astro-ph.CO - 宇宙学和天体物理学
cs.AI - 人工智能
cs.CE - 计算工程、 金融和科学
cs.CL - 计算与语言
cs.CR - 加密与安全
cs.CV - 机器视觉与模式识别
cs.DB - 数据库
cs.DC - 分布式、并行与集群计算
cs.DL - 数字图书馆
cs.HC - 人机接口
cs.IR - 信息检索
cs.IT - 信息论
cs.LG - 自动学习
cs.NE - 神经与进化计算
cs.NI - 网络和互联网体系结构
cs.RO - 机器人学
cs.SE - 软件工程
cs.SI - 社交网络与信息网络
econ.EM - 计量经济学
eess.AS - 语音处理
eess.IV - 图像与视频处理
eess.SP - 信号处理
eess.SY - 系统和控制
math-ph - 数学物理
math.OC - 优化与控制
math.PR - 概率
math.ST - 统计理论
physics.comp-ph - 计算物理学
physics.flu-dyn - 流体动力学
physics.plasm-ph - 等离子体物理
q-bio.QM - 定量方法
quant-ph - 量子物理
stat.AP - 应用统计
stat.ME - 统计方法论
stat.ML - (统计)机器学习
• [astro-ph.CO]Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation
• [astro-ph.CO]Inferring halo masses with Graph Neural Networks
• [cs.AI]A first approach to closeness distributions
• [cs.AI]Accounting for Gaussian Process Imprecision in Bayesian Optimization
• [cs.AI]An Empirical Study of Finding Similar Exercises
• [cs.AI]Causal policy ranking
• [cs.AI]From Convolutions towards Spikes: The Environmental Metric that the Community currently Misses
• [cs.AI]Improving Learning from Demonstrations by Learning from Experience
• [cs.AI]JMSNAS: Joint Model Split and Neural Architecture Search for Learning over Mobile Edge Networks
• [cs.AI]Neural Class Expression Synthesis
• [cs.AI]Self-encoding Barnacle Mating Optimizer Algorithm for Manpower Scheduling in Flow Shop
• [cs.AI]The Partially Observable History Process
• [cs.AI]Uncertainty-Aware Multiple Instance Learning fromLarge-Scale Long Time Series Data
• [cs.AI]Will We Trust What We Don’t Understand? Impact of Model Interpretability and Outcome Feedback on Trust in AI
• [cs.CE]Machine Learning-Based Assessment of Energy Behavior of RC Shear Walls
• [cs.CL]A Comparative Study on Transfer Learning and Distance Metrics in Semantic Clustering over the COVID-19 Tweets
• [cs.CL]Adversarially Constructed Evaluation Sets Are More Challenging, but May Not Be Fair
• [cs.CL]Assessing gender bias in medical and scientific masked language models with StereoSet
• [cs.CL]CCA-MDD: A Coupled Cross-Attention based Framework for Streaming Mispronunciation detection and diagnosis
• [cs.CL]CVSS-BERT: Explainable Natural Language Processing to Determine the Severity of a Computer Security Vulnerability from its Description
• [cs.CL]Coral: An Approach for Conversational Agents in Mental Health Applications
• [cs.CL]DataCLUE: A Benchmark Suite for Data-centric NLP
• [cs.CL]Document AI: Benchmarks, Models and Applications
• [cs.CL]Exploring Story Generation with Multi-task Objectives in Variational Autoencoders
• [cs.CL]Few-Shot Self-Rationalization with Natural Language Prompts
• [cs.CL]Generative Pre-Trained Transformer for Design Concept Generation: An Exploration
• [cs.CL]Improving the robustness and accuracy of biomedical language models through adversarial training
• [cs.CL]Integrated Semantic and Phonetic Post-correction for Chinese Speech Recognition
• [cs.CL]Joint Unsupervised and Supervised Training for Multilingual ASR
• [cs.CL]Literature-Augmented Clinical Outcome Prediction
• [cs.CL]Meeting Summarization with Pre-training and Clustering Methods
• [cs.CL]Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts
• [cs.CL]Multi-Vector Models with Textual Guidance for Fine-Grained Scientific Document Similarity
• [cs.CL]NVIDIA NeMo Neural Machine Translation Systems for English-German and English-Russian News and Biomedical Tasks at WMT21
• [cs.CL]STAMP 4 NLP — An Agile Framework for Rapid Quality-Driven NLP Applications Development
• [cs.CL]The role of attraction-repulsion dynamics in simulating the emergence of inflectional class systems
• [cs.CL]WikiContradiction: Detecting Self-Contradiction Articles on Wikipedia
• [cs.CR]An Overview of Backdoor Attacks Against Deep Neural Networks and Possible Defences
• [cs.CV] for Interaction Prediction
• [cs.CV]A Data-Driven Approach for Linear and Nonlinear Damage Detection Using Variational Mode Decomposition and GARCH Model
• [cs.CV]Bengali Handwritten Grapheme Classification: Deep Learning Approach
• [cs.CV]Beyond Mono to Binaural: Generating Binaural Audio from Mono Audio with Depth and Cross Modal Attention
• [cs.CV]CAR — Cityscapes Attributes Recognition A Multi-category Attributes Dataset for Autonomous Vehicles
• [cs.CV]Choose Settings Carefully: Comparing Action Unit detection at Different Settings Using a Large-Scale Dataset
• [cs.CV]Coarse-to-fine Animal Pose and Shape Estimation
• [cs.CV]Consistent Semantic Attacks on Optical Flow
• [cs.CV]DFC: Deep Feature Consistency for Robust Point Cloud Registration
• [cs.CV]DRINet++: Efficient Voxel-as-point Point Cloud Segmentation
• [cs.CV]Data Augmentation using Random Image Cropping for High-resolution Virtual Try-On (VITON-CROP)
• [cs.CV]Delta-GAN-Encoder: Encoding Semantic Changes for Explicit Image Editing, using Few Synthetic Samples
• [cs.CV]Diversified Multi-prototype Representation for Semi-supervised Segmentation
• [cs.CV]Enabling equivariance for arbitrary Lie groups
• [cs.CV]FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows
• [cs.CV]Fight Detection from Still Images in the Wild
• [cs.CV]IKEA Object State Dataset: A 6DoF object pose estimation dataset and benchmark for multi-state assembly objects
• [cs.CV]INTERN: A New Learning Paradigm Towards General Vision
• [cs.CV]Improved Robustness of Vision Transformer via PreLayerNorm in Patch Embedding
• [cs.CV]Keypoint Message Passing for Video-based Person Re-Identification
• [cs.CV]LIMEcraft: Handcrafted superpixel selection and inspection for Visual eXplanations
• [cs.CV]Language bias in Visual Question Answering: A Survey and Taxonomy
• [cs.CV]Learnable Locality-Sensitive Hashing for Video Anomaly Detection
• [cs.CV]Learning Intrinsic Images for Clothing
• [cs.CV]NENet: Monocular Depth Estimation via Neural Ensembles
• [cs.CV]Pansharpening by convolutional neural networks in the full resolution framework
• [cs.CV]Point detection through multi-instance deep heatmap regression for sutures in endoscopy
• [cs.CV]Pose Recognition in the Wild: Animal pose estimation using Agglomerative Clustering and Contrastive Learning
• [cs.CV]Rethinking Keypoint Representations: Modeling Keypoints and Poses as Objects for Multi-Person Human Pose Estimation
• [cs.CV]Robust 3D Scene Segmentation through Hierarchical and Learnable Part-Fusion
• [cs.CV]SEnSeI: A Deep Learning Module for Creating Sensor Independent Cloud Masks
• [cs.CV]Self-supervised High-fidelity and Re-renderable 3D Facial Reconstruction from a Single Image
• [cs.CV]SequentialPointNet: A strong parallelized point cloud sequence network for 3D action recognition
• [cs.CV]ShapeY: Measuring Shape Recognition Capacity Using Nearest Neighbor Matching
• [cs.CV]Single Image Object Counting and Localizing using Active-Learning
• [cs.CV]Synthetic Unknown Class Learning for Learning Unknowns
• [cs.CV]TRIG: Transformer-Based Text Recognizer with Initial Embedding Guidance
• [cs.CV]Two-dimensional Deep Regression for Early Yield Prediction of Winter Wheat
• [cs.CV]UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection
• [cs.CV]Weakly-supervised fire segmentation by visualizing intermediate CNN layers
• [cs.CV]Which CNNs and Training Settings to Choose for Action Unit Detection? A Study Based on a Large-Scale Dataset
• [cs.DB]Highly Efficient Indexing Scheme for k-Dominant Skyline Processing over Uncertain Data Streams
• [cs.DC]Online Self-Evolving Anomaly Detection in Cloud Computing Environments
• [cs.DC]Project CGX: Scalable Deep Learning on Commodity GPUs
• [cs.DC]Quo Vadis MPI RMA? Towards a More Efficient Use of MPI One-Sided Communication
• [cs.DC]Saath: Speeding up CoFlows by Exploiting the Spatial Dimension
• [cs.DC]Self-Stabilization and Byzantine Tolerance for Maximal Independent Set
• [cs.DC]Task allocation for decentralized training in heterogeneous environment
• [cs.DL]Patent Data for Engineering Design: A Review
• [cs.HC]Words of Wisdom: Representational Harms in Learning From AI Communication
• [cs.IR]Pre-training Graph Neural Network for Cross Domain Recommendation
• [cs.IR]QA4PRF: A Question Answering based Framework for Pseudo Relevance Feedback
• [cs.IR]Utilizing Textual Reviews in Latent Factor Models for Recommender Systems
• [cs.IT]A Markov Chain Approach for Myopic Multi-hop Relaying: Outage and Diversity Analysis
• [cs.IT]A fixed latency ORBGRAND decoder architecture with LUT-aided error-pattern scheduling
• [cs.IT]Continuous-Aperture MIMO for Electromagnetic Information Theory
• [cs.IT]Dense Circulant Lattices From Nonlinear Systems
• [cs.IT]Faster-than-Nyquist Asynchronous NOMA Outperforms Synchronous NOMA
• [cs.IT]Faster-than-Nyquist Signaling for MIMO Communications
• [cs.IT]Generalization Bounds and Algorithms for Learning to Communicate over Additive Noise Channels
• [cs.IT]Hybrid Beam Alignment for Multi-Path Channels: A Group Testing Viewpoint
• [cs.IT]Hybrid Reflection Modulation
• [cs.IT]Introduction to Set Shaping Theory
• [cs.IT]On Reverse Elastic Channels and the Asymmetry of Commitment Capacity under Channel Elasticity
• [cs.IT]On The Number of Different Entries in Involutory MDS Matrices over Finite Fields of Characteristic Two
• [cs.LG]A Unified and Fast Interpretable Model for Predictive Analytics
• [cs.LG]Assessing Deep Neural Networks as Probability Estimators
• [cs.LG]Automatically detecting anomalous exoplanet transits
• [cs.LG]Causal Effect Variational Autoencoder with Uniform Treatment
• [cs.LG]Comparative Analysis of Machine Learning Models for Predicting Travel Time
• [cs.LG]Deep Distilling: automated code generation using explainable deep learning
• [cs.LG]Exploiting Action Impact Regularity and Partially Known Models for Offline Reinforcement Learning
• [cs.LG]Fairness-aware Online Price Discrimination with Nonparametric Demand Models
• [cs.LG]FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
• [cs.LG]FedCostWAvg: A new averaging for better Federated Learning
• [cs.LG]Free Will Belief as a consequence of Model-based Reinforcement Learning
• [cs.LG]Grounding Psychological Shape Space in Convolutional Neural Networks
• [cs.LG]HADFL: Heterogeneity-aware Decentralized Federated Learning Framework
• [cs.LG]HiRID-ICU-Benchmark — A Comprehensive Machine Learning Benchmark on High-resolution ICU Data
• [cs.LG]Inference-Time Personalized Federated Learning
• [cs.LG]Interpretable and Fair Boolean Rule Sets via Column Generation
• [cs.LG]Interpreting Language Models Through Knowledge Graph Extraction
• [cs.LG]Inverse-Weighted Survival Games
• [cs.LG]Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks
• [cs.LG]Learning Augmentation Distributions using Transformed Risk Minimization
• [cs.LG]Learning Graph Neural Networks for Multivariate Time Series Anomaly Detection
• [cs.LG]Machine Learning and Ensemble Approach Onto Predicting Heart Disease
• [cs.LG]Machine Learning-Assisted Analysis of Small Angle X-ray Scattering
• [cs.LG]Margin-Independent Online Multiclass Learning via Convex Geometry
• [cs.LG]Mathematical Models for Local Sensing Hashes
• [cs.LG]MoRe-Fi: Motion-robust and Fine-grained Respiration Monitoring via Deep-Learning UWB Radar
• [cs.LG]ModelLight: Model-Based Meta-Reinforcement Learning for Traffic Signal Control
• [cs.LG]Modular Networks Prevent Catastrophic Interference in Model-Based Multi-Task Reinforcement Learning
• [cs.LG]Multi-Centroid Hyperdimensional Computing Approach for Epileptic Seizure Detection
• [cs.LG]Natural Gradient Variational Inference with Gaussian Mixture Models
• [cs.LG]Neural networks with linear threshold activations: structure and algorithms
• [cs.LG]Neuron-based Pruning of Deep Neural Networks with Better Generalization using Kronecker Factored Curvature Approximation
• [cs.LG]Non-separable Spatio-temporal Graph Kernels via SPDEs
• [cs.LG]Off-Policy Actor-Critic with Emphatic Weightings
• [cs.LG]On Bock’s Conjecture Regarding the Adam Optimizer
• [cs.LG]On Effective Scheduling of Model-based Reinforcement Learning
• [cs.LG]Persia: A Hybrid System Scaling Deep Learning Based Recommenders up to 100 Trillion Parameters
• [cs.LG]Phase function estimation from a diffuse optical image via deep learning
• [cs.LG]Polymatrix Competitive Gradient Descent
• [cs.LG]Rank-Regret Minimization
• [cs.LG]Reinforcement Learning with Feedback from Multiple Humans with Diverse Skills
• [cs.LG]Reshaping Smart Energy Transition: An analysis of human-building interactions in Qatar Using Machine Learning Techniques
• [cs.LG]Robust recovery for stochastic block models
• [cs.LG]Robustness of Bayesian Neural Networks to White-Box Adversarial Attacks
• [cs.LG]Selective Ensembles for Consistent Predictions
• [cs.LG]Solving Linear Algebra by Program Synthesis
• [cs.LG]Solving Probability and Statistics Problems by Program Synthesis
• [cs.LG]Switching Recurrent Kalman Networks
• [cs.LG]Thoughts on the Consistency between Ricci Flow and Neural Network Behavior
• [cs.LG]TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generation
• [cs.LG]Towards Generating Real-World Time Series Data
• [cs.LG]VisualEnv: visual Gym environments with Blender
• [cs.LG]Wyner-Ziv Gradient Compression for Federated Learning
• [cs.NE]A Multi-criteria Approach to Evolve Sparse Neural Architectures for Stock Market Forecasting
• [cs.NI]CLARA: A Constrained Reinforcement Learning Based Resource Allocation Framework for Network Slicing
• [cs.NI]Common Language for Goal-Oriented Semantic Communications: A Curriculum Learning Framework
• [cs.NI]HyperNAT: Scaling Up Network AddressTranslation with SmartNICs for Clouds
• [cs.NI]Learning Robust Scheduling with Search and Attention
• [cs.RO]2.5D Vehicle Odometry Estimation
• [cs.RO]Active Vapor-Based Robotic Wiper
• [cs.RO]Analysis of Model-Free Reinforcement Learning Control Schemes on self-balancing Wheeled Extendible System
• [cs.RO]GRI: General Reinforced Imitation and its Application to Vision-Based Autonomous Driving
• [cs.RO]Hierarchical Topometric Representation of 3D Robotic Maps
• [cs.RO]Joint State and Input Estimation of Agent Based on Recursive Kalman Filter Given Prior Knowledge
• [cs.RO]Learning to Navigate in a VUCA Environment: Hierarchical Multi-expert Approach
• [cs.RO]Rearranging the Environment to Maximize Energy with a Robotic Circuit Drawing
• [cs.RO]Towards Real-Time Monocular Depth Estimation for Robotics: A Survey
• [cs.RO]Virtual Reality for Synergistic Surgical Training and Data Generation
• [cs.SE]Is CADP an Applicable Formal Method?
• [cs.SI]Analysis of 5G academic Network based on graph representation learning method
• [cs.SI]Improving the performance of reputation evaluating by combining the structure of network and nonlinear recovery
• [cs.SI]Local News Online and COVID in the U.S.: Relationships among Coverage, Cases, Deaths, and Audience
• [econ.EM]Designing Representative and Balanced Experiments by Local Randomization
• [econ.EM]Revisiting C.S.Peirce’s Experiment: 150 Years Later
• [eess.AS]Attention-based Multi-hypothesis Fusion for Speech Summarization
• [eess.AS]Single-channel speech separation using Soft-minimum Permutation Invariant Training
• [eess.IV]A Latent Encoder Coupled Generative Adversarial Network (LE-GAN) for Efficient Hyperspectral Image Super-resolution
• [eess.IV]A layer-stress learning framework universally augments deep neural network tasks
• [eess.IV]Advancement of Deep Learning in Pneumonia and Covid-19 Classification and Localization: A Qualitative and Quantitative Analysis
• [eess.IV]Disparities in Dermatology AI: Assessments Using Diverse Clinical Images
• [eess.IV]Image-specific Convolutional Kernel Modulation for Single Image Super-resolution
• [eess.IV]Online Meta Adaptation for Variable-Rate Learned Image Compression
• [eess.IV]Solving Inverse Problems in Medical Imaging with Score-Based Generative Models
• [eess.SP]Blockage Prediction Using Wireless Signatures: Deep Learning Enables Real-World Demonstration
• [eess.SP]Deep Diffusion Models for Robust Channel Estimation
• [eess.SP]Human-error-potential Estimation based on Wearable Biometric Sensors
• [eess.SY]Graph neural network-based fault diagnosis: a review
• [math-ph]Second-order statistics of fermionic Gaussian states
• [math.OC]Data-Driven Inpatient Bed Assignment Using the P Model
• [math.OC]Learning Optimal Control with Stochastic Models of Hamiltonian Dynamics
• [math.OC]Multiclass Optimal Classification Trees with SVM-splits
• [math.OC]Stochastic Extragradient: General Analysis and Improved Rates
• [math.PR]Prediction theory in continuous time
• [math.ST]On Adaptive Confidence Sets for the Wasserstein Distances
• [math.ST]Properties of linear spectral statistics of frequency-smoothed estimated spectral coherence matrix of high-dimensional Gaussian time series
• [math.ST]Quantification of fracture roughness by change probabilities and Hurst exponents
• [physics.comp-ph]Normalizing flows for atomic solids
• [physics.flu-dyn]Global Sensitivity Analysis of Four Chamber Heart Hemodynamics Using Surrogate Models
• [physics.plasm-ph]Tracking Blobs in the Turbulent Edge Plasma of Tokamak Fusion Reactors
• [q-bio.QM]Code-free development and deployment of deep segmentation models for digital pathology
• [quant-ph]Tensor network to learn the wavefunction of data
• [stat.AP]An Empirical Evaluation of the Impact of New York’s Bail Reform on Crime Using Synthetic Controls
• [stat.AP]Bayesian inference of the climbing grade scale
• [stat.AP]Bayesian, frequentist and fiducial intervals for the difference between two binomial proportions
• [stat.AP]Hierarchical transfer learning with applications for electricity load forecasting
• [stat.AP]Joint Estimation of Extreme Precipitation at Different Spatial Scales through Mixture Modelling
• [stat.AP]Neuro-Hotnet: A Graph Theoretic Approach for Brain FC Estimation
• [stat.AP]Regional Topics in British Grocery Retail Transactions
• [stat.ME]Change-point detection for density sequence extracted from SHM data, with application to distributional information break diagnosis encountered in structural condition assessment
• [stat.ME]Inference for extreme spatial temperature events in a changing climate with application to Ireland
• [stat.ME]Multi-Parameter Regression Survival Modelling with Random Effects
• [stat.ME]Sequential Unequal Probability Sampling For Stream Population
• [stat.ME]Simultaneous inference of correlated marginal tests using intersection-union or union-intersection test principle
• [stat.ME]Translating questions to estimands in randomized clinical trials with intercurrent events
• [stat.ML]An adaptive dimension reduction algorithm for latent variables of variational autoencoder
• [stat.ML]Bayesian Optimization for Cascade-type Multi-stage Processes
• [stat.ML]Covariate Shift in High-Dimensional Random Feature Regression
• [stat.ML]Distribution Compression in Near-Linear Time
• [stat.ML]Learning with convolution and pooling operations in kernel methods
• [stat.ML]SStaGCN: Simplified stacking based graph convolutional networks
• [stat.ML]Sequential Community Mode Estimation
• [stat.ML]Sparse Graph Learning Under Laplacian-Related Constraints
·····································
• [astro-ph.CO]Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation
Alex Cole, Benjamin Kurt Miller, Samuel J. Witte, Maxwell X. Cai, Meiert W. Grootes, Francesco Nattino, Christoph Weniger
http://arxiv.org/abs/2111.08030v1
• [astro-ph.CO]Inferring halo masses with Graph Neural Networks
Pablo Villanueva-Domingo, Francisco Villaescusa-Navarro, Daniel Anglés-Alcázar, Shy Genel, Federico Marinacci, David N. Spergel, Lars Hernquist, Mark Vogelsberger, Romeel Dave, Desika Narayanan
http://arxiv.org/abs/2111.08683v1
• [cs.AI]A first approach to closeness distributions
Jesus Cerquides
http://arxiv.org/abs/2111.08357v1
• [cs.AI]Accounting for Gaussian Process Imprecision in Bayesian Optimization
Julian Rodemann, Thomas Augustin
http://arxiv.org/abs/2111.08299v1
• [cs.AI]An Empirical Study of Finding Similar Exercises
Tongwen Huang, Xihua Li
http://arxiv.org/abs/2111.08322v1
• [cs.AI]Causal policy ranking
Daniel McNamee, Hana Chockler
http://arxiv.org/abs/2111.08415v1
• [cs.AI]From Convolutions towards Spikes: The Environmental Metric that the Community currently Misses
Aviral Chharia, Shivu Chauhan, Rahul Upadhyay, Vinay Kumar
http://arxiv.org/abs/2111.08361v1
• [cs.AI]Improving Learning from Demonstrations by Learning from Experience
Haofeng Liu, Yiwen Chen, Jiayi Tan, Marcelo H Ang Jr
http://arxiv.org/abs/2111.08156v1
• [cs.AI]JMSNAS: Joint Model Split and Neural Architecture Search for Learning over Mobile Edge Networks
Yuqing Tian, Zhaoyang Zhang, Zhaohui Yang, Qianqian Yang
http://arxiv.org/abs/2111.08206v1
• [cs.AI]Neural Class Expression Synthesis
N’Dah Jean Kouagou, Stefan Heindorf, Caglar Demir, Axel-Cyrille Ngonga Ngomo
http://arxiv.org/abs/2111.08486v1
• [cs.AI]Self-encoding Barnacle Mating Optimizer Algorithm for Manpower Scheduling in Flow Shop
Shuyun Luo, Wushuang Wang, Mengyuan Fang, Weiqiang Xu
http://arxiv.org/abs/2111.08246v1
• [cs.AI]The Partially Observable History Process
Dustin Morrill, Amy R. Greenwald, Michael Bowling
http://arxiv.org/abs/2111.08102v1
• [cs.AI]Uncertainty-Aware Multiple Instance Learning fromLarge-Scale Long Time Series Data
Yuansheng Zhu, Weishi Shi, Deep Shankar Pandey, Yang Liu, Xiaofan Que, Daniel E. Krutz, Qi Yu
http://arxiv.org/abs/2111.08625v1
• [cs.AI]Will We Trust What We Don’t Understand? Impact of Model Interpretability and Outcome Feedback on Trust in AI
Daehwan Ahn, Abdullah Almaatouq, Monisha Gulabani, Kartik Hosanagar
http://arxiv.org/abs/2111.08222v1
• [cs.CE]Machine Learning-Based Assessment of Energy Behavior of RC Shear Walls
Berkay Topaloglu, Gulsen Taskin Kaya, Fatih Sutcu, Zeynep Tuna Deger
http://arxiv.org/abs/2111.08295v1
• [cs.CL]A Comparative Study on Transfer Learning and Distance Metrics in Semantic Clustering over the COVID-19 Tweets
Elnaz Zafarani-Moattar, Mohammad Reza Kangavari, Amir Masoud Rahmani
http://arxiv.org/abs/2111.08658v1
• [cs.CL]Adversarially Constructed Evaluation Sets Are More Challenging, but May Not Be Fair
Jason Phang, Angelica Chen, William Huang, Samuel R. Bowman
http://arxiv.org/abs/2111.08181v1
• [cs.CL]Assessing gender bias in medical and scientific masked language models with StereoSet
Robert Robinson
http://arxiv.org/abs/2111.08088v1
• [cs.CL]CCA-MDD: A Coupled Cross-Attention based Framework for Streaming Mispronunciation detection and diagnosis
Nianzu Zheng, Liqun Deng, Wenyong Huang, Yu Ting Yeung, Baohua Xu, Yuanyuan Guo, Yasheng Wang, Xin Jiang, Qun Liu
http://arxiv.org/abs/2111.08191v1
• [cs.CL]CVSS-BERT: Explainable Natural Language Processing to Determine the Severity of a Computer Security Vulnerability from its Description
Mustafizur Shahid, Hervé Debar
http://arxiv.org/abs/2111.08510v1
• [cs.CL]Coral: An Approach for Conversational Agents in Mental Health Applications
Harsh Sakhrani, Saloni Parekh, Shubham Mahajan
http://arxiv.org/abs/2111.08545v1
• [cs.CL]DataCLUE: A Benchmark Suite for Data-centric NLP
Liang Xu, Jiacheng Liu, Xiang Pan, Xiaojing Lu, Xiaofeng Hou
http://arxiv.org/abs/2111.08647v1
• [cs.CL]Document AI: Benchmarks, Models and Applications
Lei Cui, Yiheng Xu, Tengchao Lv, Furu Wei
http://arxiv.org/abs/2111.08609v1
• [cs.CL]Exploring Story Generation with Multi-task Objectives in Variational Autoencoders
Zhuohan Xie, Trevor Cohn, Jey Han Lau
http://arxiv.org/abs/2111.08133v1
• [cs.CL]Few-Shot Self-Rationalization with Natural Language Prompts
Ana Marasović, Iz Beltagy, Doug Downey, Matthew E. Peters
http://arxiv.org/abs/2111.08284v1
• [cs.CL]Generative Pre-Trained Transformer for Design Concept Generation: An Exploration
Qihao Zhu, Jianxi Luo
http://arxiv.org/abs/2111.08489v1
• [cs.CL]Improving the robustness and accuracy of biomedical language models through adversarial training
Milad Moradi, Matthias Samwald
http://arxiv.org/abs/2111.08529v1
• [cs.CL]Integrated Semantic and Phonetic Post-correction for Chinese Speech Recognition
Yi-Chang Chen, Chun-Yen Cheng, Ming-Chieh Sung, Yi-Ren Yeh
http://arxiv.org/abs/2111.08400v1
• [cs.CL]Joint Unsupervised and Supervised Training for Multilingual ASR
Junwen Bai, Bo Li, Yu Zhang, Ankur Bapna, Nikhil Siddhartha, Khe Chai Sim, Tara N. Sainath
http://arxiv.org/abs/2111.08137v1
• [cs.CL]Literature-Augmented Clinical Outcome Prediction
Aakanksha Naik, Sravanthi Parasa, Sergey Feldman, Lucy Lu Wang, Tom Hope
http://arxiv.org/abs/2111.08374v1
• [cs.CL]Meeting Summarization with Pre-training and Clustering Methods
Andras Huebner, Wei Ji, Xiang Xiao
http://arxiv.org/abs/2111.08210v1
• [cs.CL]Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts
Yan Zeng, Xinsong Zhang, Hang Li
http://arxiv.org/abs/2111.08276v1
• [cs.CL]Multi-Vector Models with Textual Guidance for Fine-Grained Scientific Document Similarity
Sheshera Mysore, Arman Cohan, Tom Hope
http://arxiv.org/abs/2111.08366v1
• [cs.CL]NVIDIA NeMo Neural Machine Translation Systems for English-German and English-Russian News and Biomedical Tasks at WMT21
Sandeep Subramanian, Oleksii Hrinchuk, Virginia Adams, Oleksii Kuchaiev
http://arxiv.org/abs/2111.08634v1
• [cs.CL]STAMP 4 NLP — An Agile Framework for Rapid Quality-Driven NLP Applications Development
Philipp Kohl, Oliver Schmidts, Lars Klöser, Henri Werth, Bodo Kraft, Albert Zündorf
http://arxiv.org/abs/2111.08408v1
• [cs.CL]The role of attraction-repulsion dynamics in simulating the emergence of inflectional class systems
Erich R. Round, Sacha Beniamine, Louise Esher
http://arxiv.org/abs/2111.08465v1
• [cs.CL]WikiContradiction: Detecting Self-Contradiction Articles on Wikipedia
Cheng Hsu, Cheng-Te Li, Diego Saez-Trumper, Yi-Zhan Hsu
http://arxiv.org/abs/2111.08543v1
• [cs.CR]An Overview of Backdoor Attacks Against Deep Neural Networks and Possible Defences
Wei Guo, Benedetta Tondi, Mauro Barni
http://arxiv.org/abs/2111.08429v1
• [cs.CV] for Interaction Prediction
David Wu, Yunnan Wu
http://arxiv.org/abs/2111.08184v1
• [cs.CV]A Data-Driven Approach for Linear and Nonlinear Damage Detection Using Variational Mode Decomposition and GARCH Model
Vahid Reza Gharehbaghi, Hashem Kalbkhani, Ehsan Noroozinejad Farsangi, T. Y. Yang, Seyedali Mirjalili
http://arxiv.org/abs/2111.08620v1
• [cs.CV]Bengali Handwritten Grapheme Classification: Deep Learning Approach
Tarun Roy, Hasib Hasan, Kowsar Hossain, Masuma Akter Rumi
http://arxiv.org/abs/2111.08249v1
• [cs.CV]Beyond Mono to Binaural: Generating Binaural Audio from Mono Audio with Depth and Cross Modal Attention
Kranti Kumar Parida, Siddharth Srivastava, Gaurav Sharma
http://arxiv.org/abs/2111.08046v1
• [cs.CV]CAR — Cityscapes Attributes Recognition A Multi-category Attributes Dataset for Autonomous Vehicles
Kareem Metwaly, Aerin Kim, Elliot Branson, Vishal Monga
http://arxiv.org/abs/2111.08243v1
• [cs.CV]Choose Settings Carefully: Comparing Action Unit detection at Different Settings Using a Large-Scale Dataset
Mina Bishay, Ahmed Ghoneim, Mohamed Ashraf, Mohammad Mavadati
http://arxiv.org/abs/2111.08324v1
• [cs.CV]Coarse-to-fine Animal Pose and Shape Estimation
Chen Li, Gim Hee Lee
http://arxiv.org/abs/2111.08176v1
• [cs.CV]Consistent Semantic Attacks on Optical Flow
Tom Koren, Lior Talker, Michael Dinerstein, Roy J Jevnisek
http://arxiv.org/abs/2111.08485v1
• [cs.CV]DFC: Deep Feature Consistency for Robust Point Cloud Registration
Zhu Xu, Zhengyao Bai, Huijie Liu, Qianjie Lu, Shenglan Fan
http://arxiv.org/abs/2111.07597v2
• [cs.CV]DRINet++: Efficient Voxel-as-point Point Cloud Segmentation
Maosheng Ye, Rui Wan, Shuangjie Xu, Tongyi Cao, Qifeng Chen
http://arxiv.org/abs/2111.08318v1
• [cs.CV]Data Augmentation using Random Image Cropping for High-resolution Virtual Try-On (VITON-CROP)
Taewon Kang, Sunghyun Park, Seunghwan Choi, Jaegul Choo
http://arxiv.org/abs/2111.08270v1
• [cs.CV]Delta-GAN-Encoder: Encoding Semantic Changes for Explicit Image Editing, using Few Synthetic Samples
Nir Diamant, Nitsan Shandor, Alex M Bronstein
http://arxiv.org/abs/2111.08419v1
• [cs.CV]Diversified Multi-prototype Representation for Semi-supervised Segmentation
Jizong Peng, Christian Desrosiers, Marco Pedersoli
http://arxiv.org/abs/2111.08651v1
• [cs.CV]Enabling equivariance for arbitrary Lie groups
Lachlan E. MacDonald, Sameera Ramasinghe, Simon Lucey
http://arxiv.org/abs/2111.08251v1
• [cs.CV]FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows
Jiawei Yu, Ye Zheng, Xiang Wang, Wei Li, Yushuang Wu, Rui Zhao, Liwei Wu
http://arxiv.org/abs/2111.07677v2
• [cs.CV]Fight Detection from Still Images in the Wild
Şeymanur Aktı, Ferda Ofli, Muhammad Imran, Hazım Kemal Ekenel
http://arxiv.org/abs/2111.08370v1
• [cs.CV]IKEA Object State Dataset: A 6DoF object pose estimation dataset and benchmark for multi-state assembly objects
Yongzhi Su, Mingxin Liu, Jason Rambach, Antonia Pehrson, Anton Berg, Didier Stricker
http://arxiv.org/abs/2111.08614v1
• [cs.CV]INTERN: A New Learning Paradigm Towards General Vision
Jing Shao, Siyu Chen, Yangguang Li, Kun Wang, Zhenfei Yin, Yinan He, Jianing Teng, Qinghong Sun, Mengya Gao, Jihao Liu, Gengshi Huang, Guanglu Song, Yichao Wu, Yuming Huang, Fenggang Liu, Huan Peng, Shuo Qin, Chengyu Wang, Yujie Wang, Conghui He, Ding Liang, Yu Liu, Fengwei Yu, Junjie Yan, Dahua Lin, Xiaogang Wang, Yu Qiao
http://arxiv.org/abs/2111.08687v1
• [cs.CV]Improved Robustness of Vision Transformer via PreLayerNorm in Patch Embedding
Bum Jun Kim, Hyeyeon Choi, Hyeonah Jang, Dong Gu Lee, Wonseok Jeong, Sang Woo Kim
http://arxiv.org/abs/2111.08413v1
• [cs.CV]Keypoint Message Passing for Video-based Person Re-Identification
Di Chen, Andreas Doering, Shanshan Zhang, Jian Yang, Juergen Gall, Bernt Schiele
http://arxiv.org/abs/2111.08279v1
• [cs.CV]LIMEcraft: Handcrafted superpixel selection and inspection for Visual eXplanations
Weronika Hryniewska, Adrianna Grudzień, Przemysław Biecek
http://arxiv.org/abs/2111.08094v1
• [cs.CV]Language bias in Visual Question Answering: A Survey and Taxonomy
Desen Yuan
http://arxiv.org/abs/2111.08531v1
• [cs.CV]Learnable Locality-Sensitive Hashing for Video Anomaly Detection
Yue Lu, Congqi Cao, Yanning Zhang
http://arxiv.org/abs/2111.07839v2
• [cs.CV]Learning Intrinsic Images for Clothing
Kuo Jiang, Zian Wang, Xiaodong Yang
http://arxiv.org/abs/2111.08521v1
• [cs.CV]NENet: Monocular Depth Estimation via Neural Ensembles
Shuwei Shao, Ran Li, Zhongcai Pei, Zhong Liu, Weihai Chen, Wentao Zhu, Xingming Wu, Baochang Zhang
http://arxiv.org/abs/2111.08313v1
• [cs.CV]Pansharpening by convolutional neural networks in the full resolution framework
Matteo Ciotola, Sergio Vitale, Antonio Mazza, Giovanni Poggi, Giuseppe Scarpa
http://arxiv.org/abs/2111.08334v1
• [cs.CV]Point detection through multi-instance deep heatmap regression for sutures in endoscopy
Lalith Sharan, Gabriele Romano, Julian Brand, Halvar Kelm, Matthias Karck, Raffaele De Simone, Sandy Engelhardt
http://arxiv.org/abs/2111.08468v1
• [cs.CV]Pose Recognition in the Wild: Animal pose estimation using Agglomerative Clustering and Contrastive Learning
Samayan Bhattacharya, Sk Shahnawaz
http://arxiv.org/abs/2111.08259v1
• [cs.CV]Rethinking Keypoint Representations: Modeling Keypoints and Poses as Objects for Multi-Person Human Pose Estimation
William McNally, Kanav Vats, Alexander Wong, John McPhee
http://arxiv.org/abs/2111.08557v1
• [cs.CV]Robust 3D Scene Segmentation through Hierarchical and Learnable Part-Fusion
Anirud Thyagharajan, Benjamin Ummenhofer, Prashant Laddha, Om J Omer, Sreenivas Subramoney
http://arxiv.org/abs/2111.08434v1
• [cs.CV]SEnSeI: A Deep Learning Module for Creating Sensor Independent Cloud Masks
Alistair Francis, John Mrziglod, Panagiotis Sidiropoulos, Jan-Peter Muller
http://arxiv.org/abs/2111.08349v1
• [cs.CV]Self-supervised High-fidelity and Re-renderable 3D Facial Reconstruction from a Single Image
Mingxin Yang, Jianwei Guo, Zhanglin Cheng, Xiaopeng Zhang, Dong-Ming Yan
http://arxiv.org/abs/2111.08282v1
• [cs.CV]SequentialPointNet: A strong parallelized point cloud sequence network for 3D action recognition
Xing Li, Qian Huang, Zhijian Wang, Zhenjie Hou, Tianjin Yang
http://arxiv.org/abs/2111.08492v1
• [cs.CV]ShapeY: Measuring Shape Recognition Capacity Using Nearest Neighbor Matching
Jong Woo Nam, Amanda S. Rios, Bartlett W. Mel
http://arxiv.org/abs/2111.08174v1
• [cs.CV]Single Image Object Counting and Localizing using Active-Learning
Inbar Huberman-Spiegelglas, Raanan Fattal
http://arxiv.org/abs/2111.08383v1
• [cs.CV]Synthetic Unknown Class Learning for Learning Unknowns
Jaeyeon Jang
http://arxiv.org/abs/2111.08062v1
• [cs.CV]TRIG: Transformer-Based Text Recognizer with Initial Embedding Guidance
Yue Tao, Zhiwei Jia, Runze Ma, Shugong Xu
http://arxiv.org/abs/2111.08314v1
• [cs.CV]Two-dimensional Deep Regression for Early Yield Prediction of Winter Wheat
Giorgio Morales, John W. Sheppard
http://arxiv.org/abs/2111.08069v1
• [cs.CV]UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection
Andra Acsintoae, Andrei Florescu, Mariana-Iuliana Georgescu, Tudor Mare, Paul Sumedrea, Radu Tudor Ionescu, Fahad Shahbaz Khan, Mubarak Shah
http://arxiv.org/abs/2111.08644v1
• [cs.CV]Weakly-supervised fire segmentation by visualizing intermediate CNN layers
Milad Niknejad, Alexandre Bernardino
http://arxiv.org/abs/2111.08401v1
• [cs.CV]Which CNNs and Training Settings to Choose for Action Unit Detection? A Study Based on a Large-Scale Dataset
Mina Bishay, Ahmed Ghoneim, Mohamed Ashraf, Mohammad Mavadati
http://arxiv.org/abs/2111.08320v1
• [cs.DB]Highly Efficient Indexing Scheme for k-Dominant Skyline Processing over Uncertain Data Streams
Chuan-Chi Lai, Hsuan-Yu Lin, Chuan-Ming Liu
http://arxiv.org/abs/2111.08300v1
• [cs.DC]Online Self-Evolving Anomaly Detection in Cloud Computing Environments
Haili Wang, Jingda Guo, Xu Ma, Song Fu, Qing Yang, Yunzhong Xu
http://arxiv.org/abs/2111.08232v1
• [cs.DC]Project CGX: Scalable Deep Learning on Commodity GPUs
Ilia Markov, Hamidreza Ramezani, Dan Alistarh
http://arxiv.org/abs/2111.08617v1
• [cs.DC]Quo Vadis MPI RMA? Towards a More Efficient Use of MPI One-Sided Communication
Joseph Schuchart, Christoph Niethammer, José Gracia, George Bosilca
http://arxiv.org/abs/2111.08142v1
• [cs.DC]Saath: Speeding up CoFlows by Exploiting the Spatial Dimension
Akshay Jajoo, Rohan Gandhi, Y. Charlie Hu, Cheng-Kok Koh
http://arxiv.org/abs/2111.08572v1
• [cs.DC]Self-Stabilization and Byzantine Tolerance for Maximal Independent Set
Johanne Cohen, Laurence Pilard, Jonas Sénizergues
http://arxiv.org/abs/2111.08348v1
• [cs.DC]Task allocation for decentralized training in heterogeneous environment
Yongyue Chao, Mingxue Liao, Jiaxin Gao
http://arxiv.org/abs/2111.08272v1
• [cs.DL]Patent Data for Engineering Design: A Review
Shuo Jiang, Serhad Sarica, Binyang Song, Jie Hu, Jianxi Luo
http://arxiv.org/abs/2111.08500v1
• [cs.HC]Words of Wisdom: Representational Harms in Learning From AI Communication
Amanda Buddemeyer, Erin Walker, Malihe Alikhani
http://arxiv.org/abs/2111.08581v1
• [cs.IR]Pre-training Graph Neural Network for Cross Domain Recommendation
Chen Wang, Yueqing Liang, Zhiwei Liu, Tao Zhang, Philip S. Yu
http://arxiv.org/abs/2111.08268v1
• [cs.IR]QA4PRF: A Question Answering based Framework for Pseudo Relevance Feedback
Handong Ma, Jiawei Hou, Chenxu Zhu, Weinan Zhang, Ruiming Tang, Jincai Lai, Jieming Zhu, Xiuqiang He, Yong Yu
http://arxiv.org/abs/2111.08229v1
• [cs.IR]Utilizing Textual Reviews in Latent Factor Models for Recommender Systems
Tatev Karen Aslanyan, Flavius Frasincar
http://arxiv.org/abs/2111.08538v1
• [cs.IT]A Markov Chain Approach for Myopic Multi-hop Relaying: Outage and Diversity Analysis
Andreas Nicolaides, Constantinos Psomas, Ioannis Krikidis
http://arxiv.org/abs/2111.08296v1
• [cs.IT]A fixed latency ORBGRAND decoder architecture with LUT-aided error-pattern scheduling
Carlo Condo
http://arxiv.org/abs/2111.08134v1
• [cs.IT]Continuous-Aperture MIMO for Electromagnetic Information Theory
Zijian Zhang, Linglong Dai
http://arxiv.org/abs/2111.08630v1
• [cs.IT]Dense Circulant Lattices From Nonlinear Systems
William Lima da Silva Pinto, Carina Alves
http://arxiv.org/abs/2111.08084v1
• [cs.IT]Faster-than-Nyquist Asynchronous NOMA Outperforms Synchronous NOMA
Shuagyang Li, Zhiqiang Wei, Weijie Yuan, Jinhong Yuan, Baoming Bai, Derrick Wing Kwan Ng, Lajos Hanzo
http://arxiv.org/abs/2111.08258v1
• [cs.IT]Faster-than-Nyquist Signaling for MIMO Communications
Zichao Zhang, Melda Yuksel, Halim Yanikomeroglu
http://arxiv.org/abs/2111.07867v2
• [cs.IT]Generalization Bounds and Algorithms for Learning to Communicate over Additive Noise Channels
Nir Weinberger
http://arxiv.org/abs/2111.08253v1
• [cs.IT]Hybrid Beam Alignment for Multi-Path Channels: A Group Testing Viewpoint
Ozlem Yildiz, Abbas Khalili, Elza Erkip
http://arxiv.org/abs/2111.08159v1
• [cs.IT]Hybrid Reflection Modulation
Zehra Yigit, Ertugrul Basar, Miaowen Wen, Ibrahim Altunbas
http://arxiv.org/abs/2111.08355v1
• [cs.IT]Introduction to Set Shaping Theory
Solomon Kozlov
http://arxiv.org/abs/2111.08369v1
• [cs.IT]On Reverse Elastic Channels and the Asymmetry of Commitment Capacity under Channel Elasticity
Amitalok J. Budkuley, Pranav Joshi, Manideep Mamindlapally, Anuj Kumar Yadav
http://arxiv.org/abs/2111.08477v1
• [cs.IT]On The Number of Different Entries in Involutory MDS Matrices over Finite Fields of Characteristic Two
Muhammad Afifurrahman
http://arxiv.org/abs/2111.08352v1
• [cs.LG]A Unified and Fast Interpretable Model for Predictive Analytics
Rui Ding, Tianchi Qiao, Yunan Zhu, Zhitao Zou, Shi Han, Dongmei Zhang
http://arxiv.org/abs/2111.08255v1
• [cs.LG]Assessing Deep Neural Networks as Probability Estimators
Yu Pan, Kwo-Sen Kuo, Michael L. Rilee, Hongfeng Yu
http://arxiv.org/abs/2111.08239v1
• [cs.LG]Automatically detecting anomalous exoplanet transits
Christoph J. Hönes, Benjamin Kurt Miller, Ana M. Heras, Bernard H. Foing
http://arxiv.org/abs/2111.08679v1
• [cs.LG]Causal Effect Variational Autoencoder with Uniform Treatment
Daniel Jiwoong Im, Kyunghyun Cho, Narges Razavian
http://arxiv.org/abs/2111.08656v1
• [cs.LG]Comparative Analysis of Machine Learning Models for Predicting Travel Time
Armstrong Aboah, Elizabeth Arthur
http://arxiv.org/abs/2111.08226v1
• [cs.LG]Deep Distilling: automated code generation using explainable deep learning
Paul J. Blazek, Kesavan Venkatesh, Milo M. Lin
http://arxiv.org/abs/2111.08275v1
• [cs.LG]Exploiting Action Impact Regularity and Partially Known Models for Offline Reinforcement Learning
Vincent Liu, James Wright, Martha White
http://arxiv.org/abs/2111.08066v1
• [cs.LG]Fairness-aware Online Price Discrimination with Nonparametric Demand Models
Xi Chen, Xuan Zhang, Yuan Zhou
http://arxiv.org/abs/2111.08221v1
• [cs.LG]FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
Yuezhou Wu, Yan Kang, Jiahuan Luo, Yuanqin He, Qiang Yang
http://arxiv.org/abs/2111.08211v1
• [cs.LG]FedCostWAvg: A new averaging for better Federated Learning
Leon Mächler, Ivan Ezhov, Florian Kofler, Suprosanna Shit, Johannes C. Paetzold, Timo Loehr, Benedikt Wiestler, Bjoern Menze
http://arxiv.org/abs/2111.08649v1
• [cs.LG]Free Will Belief as a consequence of Model-based Reinforcement Learning
Erik M. Rehn
http://arxiv.org/abs/2111.08435v1
• [cs.LG]Grounding Psychological Shape Space in Convolutional Neural Networks
Lucas Bechberger, Kai-Uwe Kühnberger
http://arxiv.org/abs/2111.08409v1
• [cs.LG]HADFL: Heterogeneity-aware Decentralized Federated Learning Framework
Jing Cao, Zirui Lian, Weihong Liu, Zongwei Zhu, Cheng Ji
http://arxiv.org/abs/2111.08274v1
• [cs.LG]HiRID-ICU-Benchmark — A Comprehensive Machine Learning Benchmark on High-resolution ICU Data
Hugo Yèche, Rita Kuznetsova, Marc Zimmermann, Matthias Hüser, Xinrui Lyu, Martin Faltys, Gunnar Rätsch
http://arxiv.org/abs/2111.08536v1
• [cs.LG]Inference-Time Personalized Federated Learning
Ohad Amosy, Gal Eyal, Gal Chechik
http://arxiv.org/abs/2111.08356v1
• [cs.LG]Interpretable and Fair Boolean Rule Sets via Column Generation
Connor Lawless, Sanjeeb Dash, Oktay Gunluk, Dennis Wei
http://arxiv.org/abs/2111.08466v1
• [cs.LG]Interpreting Language Models Through Knowledge Graph Extraction
Vinitra Swamy, Angelika Romanou, Martin Jaggi
http://arxiv.org/abs/2111.08546v1
• [cs.LG]Inverse-Weighted Survival Games
Xintian Han, Mark Goldstein, Aahlad Puli, Thomas Wies, Adler J Perotte, Rajesh Ranganath
http://arxiv.org/abs/2111.08175v1
• [cs.LG]Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks
Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Mahmut T. Kandemir, Anand Sivasubramaniam
http://arxiv.org/abs/2111.08202v1
• [cs.LG]Learning Augmentation Distributions using Transformed Risk Minimization
Evangelos Chatzipantazis, Stefanos Pertigkiozoglou, Edgar Dobriban, Kostas Daniilidis
http://arxiv.org/abs/2111.08190v1
• [cs.LG]Learning Graph Neural Networks for Multivariate Time Series Anomaly Detection
Saswati Ray, Sana Lakdawala, Mononito Goswami, Chufan Gao
http://arxiv.org/abs/2111.08082v1
• [cs.LG]Machine Learning and Ensemble Approach Onto Predicting Heart Disease
Aaditya Surya
http://arxiv.org/abs/2111.08667v1
• [cs.LG]Machine Learning-Assisted Analysis of Small Angle X-ray Scattering
Piotr Tomaszewski, Shun Yu, Markus Borg, Jerk Rönnols
http://arxiv.org/abs/2111.08645v1
• [cs.LG]Margin-Independent Online Multiclass Learning via Convex Geometry
Guru Guruganesh, Allen Liu, Jon Schneider, Joshua Wang
http://arxiv.org/abs/2111.08057v1
• [cs.LG]Mathematical Models for Local Sensing Hashes
Li Wang, Lilon Wangner
http://arxiv.org/abs/2111.08344v1
• [cs.LG]MoRe-Fi: Motion-robust and Fine-grained Respiration Monitoring via Deep-Learning UWB Radar
Tianyue Zheng, Zhe Chen, Shujie Zhang, Chao Cai, Jun Luo
http://arxiv.org/abs/2111.08195v1
• [cs.LG]ModelLight: Model-Based Meta-Reinforcement Learning for Traffic Signal Control
Xingshuai Huang, Di Wu, Michael Jenkin, Benoit Boulet
http://arxiv.org/abs/2111.08067v1
• [cs.LG]Modular Networks Prevent Catastrophic Interference in Model-Based Multi-Task Reinforcement Learning
Robin Schiewer, Laurenz Wiskott
http://arxiv.org/abs/2111.08010v1
• [cs.LG]Multi-Centroid Hyperdimensional Computing Approach for Epileptic Seizure Detection
Una Pale, Tomas Teijeiro, David Atienza
http://arxiv.org/abs/2111.08463v1
• [cs.LG]Natural Gradient Variational Inference with Gaussian Mixture Models
Farzaneh Mahdisoltani
http://arxiv.org/abs/2111.08002v1
• [cs.LG]Neural networks with linear threshold activations: structure and algorithms
Sammy Khalife, Amitabh Basu
http://arxiv.org/abs/2111.08117v1
• [cs.LG]Neuron-based Pruning of Deep Neural Networks with Better Generalization using Kronecker Factored Curvature Approximation
Abdolghani Ebrahimi, Diego Klabjan
http://arxiv.org/abs/2111.08577v1
• [cs.LG]Non-separable Spatio-temporal Graph Kernels via SPDEs
Alexander Nikitin, ST John, Arno Solin, Samuel Kaski
http://arxiv.org/abs/2111.08524v1
• [cs.LG]Off-Policy Actor-Critic with Emphatic Weightings
Eric Graves, Ehsan Imani, Raksha Kumaraswamy, Martha White
http://arxiv.org/abs/2111.08172v1
• [cs.LG]On Bock’s Conjecture Regarding the Adam Optimizer
Mohamed Akrout, Douglas Tweed
http://arxiv.org/abs/2111.08162v1
• [cs.LG]On Effective Scheduling of Model-based Reinforcement Learning
Hang Lai, Jian Shen, Weinan Zhang, Yimin Huang, Xing Zhang, Ruiming Tang, Yong Yu, Zhenguo Li
http://arxiv.org/abs/2111.08550v1
• [cs.LG]Persia: A Hybrid System Scaling Deep Learning Based Recommenders up to 100 Trillion Parameters
Xiangru Lian, Binhang Yuan, Xuefeng Zhu, Yulong Wang, Yongjun He, Honghuan Wu, Lei Sun, Haodong Lyu, Chengjun Liu, Xing Dong, Yiqiao Liao, Mingnan Luo, Congfei Zhang, Jingru Xie, Haonan Li, Lei Chen, Renjie Huang, Jianying Lin, Chengchun Shu, Xuezhong Qiu, Zhishan Liu, Dongying Kong, Lei Yuan, Hai Yu, Sen Yang, Ce Zhang, Ji Liu
http://arxiv.org/abs/2111.05897v2
• [cs.LG]Phase function estimation from a diffuse optical image via deep learning
Yuxuan Liang, Chuang Niu, Chen Wei, Shenghan Ren, Wenxiang Cong, Ge Wang
http://arxiv.org/abs/2111.08227v1
• [cs.LG]Polymatrix Competitive Gradient Descent
Jeffrey Ma, Alistair Letcher, Florian Schäfer, Yuanyuan Shi, Anima Anandkumar
http://arxiv.org/abs/2111.08565v1
• [cs.LG]Rank-Regret Minimization
Xingxing Xiao, Jianzhong Li
http://arxiv.org/abs/2111.08563v1
• [cs.LG]Reinforcement Learning with Feedback from Multiple Humans with Diverse Skills
Taku Yamagata, Ryan McConville, Raul Santos-Rodriguez
http://arxiv.org/abs/2111.08596v1
• [cs.LG]Reshaping Smart Energy Transition: An analysis of human-building interactions in Qatar Using Machine Learning Techniques
Rateb Jabbar, Esmat Zaidan, Ahmed ben Said, Ali Ghofrani
http://arxiv.org/abs/2111.08333v1
• [cs.LG]Robust recovery for stochastic block models
Jingqiu Ding, Tommaso d’Orsi, Rajai Nasser, David Steurer
http://arxiv.org/abs/2111.08568v1
• [cs.LG]Robustness of Bayesian Neural Networks to White-Box Adversarial Attacks
Adaku Uchendu, Daniel Campoy, Christopher Menart, Alexandra Hildenbrandt
http://arxiv.org/abs/2111.08591v1
• [cs.LG]Selective Ensembles for Consistent Predictions
Emily Black, Klas Leino, Matt Fredrikson
http://arxiv.org/abs/2111.08230v1
• [cs.LG]Solving Linear Algebra by Program Synthesis
Iddo Drori, Nakul Verma
http://arxiv.org/abs/2111.08171v1
• [cs.LG]Solving Probability and Statistics Problems by Program Synthesis
Leonard Tang, Elizabeth Ke, Nikhil Singh, Nakul Verma, Iddo Drori
http://arxiv.org/abs/2111.08267v1
• [cs.LG]Switching Recurrent Kalman Networks
Giao Nguyen-Quynh, Philipp Becker, Chen Qiu, Maja Rudolph, Gerhard Neumann
http://arxiv.org/abs/2111.08291v1
• [cs.LG]Thoughts on the Consistency between Ricci Flow and Neural Network Behavior
Jun Chen, Tianxin Huang, Wenzhou Chen, Yong Liu
http://arxiv.org/abs/2111.08410v1
• [cs.LG]TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generation
Abhyuday Desai, Cynthia Freeman, Zuhui Wang, Ian Beaver
http://arxiv.org/abs/2111.08095v1
• [cs.LG]Towards Generating Real-World Time Series Data
Hengzhi Pei, Kan Ren, Yuqing Yang, Chang Liu, Tao Qin, Dongsheng Li
http://arxiv.org/abs/2111.08386v1
• [cs.LG]VisualEnv: visual Gym environments with Blender
Andrea Scorsoglio, Roberto Furfaro
http://arxiv.org/abs/2111.08096v1
• [cs.LG]Wyner-Ziv Gradient Compression for Federated Learning
Kai Liang, Huiru Zhong, Haoning Chen, Youlong Wu
http://arxiv.org/abs/2111.08277v1
• [cs.NE]A Multi-criteria Approach to Evolve Sparse Neural Architectures for Stock Market Forecasting
Faizal Hafiz, Jan Broekaert, Davide La Torre, Akshya Swain
http://arxiv.org/abs/2111.08060v1
• [cs.NI]CLARA: A Constrained Reinforcement Learning Based Resource Allocation Framework for Network Slicing
Yongshuai Liu, Jiaxin Ding, Zhi-Li Zhang, Xin Liu
http://arxiv.org/abs/2111.08397v1
• [cs.NI]Common Language for Goal-Oriented Semantic Communications: A Curriculum Learning Framework
Mohammad Karimzadeh Farshbafan, Walid Saad, Merouane Debbah
http://arxiv.org/abs/2111.08051v1
• [cs.NI]HyperNAT: Scaling Up Network AddressTranslation with SmartNICs for Clouds
Shaoke Fang, Qingsong Liu, Wenfei Wu
http://arxiv.org/abs/2111.08193v1
• [cs.NI]Learning Robust Scheduling with Search and Attention
David Sandberg, Tor Kvernvik, Francesco Davide Calabrese
http://arxiv.org/abs/2111.08073v1
• [cs.RO]2.5D Vehicle Odometry Estimation
Ciaran Eising, Leroy-Francisco Pereira, Jonathan Horgan, Anbuchezhiyan Selvaraju, John McDonald, Paul Moran
http://arxiv.org/abs/2111.08398v1
• [cs.RO]Active Vapor-Based Robotic Wiper
Takuya Kiyokawa, Hiroki Katayama, Jun Takamatsu
http://arxiv.org/abs/2111.08248v1
• [cs.RO]Analysis of Model-Free Reinforcement Learning Control Schemes on self-balancing Wheeled Extendible System
Kanishk ., Rushil Kumar, Vikas Rastogi, Ajeet Kumar
http://arxiv.org/abs/2111.08389v1
• [cs.RO]GRI: General Reinforced Imitation and its Application to Vision-Based Autonomous Driving
Raphael Chekroun, Marin Toromanoff, Sascha Hornauer, Fabien Moutarde
http://arxiv.org/abs/2111.08575v1
• [cs.RO]Hierarchical Topometric Representation of 3D Robotic Maps
ZhenpengHe, HaoSun, JiaweiHou, YajunHa, Sören Schwertfeger
http://arxiv.org/abs/2111.08283v1
• [cs.RO]Joint State and Input Estimation of Agent Based on Recursive Kalman Filter Given Prior Knowledge
Zida Wu, Zhaoliang Zheng, Ankur Mehta
http://arxiv.org/abs/2111.08091v1
• [cs.RO]Learning to Navigate in a VUCA Environment: Hierarchical Multi-expert Approach
Wenqi Zhang, Kai Zhao, Peng Li, Xiao Zhu, Faping Ye, Weijie Jiang, Huiqiao Fu, Tao Wang
http://arxiv.org/abs/2111.08364v1
• [cs.RO]Rearranging the Environment to Maximize Energy with a Robotic Circuit Drawing
Xianglong Tan, Zhikang Liu, Chen Yu, Andre Rosendo
http://arxiv.org/abs/2111.08147v1
• [cs.RO]Towards Real-Time Monocular Depth Estimation for Robotics: A Survey
Xingshuai Dong, Matthew A. Garratt, Sreenatha G. Anavatti, Hussein A. Abbass
http://arxiv.org/abs/2111.08600v1
• [cs.RO]Virtual Reality for Synergistic Surgical Training and Data Generation
Adnan Munawar, Zhaoshuo Li, Punit Kunjam, Nimesh Nagururu, Andy S. Ding, Peter Kazanzides, Thomas Looi, Francis X. Creighton, Russell H. Taylor, Mathias Unberath
http://arxiv.org/abs/2111.08097v1
• [cs.SE]Is CADP an Applicable Formal Method?
Hubert Garavel, Frédéric Lang, Radu Mateescu, Wendelin Serwe
http://arxiv.org/abs/2111.08203v1
• [cs.SI]Analysis of 5G academic Network based on graph representation learning method
Xiaoming Li, Guangquan Xu, Wei Yu, Pengfei Jiao, Xiangyu Song
http://arxiv.org/abs/2111.08264v1
• [cs.SI]Improving the performance of reputation evaluating by combining the structure of network and nonlinear recovery
Meng Li, Chengyuan Han, Yuanxiang Jiang, Zengru Di
http://arxiv.org/abs/2111.08092v1
• [cs.SI]Local News Online and COVID in the U.S.: Relationships among Coverage, Cases, Deaths, and Audience
Kenneth Joseph, Benjamin D. Horne, Jon Green, John P. Wihbey
http://arxiv.org/abs/2111.08515v1
• [econ.EM]Designing Representative and Balanced Experiments by Local Randomization
Max Cytrynbaum
http://arxiv.org/abs/2111.08157v1
• [econ.EM]Revisiting C.S.Peirce’s Experiment: 150 Years Later
Deep Mukhopadhyay
http://arxiv.org/abs/2111.08054v1
• [eess.AS]Attention-based Multi-hypothesis Fusion for Speech Summarization
Takatomo Kano, Atsunori Ogawa, Marc Delcroix, Shinji Watanabe
http://arxiv.org/abs/2111.08201v1
• [eess.AS]Single-channel speech separation using Soft-minimum Permutation Invariant Training
Midia Yousefi, John H. L. Hansen
http://arxiv.org/abs/2111.08635v1
• [eess.IV]A Latent Encoder Coupled Generative Adversarial Network (LE-GAN) for Efficient Hyperspectral Image Super-resolution
Yue Shi, Liangxiu Han, Lianghao Han, Sheng Chang, Tongle Hu, Darren Dancey
http://arxiv.org/abs/2111.08685v1
• [eess.IV]A layer-stress learning framework universally augments deep neural network tasks
Shihao Shao, Yong Liu, Qinghua Cui
http://arxiv.org/abs/2111.08597v1
• [eess.IV]Advancement of Deep Learning in Pneumonia and Covid-19 Classification and Localization: A Qualitative and Quantitative Analysis
Aakash Shah, Manan Shah
http://arxiv.org/abs/2111.08606v1
• [eess.IV]Disparities in Dermatology AI: Assessments Using Diverse Clinical Images
Roxana Daneshjou, Kailas Vodrahalli, Weixin Liang, Roberto A Novoa, Melissa Jenkins, Veronica Rotemberg, Justin Ko, Susan M Swetter, Elizabeth E Bailey, Olivier Gevaert, Pritam Mukherjee, Michelle Phung, Kiana Yekrang, Bradley Fong, Rachna Sahasrabudhe, James Zou, Albert Chiou
http://arxiv.org/abs/2111.08006v1
• [eess.IV]Image-specific Convolutional Kernel Modulation for Single Image Super-resolution
Yuanfei Huang, Jie Li, Yanting Hu, Xinbo Gao, Hua Huang
http://arxiv.org/abs/2111.08362v1
• [eess.IV]Online Meta Adaptation for Variable-Rate Learned Image Compression
Wei Jiang, Wei Wang, Songnan Li, Shan Liu
http://arxiv.org/abs/2111.08256v1
• [eess.IV]Solving Inverse Problems in Medical Imaging with Score-Based Generative Models
Yang Song, Liyue Shen, Lei Xing, Stefano Ermon
http://arxiv.org/abs/2111.08005v1
• [eess.SP]Blockage Prediction Using Wireless Signatures: Deep Learning Enables Real-World Demonstration
Shunyao Wu, Muhammad Alrabeiah, Chaitali Chakrabarti, Ahmed Alkhateeb
http://arxiv.org/abs/2111.08242v1
• [eess.SP]Deep Diffusion Models for Robust Channel Estimation
Marius Arvinte, Jonathan I Tamir
http://arxiv.org/abs/2111.08177v1
• [eess.SP]Human-error-potential Estimation based on Wearable Biometric Sensors
Hiroki Ohashi, Hiroto Nagayoshi
http://arxiv.org/abs/2111.08502v1
• [eess.SY]Graph neural network-based fault diagnosis: a review
Zhiwen Chen, Jiamin Xu, Cesare Alippi, Steven X. Ding, Yuri Shardt, Tao Peng, Chunhua Yang
http://arxiv.org/abs/2111.08185v1
• [math-ph]Second-order statistics of fermionic Gaussian states
Youyi Huang, Lu Wei
http://arxiv.org/abs/2111.08216v1
• [math.OC]Data-Driven Inpatient Bed Assignment Using the P Model
Shasha Han, Shuangchi He, Hong Choon Oh
http://arxiv.org/abs/2111.08269v1
• [math.OC]Learning Optimal Control with Stochastic Models of Hamiltonian Dynamics
Chandrajit Bajaj, Minh Nguyen
http://arxiv.org/abs/2111.08108v1
• [math.OC]Multiclass Optimal Classification Trees with SVM-splits
Víctor Blanco, Alberto Japón, Justo Puerto
http://arxiv.org/abs/2111.08674v1
• [math.OC]Stochastic Extragradient: General Analysis and Improved Rates
Eduard Gorbunov, Hugo Berard, Gauthier Gidel, Nicolas Loizou
http://arxiv.org/abs/2111.08611v1
• [math.PR]Prediction theory in continuous time
N. H. Bingham
http://arxiv.org/abs/2111.08560v1
• [math.ST]On Adaptive Confidence Sets for the Wasserstein Distances
Neil Deo, Thibault Randrianarisoa
http://arxiv.org/abs/2111.08505v1
• [math.ST]Properties of linear spectral statistics of frequency-smoothed estimated spectral coherence matrix of high-dimensional Gaussian time series
Philippe Loubaton, Alexis Rosuel
http://arxiv.org/abs/2111.08047v1
• [math.ST]Quantification of fracture roughness by change probabilities and Hurst exponents
Tim Gutjahr, Sina Hale, Karsten Keller, Philipp Blum, Steffen Winter
http://arxiv.org/abs/2111.08661v1
• [physics.comp-ph]Normalizing flows for atomic solids
Peter Wirnsberger, George Papamakarios, Borja Ibarz, Sébastien Racanière, Andrew J. Ballard, Alexander Pritzel, Charles Blundell
http://arxiv.org/abs/2111.08696v1
• [physics.flu-dyn]Global Sensitivity Analysis of Four Chamber Heart Hemodynamics Using Surrogate Models
Elias Karabelas, Stefano Longobardi, Jana Fuchsberger, Orod Razeghi, Cristobal Rodero, Marina Strocchi, Ronak Rajani, Gundolf Haase, Gernot Plank, Steven Niederer
http://arxiv.org/abs/2111.08339v1
• [physics.plasm-ph]Tracking Blobs in the Turbulent Edge Plasma of Tokamak Fusion Reactors
Woonghee Han, Randall A. Pietersen, Rafael Villamor-Lora, Matthew Beveridge, Nicola Offeddu, Theodore Golfinopoulos, Christian Theiler, James L. Terry, Earl S. Marmar, Iddo Drori
http://arxiv.org/abs/2111.08570v1
• [q-bio.QM]Code-free development and deployment of deep segmentation models for digital pathology
Henrik Sahlin Pettersen, Ilya Belevich, Elin Synnøve Røyset, Erik Smistad, Eija Jokitalo, Ingerid Reinertsen, Ingunn Bakke, André Pedersen
http://arxiv.org/abs/2111.08430v1
• [quant-ph]Tensor network to learn the wavefunction of data
Anatoly Dymarsky, Kirill Pavlenko
http://arxiv.org/abs/2111.08014v1
• [stat.AP]An Empirical Evaluation of the Impact of New York’s Bail Reform on Crime Using Synthetic Controls
Angela Zhou, Andrew Koo, Nathan Kallus, Rene Ropac, Richard Peterson, Stephen Koppel, Tiffany Bergin
http://arxiv.org/abs/2111.08664v1
• [stat.AP]Bayesian inference of the climbing grade scale
Alexei Drummond, Alex Popinga
http://arxiv.org/abs/2111.08140v1
• [stat.AP]Bayesian, frequentist and fiducial intervals for the difference between two binomial proportions
Lizanne Raubenheimer
http://arxiv.org/abs/2111.08610v1
• [stat.AP]Hierarchical transfer learning with applications for electricity load forecasting
Solenne Gaucher, Yannig Goude, Anestis Antoniadis
http://arxiv.org/abs/2111.08512v1
• [stat.AP]Joint Estimation of Extreme Precipitation at Different Spatial Scales through Mixture Modelling
Jordan Richards, Jonathan A. Tawn, Simon J. Brown
http://arxiv.org/abs/2111.08469v1
• [stat.AP]Neuro-Hotnet: A Graph Theoretic Approach for Brain FC Estimation
Nathan Tung, Eli Upfal, Jerome Sanes, Ani Eloyan
http://arxiv.org/abs/2111.08118v1
• [stat.AP]Regional Topics in British Grocery Retail Transactions
Mariflor Vega Carrasco, Mirco Musolesi, Jason O’Sullivan, Rosie Prior, Ioanna Manolopoulou
http://arxiv.org/abs/2111.08078v1
• [stat.ME]Change-point detection for density sequence extracted from SHM data, with application to distributional information break diagnosis encountered in structural condition assessment
Xinyi Lei, Zhicheng Chen, Hui Li, Shiyin Wei
http://arxiv.org/abs/2111.08260v1
• [stat.ME]Inference for extreme spatial temperature events in a changing climate with application to Ireland
Dáire Healy, Andrew Parnell, Peter Thorne, Jonathan Tawn
http://arxiv.org/abs/2111.08616v1
• [stat.ME]Multi-Parameter Regression Survival Modelling with Random Effects
Fatima-Zahra Jaouimaa, Il Do Ha, Kevin Burke
http://arxiv.org/abs/2111.08573v1
• [stat.ME]Sequential Unequal Probability Sampling For Stream Population
Bardia Panahbehagh, Raphaël Jauslin, Yves Tillé
http://arxiv.org/abs/2111.08433v1
• [stat.ME]Simultaneous inference of correlated marginal tests using intersection-union or union-intersection test principle
Ludwig A. Hothorn
http://arxiv.org/abs/2111.08694v1
• [stat.ME]Translating questions to estimands in randomized clinical trials with intercurrent events
Mats J. Stensrud, Oliver Dukes
http://arxiv.org/abs/2111.08509v1
• [stat.ML]An adaptive dimension reduction algorithm for latent variables of variational autoencoder
Yiran Dong, Chuanhou Gao
http://arxiv.org/abs/2111.08493v1
• [stat.ML]Bayesian Optimization for Cascade-type Multi-stage Processes
Shunya Kusakawa, Shion Takeno, Yu Inatsu, Kentaro Kutsukake, Shogo Iwazaki, Takashi Nakano, Toru Ujihara, Masayuki Karasuyama, Ichiro Takeuchi
http://arxiv.org/abs/2111.08330v1
• [stat.ML]Covariate Shift in High-Dimensional Random Feature Regression
Nilesh Tripuraneni, Ben Adlam, Jeffrey Pennington
http://arxiv.org/abs/2111.08234v1
• [stat.ML]Distribution Compression in Near-Linear Time
Abhishek Shetty, Raaz Dwivedi, Lester Mackey
http://arxiv.org/abs/rg/abs/2111.07941v1
• [stat.ML]Learning with convolution and pooling operations in kernel methods
Theodor Misiakiewicz, Song Mei
http://arxiv.org/abs/2111.08308v1
• [stat.ML]SStaGCN: Simplified stacking based graph convolutional networks
Jia Cai, Zhilong Xiong, Shaogao Lv
http://arxiv.org/abs/2111.08228v1
• [stat.ML]Sequential Community Mode Estimation
Shubham Anand Jain, Shreyas Goenka, Divyam Bapna, Nikhil Karamchandani, Jayakrishnan Nair
http://arxiv.org/abs/2111.08535v1
• [stat.ML]Sparse Graph Learning Under Laplacian-Related Constraints
Jitendra K. Tugnait
http://arxiv.org/abs/2111.08161v1