetric hydrophone arrays. Time-difference-of-arrival (TDOA) measurements of echolocation

Mohsen Zahmatkesh, Seyyed Ali Emami, Afshin Banazadeh, Paolo Castaldi

Attitude control of a novel regional truss-braced wing aircraft with low stability characteristics is addressed in this paper using Reinforcement Learning (RL). In recent years, RL has been increasingly employed in challenging applications, particularly, autonomous flight control. However, a significant predicament confronting discrete RL algorithms is the d

Yupeng Hou, Zhankui He, Julian McAuley, Wayne Xin Zhao

Recently, the generality of natural language text has been leveraged to develop transferable recommender systems. The basic idea is to employ pre-trained language models~(PLM) to encode item text into item representations. Despite the promising transferability, the binding between item text and item representations might be too tight, leading to potential pr

Zhiyuan Ren, Zhihong Pan, Xin Zhou, Le Kang

We propose a simple and novel method for generating 3D human motion from complex natural language sentences, which describe different velocity, direction and composition of all kinds of actions. Different from existing methods that use classical generative architecture, we apply the Denoising Diffusion Probabilistic Model to this task, synthesizing diverse m

Md Tawkat Islam Khondaker, El Moatez Billah Nagoudi, AbdelRahim Elmadany, Muhammad Abdul-Mageed

Contrastive learning (CL) brought significant progress to various NLP tasks. Despite this progress, CL has not been applied to Arabic NLP to date. Nor is it clear how much benefits it could bring to particular classes of tasks such as those involved in Arabic social meaning (e.g., sentiment analysis, dialect identification, hate speech detection). In this wo

I. A. Alexeev, A. A. Khartov

Multivariate discrete probability laws are considered. We show that such laws are quasi-infinitely divisible if and only if their characteristic functions are separated from zero. We generalize the existing results for the univariate discrete laws and for the multivariate laws on $\mathbb{Z}^d$. The Cram\'er-Wold devices for infinite and quasi-infinite divis

Yiheng Lin, Yang Hu, Guannan Qu, Tongxin Li

We study Model Predictive Control (MPC) and propose a general analysis pipeline to bound its dynamic regret. The pipeline first requires deriving a perturbation bound for a finite-time optimal control problem. Then, the perturbation bound is used to bound the per-step error of MPC, which leads to a bound on the dynamic regret. Thus, our pipeline reduces the

Zhen Qin, Jun Tao, Le Yang, Ming Jiang

The maximum correntropy criterion (MCC) has been employed to design outlier-robust adaptive filtering algorithms, among which the recursive MCC (RMCC) algorithm is a typical one. Motivated by the success of our recently proposed proportionate recursive least squares (PRLS) algorithm for sparse system identification, we propose to introduce the proportionate

Akansha Singh Bansal, Yoonjin Lee, Kyle Hilburn, Imme Ebert-Uphoff

Atmospheric processes involve both space and time. This is why human analysis of atmospheric imagery can often extract more information from animated loops of image sequences than from individual images. Automating such an analysis requires the ability to identify spatio-temporal patterns in image sequences which is a very challenging task, because of the en

Songyang Zhang, Linfeng Song, Lifeng Jin, Haitao Mi

Video-aided grammar induction aims to leverage video information for finding more accurate syntactic grammars for accompanying text. While previous work focuses on building systems for inducing grammars on text that are well-aligned with video content, we investigate the scenario, in which text and video are only in loose correspondence. Such data can be fou

Niranjan Uma Naresh, Ziyan Jiang, Ankit, Sungjin Lee

Conversational understanding is an integral part of modern intelligent devices. In a large fraction of the global traffic from customers using smart digital assistants, frictions in dialogues may be attributed to incorrect understanding of the entities in a customer's query due to factors including ambiguous mentions, mispronunciation, background noise and f

Anne de Bortoli, Yacine Baouch, Mustapha Masdan

Transforming the construction sector is key to reaching net-zero, and many stakeholders expect its decarbonization through digitalization. But no quantified evidence has been brought to date. We propose the first environmental quantification of the impact of Building Information Modeling (BIM) in the construction sector. Specifically, the direct and indirect

Jazlyn A. Mooney, Lily Agranat-Tamir, Jonathan K. Pritchard, Noah A. Rosenberg

In genetically admixed populations, admixed individuals possess ancestry from multiple source groups. Studies of human genetic admixture frequently estimate ancestry components corresponding to fractions of individual genomes that trace to specific ancestral populations. However, the same numerical ancestry fraction can represent a wide array of admixture sc

Einar Gabbassov

An essential consideration in urban transit facility planning is service efficiency and accessibility. Previous research has shown that reducing the number of facilities along a route may increase efficiency but decrease accessibility. Striking a balance between these two is a critical consideration in transit planning. Transit facility consolidation is a co

Einar Gabbassov, Miguel Moreno-Molina, Iñaki Comas, Maxwell Libbrecht

The occurrence of multiple strains of a bacterial pathogen such as M. tuberculosis or C. difficile within a single human host, referred to as a mixed infection, has important implications for both healthcare and public health. However, methods for detecting it, and especially determining the proportion and identities of the underlying strains, from WGS (whol

Ilya Mandel, Andrei P. Igoshev

The speeds of young isolated pulsars are generally inferred from their observed 2-d velocities on the plane of the sky under the assumption that the unobserved radial velocity is not special, i.e., that the measured 2-d velocity is an isotropic projection of the full 3-d velocity. However, if pulsar spins are preferentially aligned with kicks, then the obser

Victor Guba

We improve some known estimates for the density of the Cayley graph of Thompson's group F in standard generators.

Piotr Miska, János T. Tóth

Let $0\leq q\leq1$ and $\mathbb{N}$ denotes the set of all positive integers. In this paper we will deal with it too the family $\mathcal{U}(x^q)$ of all regularly distributed set $X \subset \mathbb{N}$ whose ratio block sequence is asymptotically distributed with distribution function $g(x) = x^q;\ x \in(0,1]$, and we will show that the regular distributed

Avinash Madasu, Shashank Srivastava

Large language models (LMs) have rapidly become a mainstay in Natural Language Processing. These models are known to acquire rich linguistic knowledge from training on large amounts of text. In this paper, we investigate if pre-training on text also confers these models with helpful `inductive biases' for non-linguistic reasoning. On a set of 19 diverse non-

Shiqi Liu, Mengdi Xu, Piede Huang, Yongkang Liu

Continual reinforcement learning aims to sequentially learn a variety of tasks, retaining the ability to perform previously encountered tasks while simultaneously developing new policies for novel tasks. However, current continual RL approaches overlook the fact that certain tasks are identical under basic group operations like rotations or translations, esp

Masato Hagiwara, Benjamin Hoffman, Jen-Yu Liu, Maddie Cusimano

The use of machine learning (ML) based techniques has become increasingly popular in the field of bioacoustics over the last years. Fundamental requirements for the successful application of ML based techniques are curated, agreed upon, high-quality datasets and benchmark tasks to be learned on a given dataset. However, the field of bioacoustics so far lacks

Hui Guo, Xin Wang, Siwei Lyu

The COVID pandemic has led to the wide adoption of online video calls in recent years. However, the increasing reliance on video calls provides opportunities for new impersonation attacks by fraudsters using the advanced real-time DeepFakes. Real-time DeepFakes pose new challenges to detection methods, which have to run in real-time as a video call is ongoin

Hua Chen, Jian-Meng Li, Kelei Wang

In this paper we develop a blow up theory for the parabolic-elliptic Keller-Segel system, which can be viewed as a parabolic counterpart to the Liouville equation. This theory is applied to the study of first time singularities, ancient solutions and entire solutions, leading to a description of the blow-up limit in the first problem, and the large scale str

Chen Chen, Matin Yarmand, Varun Singh, Michael V. Sherer

Contouring is an indispensable step in Radiotherapy (RT) treatment planning. However, today's contouring software is constrained to only work with a 2D display, which is less intuitive and requires high task loads. Virtual Reality (VR) has shown great potential in various specialties of healthcare and health sciences education due to the unique advantages of

Shaiban Ahmed, Rasheed Abid, S. Kaisar Alam

Adaptive stretching, where the post compression signal is iteratively stretched to maximize the correlation between the pre and post compression rf echo frames, has demonstrated superior performance compared to gradient based methods. At higher levels of applied strain however, adaptive stretching suffers from decorrelation noise and the image quality deteri

Elkebir Sarhrouni, Ahmed Hammouch, Driss Aboutajdine

Remote sensing is a higher technology to produce knowledge for data mining applications. In principle hyperspectral images (HSIs) is a remote sensing tool that provides precise classification of regions. The HSI contains more than a hundred of images of the ground truth (GT) map. Some images are carrying relevant information, but others describe redundant in