astro-ph.CO - 宇宙学和天体物理学
cs.AI - 人工智能
cs.AR - 硬件体系结构
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.CY - 计算与社会
cs.DC - 分布式、并行与集群计算
cs.DL - 数字图书馆
cs.DS - 数据结构与算法
cs.GT - 计算机科学与博弈论
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.SD - 声音处理
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.DS - 动力系统
math.OC - 优化与控制
math.PR - 概率
math.ST - 统计理论
physics.flu-dyn - 流体动力学
physics.plasm-ph - 等离子体物理
q-bio.QM - 定量方法
q-fin.RM - 风险管理
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]Inferring dark matter substructure with astrometric lensing beyond the power spectrum
• [cs.AI]A Table-Based Representation for Probabilistic Logic: Preliminary Results
• [cs.AI]An Ample Approach to Data and Modeling
• [cs.AI]Compression, The Fermi Paradox and Artificial Super-Intelligence
• [cs.AI]Debiased Graph Contrastive Learning
• [cs.AI]Deep Synoptic Monte Carlo Planning in Reconnaissance Blind Chess
• [cs.AI]Empowering Local Communities Using Artificial Intelligence
• [cs.AI]SMProbLog: Stable Model Semantics in ProbLog and its Applications in Argumentation
• [cs.AI]The Artificial Scientist: Logicist, Emergentist, and Universalist Approaches to Artificial General Intelligence
• [cs.AI]Thinking Fast and Slow in AI: the Role of Metacognition
• [cs.AR]Benchmarking Memory-Centric Computing Systems: Analysis of Real Processing-in-Memory Hardware
• [cs.AR]RASA: Efficient Register-Aware Systolic Array Matrix Engine for CPU
• [cs.CL]A Survey On Neural Word Embeddings
• [cs.CL]ASR Rescoring and Confidence Estimation with ELECTRA
• [cs.CL]Analyzing the Impact of COVID-19 on Economy from the Perspective of Users Reviews
• [cs.CL]AraCOVID19-SSD: Arabic COVID-19 Sentiment and Sarcasm Detection Dataset
• [cs.CL]ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts
• [cs.CL]Data Augmentation Approaches in Natural Language Processing: A Survey
• [cs.CL]DistilHuBERT: Speech Representation Learning by Layer-wise Distillation of Hidden-unit BERT
• [cs.CL]Exploiting Twitter as Source of Large Corpora of Weakly Similar Pairs for Semantic Sentence Embeddings
• [cs.CL]FoodChem: A food-chemical relation extraction model
• [cs.CL]Investigating the Impact of Pre-trained Language Models on Dialog Evaluation
• [cs.CL]LawSum: A weakly supervised approach for Indian Legal Document Summarization
• [cs.CL]Learning Sense-Specific Static Embeddings using Contextualised Word Embeddings as a Proxy
• [cs.CL]MoEfication: Conditional Computation of Transformer Models for Efficient Inference
• [cs.CL]NaRLE: Natural Language Models using Reinforcement Learning with Emotion Feedback
• [cs.CL]Neural Transition System for End-to-End Opinion Role Labeling
• [cs.CL]On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation
• [cs.CL]Privacy enabled Financial Text Classification using Differential Privacy and Federated Learning
• [cs.CL]Rerunning OCR — A Machine Learning Approach to Quality Assessment and Enhancement Prediction
• [cs.CL]Revisiting Self-Training for Few-Shot Learning of Language Model
• [cs.CL]Sicilian Translator: A Recipe for Low-Resource NMT
• [cs.CL]TENT: Text Classification Based on ENcoding Tree Learning
• [cs.CL]TLDR9+: A Large Scale Resource for Extreme Summarization of Social Media Posts
• [cs.CL]Teach Me What to Say and I Will Learn What to Pick: Unsupervised Knowledge Selection Through Response Generation with Pretrained Generative Models
• [cs.CL]Truth-Conditional Captioning of Time Series Data
• [cs.CL]Using Psuedolabels for training Sentiment Classifiers makes the model generalize better across datasets
• [cs.CL]ur-iw-hnt at GermEval 2021: An Ensembling Strategy with Multiple BERT Models
• [cs.CR]Adversarial Robustness Verification and Attack Synthesis in Stochastic Systems
• [cs.CR]Blockchain-based Federated Learning: A Comprehensive Survey
• [cs.CR]Dataset: Large-scale Urban IoT Activity Data for DDoS Attack Emulation
• [cs.CR]Differential Privacy of Dirichlet Posterior Sampling
• [cs.CR]Machine learning attack on copy detection patterns: are 1x1 patterns cloneable?
• [cs.CV]: High-resolution multi-shot video editing
• [cs.CV]A Methodology to Identify Cognition Gaps in Visual Recognition Applications Based on Convolutional Neural Networks
• [cs.CV]Adversarial Attacks on Black Box Video Classifiers: Leveraging the Power of Geometric Transformations
• [cs.CV]An Experimental Evaluation on Deepfake Detection using Deep Face Recognition
• [cs.CV]An Integrated System for Mobile Image-Based Dietary Assessment
• [cs.CV]Anchor-free Oriented Proposal Generator for Object Detection
• [cs.CV]De-rendering Stylized Texts
• [cs.CV]Deep Instance Segmentation with High-Resolution Automotive Radar
• [cs.CV]Deep Learning Approach Protecting Privacy in Camera-Based Critical Applications
• [cs.CV]Efficient Modelling Across Time of Human Actions and Interactions
• [cs.CV]FooDI-ML: a large multi-language dataset of food, drinks and groceries images and descriptions
• [cs.CV]Frequency Aware Face Hallucination Generative Adversarial Network with Semantic Structural Constraint
• [cs.CV]HDR-cGAN: Single LDR to HDR Image Translation using Conditional GAN
• [cs.CV]HighlightMe: Detecting Highlights from Human-Centric Videos
• [cs.CV]How You Move Your Head Tells What You Do: Self-supervised Video Representation Learning with Egocentric Cameras and IMU Sensors
• [cs.CV]Investigating Fairness of Ocular Biometrics Among Young, Middle-Aged, and Older Adults
• [cs.CV]Let there be a clock on the beach: Reducing Object Hallucination in Image Captioning
• [cs.CV]MetaPix: Domain Transfer for Semantic Segmentation by Meta Pixel Weighting
• [cs.CV]Mix3D: Out-of-Context Data Augmentation for 3D Scenes
• [cs.CV]MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer
• [cs.CV]Multi-Object Tracking with Deep Learning Ensemble for Unmanned Aerial System Applications
• [cs.CV]Pixel-Level Bijective Matching for Video Object Segmentation
• [cs.CV]Procedure Planning in Instructional Videosvia Contextual Modeling and Model-based Policy Learning
• [cs.CV]Quantified Facial Expressiveness for Affective Behavior Analytics
• [cs.CV]RapidAI4EO: A Corpus for Higher Spatial and Temporal Reasoning
• [cs.CV]Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation
• [cs.CV]Spatial Context Awareness for Unsupervised Change Detection in Optical Satellite Images
• [cs.CV]Structured Bird’s-Eye-View Traffic Scene Understanding from Onboard Images
• [cs.CV]UHP-SOT: An Unsupervised High-Performance Single Object Tracker
• [cs.CV]VTAMIQ: Transformers for Attention Modulated Image Quality Assessment
• [cs.CV]Waypoint Models for Instruction-guided Navigation in Continuous Environments
• [cs.CY]Multimodal datasets: misogyny, pornography, and malignant stereotypes
• [cs.CY]Social Co-OS: Cyber-Human Social Co-Operating System
• [cs.CY]Traffic control Management System and Collision Avoidance System
• [cs.DC]A Community Roadmap for Scientific Workflows Research and Development
• [cs.DC]Crashworthiness design of 3D lattice-structure filled thin-walled tubes based on data mining
• [cs.DC]Cuttlefish: Library for Achieving Energy Efficiency in Multicore Parallel Programs
• [cs.DC]Learning, Computing, and Trustworthiness in Intelligent IoT Environments: Performance-Energy Tradeoffs
• [cs.DC]Local certification of MSO properties for bounded treedepth graphs
• [cs.DC]S2 Reducer: High-Performance Sparse Communication to Accelerate Distributed Deep Learning
• [cs.DL]Emerging trends and collaboration patterns unveil the scientific production in blockchain technology: A bibliometric and network analysis from 2014-2020
• [cs.DS]Inferring Hidden Structures in Random Graphs
• [cs.DS]Random Subgraph Detection Using Queries
• [cs.GT]Differentiable Equilibrium Computation with Decision Diagrams for Stackelberg Models of Combinatorial Congestion Games
• [cs.HC]AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts
• [cs.HC]Analysis of the relation between smartphone usage changes during the COVID-19 pandemic and usage preferences on apps
• [cs.IR]OPAD: An Optimized Policy-based Active Learning Framework for Document Content Analysis
• [cs.IR]Reddit-TUDFE: practical tool to explore Reddit usability in data science and knowledge processing
• [cs.IR]SDR: Efficient Neural Re-ranking using Succinct Document Representation
• [cs.IR]Voice Information Retrieval In Collaborative Information Seeking
• [cs.IT]A Modified Q-Learning Algorithm for Rate-Profiling of Polarization Adjusted Convolutional (PAC) Codes
• [cs.IT]Analysis and Optimization of HARQ for URLLC
• [cs.IT]Cellular Network Radio Propagation Modeling with Deep Convolutional Neural Networks
• [cs.IT]Enabling Cell-Free Massive MIMO Systems with Wireless Millimeter Wave Fronthaul
• [cs.IT]Lifted Reed-Solomon Codes and Lifted Multiplicity Codes
• [cs.IT]On bases and the dimensions of twisted centralizer codes
• [cs.IT]On the Maximum Achievable Sum-rate of the RIS-aided MIMO Broadcast Channel
• [cs.IT]On the Properties of Error Patterns in the Constant Lee Weight Channel
• [cs.IT]Pilot Decontamination Processing in Cell-Free Massive MIMO
• [cs.IT]Rate Splitting Multiple Access for Semi-Grant-Free Transmissions
• [cs.IT]Simultaneous Information and Energy Transmission with Finite Constellations
• [cs.IT]Time-Based Quantization for FRI and Bandlimited signals
• [cs.LG]-UQ: Accurate Uncertainty Quantification via Anchor Marginalization
• [cs.LG]A Critique of Strictly Batch Imitation Learning
• [cs.LG]A manifold learning approach for gesture identification from micro-Doppler radar measurements
• [cs.LG]A new harmonium for pattern recognition in survival data
• [cs.LG]AdjointBackMapV2: Precise Reconstruction of Arbitrary CNN Unit’s Activation via Adjoint Operators
• [cs.LG]An Efficient Anomaly Detection Approach using Cube Sampling with Streaming Data
• [cs.LG]An energy-based model for neuro-symbolic reasoning on knowledge graphs
• [cs.LG]Attaining Interpretability in Reinforcement Learning via Hierarchical Primitive Composition
• [cs.LG]Attention Augmented Convolutional Transformer for Tabular Time-series
• [cs.LG]Autoregressive Diffusion Models
• [cs.LG]Bottom-up Hierarchical Classification Using Confusion-based Logit Compression
• [cs.LG]CARL: A Benchmark for Contextual and Adaptive Reinforcement Learning
• [cs.LG]Combining Physics and Deep Learning to learn Continuous-Time Dynamics Models
• [cs.LG]Cross-Modal Virtual Sensing for Combustion Instability Monitoring
• [cs.LG]Deep Neural Networks and Tabular Data: A Survey
• [cs.LG]Distribution Mismatch Correction for Improved Robustness in Deep Neural Networks
• [cs.LG]Dropout Q-Functions for Doubly Efficient Reinforcement Learning
• [cs.LG]Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication
• [cs.LG]Exploring the Limits of Large Scale Pre-training
• [cs.LG]Federating for Learning Group Fair Models
• [cs.LG]Global Convergence and Stability of Stochastic Gradient Descent
• [cs.LG]Graph Coloring: Comparing Cluster Graphs to Factor Graphs
• [cs.LG]HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization
• [cs.LG]Hypernetworks for Continual Semi-Supervised Learning
• [cs.LG]Improved architectures and training algorithms for deep operator networks
• [cs.LG]Inductive learning for product assortment graph completion
• [cs.LG]Information-theoretic generalization bounds for black-box learning algorithms
• [cs.LG]Label differential privacy via clustering
• [cs.LG]Learning to shortcut and shortlist order fulfillment deciding
• [cs.LG]Multi-Objective Few-shot Learning for Fair Classification
• [cs.LG]Multi-axis Attentive Prediction for Sparse EventData: An Application to Crime Prediction
• [cs.LG]NeurWIN: Neural Whittle Index Network For Restless Bandits Via Deep RL
• [cs.LG]Noisy Feature Mixup
• [cs.LG]Optimal N-ary ECOC Matrices for Ensemble Classification
• [cs.LG]Optimization with Constraint Learning: A Framework and Survey
• [cs.LG]Pre-Quantized Deep Learning Models Codified in ONNX to Enable Hardware/Software Co-Design
• [cs.LG]Rapid training of deep neural networks without skip connections or normalization layers using Deep Kernel Shaping
• [cs.LG]Robust Linear Classification from Limited Training Data
• [cs.LG]Secure Aggregation for Buffered Asynchronous Federated Learning
• [cs.LG]Semi-Supervised Deep Learning for Multiplex Networks
• [cs.LG]Short-term precipitation prediction using deep learning
• [cs.LG]TensorPlan and the Few Actions Lower Bound for Planning in MDPs under Linear Realizability of Optimal Value Functions
• [cs.LG]Top-N: Equivariant set and graph generation without exchangeability
• [cs.LG]Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble
• [cs.LG]When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint
• [cs.NE]Neural Network Adversarial Attack Method Based on Improved Genetic Algorithm
• [cs.NE]Solving even-parity problems using traceless genetic programming
• [cs.NI]DeepEdge: A Deep Reinforcement Learning based Task Orchestrator for Edge Computing
• [cs.NI]On-Demand Networking for Ubiquitous Connectivity and Network Resilience: A Network-in-a-Box Solution
• [cs.RO]AEROS: Adaptive RObust least-Squares for Graph-Based SLAM
• [cs.RO]AquaVis: A Perception-Aware Autonomous Navigation Framework for Underwater Vehicles
• [cs.RO]CNN-based Human Detection for UAVs in Search and Rescue
• [cs.RO]Continuous-Time Fitted Value Iteration for Robust Policies
• [cs.RO]Deep Reinforcement Learning for Decentralized Multi-Robot Exploration with Macro Actions
• [cs.RO]Deep reinforcement learning for guidewire navigation in coronary artery phantom
• [cs.RO]Design and Characterization of a 3D-printed Pneumatically-driven Bistable Valve with Tunable Characteristics
• [cs.RO]Fessonia: a Method for Real-Time Estimation of Human Operator Workload Using Behavioural Entropy
• [cs.RO]Fully Self-Supervised Class Awareness in Dense Object Descriptors
• [cs.RO]Guiding Evolutionary Strategies by Differentiable Robot Simulators
• [cs.RO]Hybrid Event Shaping to Stabilize Periodic Hybrid Orbits
• [cs.RO]Improved Reinforcement Learning Coordinated Control of a Mobile Manipulator using Joint Clamping
• [cs.RO]Inverse Kinematics and Dexterous Workspace Formulation for 2-Segment Continuum Robots with Inextensible Segments
• [cs.RO]LLOL: Low-Latency Odometry for Spinning Lidars
• [cs.RO]Learned Uncertainty Calibration for Visual Inertial Localization
• [cs.RO]Mapless Navigation: Learning UAVs Motion forExploration of Unknown Environments
• [cs.RO]Motion Control of Redundant Robots with Generalised Inequality Constraints
• [cs.RO]Season-invariant GNSS-denied visual localization for UAVs
• [cs.RO]Set-theoretic Localization for Mobile Robots with Infrastructure-based Sensing
• [cs.SD]Sound Event Detection Transformer: An Event-based End-to-End Model for Sound Event Detection
• [cs.SE]LogDP: Combining Dependency and Proximity for Log-based Anomaly Detection
• [cs.SI]Extracting Major Topics of COVID-19 Related Tweets
• [cs.SI]Structural Models of Human Social Interactions in Online Smart Communities: the Case of Region-based Journalists on Twitter
• [econ.EM]A New Multivariate Predictive Model for Stock Returns
• [eess.AS]Speech Technology for Everyone: Automatic Speech Recognition for Non-Native English with Transfer Learning
• [eess.IV]DA-DRN: Degradation-Aware Deep Retinex Network for Low-Light Image Enhancement
• [eess.IV]Deep Subspace analysing for Semi-Supervised multi-label classification of Diabetic Foot Ulcer
• [eess.IV]Double Encoder-Decoder Networks for Gastrointestinal Polyp Segmentation
• [eess.IV]Proxy-bridged Image Reconstruction Network for Anomaly Detection in Medical Images
• [eess.IV]Self-Supervised Learning of Perceptually Optimized Block Motion Estimates for Video Compression
• [eess.IV]Transfer Learning U-Net Deep Learning for Lung Ultrasound Segmentation
• [eess.SP]Seizure Classification Using Parallel Genetic Naive Bayes Classifiers
• [eess.SP]Wireless Link Scheduling via Graph Representation Learning: A Comparative Study of Different Supervision Levels
• [eess.SY]Controlled-Variable Selection based on Chaos Theory for the Tennessee Eastman Plant
• [eess.SY]Learning to Solve the AC Optimal Power Flow via a Lagrangian Approach
• [math.DS]Data-driven Nonlinear Model Reduction to Spectral Submanifolds in Mechanical Systems
• [math.OC]A study of first-passage time minimization via Q-learning in heated gridworlds
• [math.OC]Joint optimization of sales-mix and generation plan for a large electricity producer
• [math.OC]KKT Conditions, First-Order and Second-Order Optimization, and Distributed Optimization: Tutorial and Survey
• [math.PR]The Rescaled Polya Urn and the Wright-Fisher process with mutation
• [math.ST]A Review of Brown 1971 (in)admissibility results under scale mixtures of Gaussian priors
• [math.ST]Estimation and Concentration of Missing Mass of Functions of Discrete Probability Distributions
• [math.ST]Exponential confidence region based on the projection density estimate. Recursivity of these estimations
• [math.ST]Robust censored regression with l1-norm regularization
• [physics.flu-dyn]Applying Machine Learning to Study Fluid Mechanics
• [physics.flu-dyn]The Potential of Machine Learning to Enhance Computational Fluid Dynamics
• [physics.plasm-ph]Inference and De-Noising of Non-Gaussian Particle Distribution Functions: A Generative Modeling Approach
• [q-bio.QM]Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation
• [q-fin.RM]Predicting Credit Risk for Unsecured Lending: A Machine Learning Approach
• [quant-ph]Feasible Architecture for Quantum Fully Convolutional Networks
• [quant-ph]Lossy compression of statistical data using quantum annealer
• [stat.AP]Evaluating the impact of local tracing partnerships on the performance of contact tracing for COVID-19 in England
• [stat.AP]Multilevel models with random residual variances for joint modelling school value-added effects on the mean and variance of student achievement
• [stat.AP]Parametric study of E. coli incidence with reference to the New Zealand freshwater standards and the Manawatū-Whanganui region
• [stat.AP]The Quality of the 2020 Census: An Independent Assessment of Census Bureau Activities Critical to Data Quality
• [stat.ME]Beware the Gini Index! A New Inequality Measure
• [stat.ME]When can relative risks provide causal estimates?
• [stat.ML]Classification of high-dimensional data with spiked covariance matrix structure
• [stat.ML]Estimating Potential Outcome Distributions with Collaborating Causal Networks
• [stat.ML]Permute Me Softly: Learning Soft Permutations for Graph Representations
• [stat.ML]Random matrices in service of ML footprint: ternary random features with no performance loss
• [stat.ML]Stochastic functional analysis with applications to robust machine learning
·····································
• [astro-ph.CO]Inferring dark matter substructure with astrometric lensing beyond the power spectrum
Siddharth Mishra-Sharma
http://arxiv.org/abs/2110.01620v1
• [cs.AI]A Table-Based Representation for Probabilistic Logic: Preliminary Results
Simon Vandevelde, Victor Verreet, Luc De Raedt, Joost Vennekens
http://arxiv.org/abs/2110.01909v1
• [cs.AI]An Ample Approach to Data and Modeling
Luciano da F. Costa
http://arxiv.org/abs/2110.01776v1
• [cs.AI]Compression, The Fermi Paradox and Artificial Super-Intelligence
Michael Timothy Bennett
http://arxiv.org/abs/2110.01835v1
• [cs.AI]Debiased Graph Contrastive Learning
Jun Xia, Lirong Wu, Jintao Chen, Ge Wang, Stan Z. Li
http://arxiv.org/abs/2110.02027v1
• [cs.AI]Deep Synoptic Monte Carlo Planning in Reconnaissance Blind Chess
Gregory Clark
http://arxiv.org/abs/2110.01810v1
• [cs.AI]Empowering Local Communities Using Artificial Intelligence
Yen-Chia Hsu, Ting-Hao ‘Kenneth’ Huang, Himanshu Verma, Andrea Mauri, Illah Nourbakhsh, Alessandro Bozzon
http://arxiv.org/abs/2110.02007v1
• [cs.AI]SMProbLog: Stable Model Semantics in ProbLog and its Applications in Argumentation
Pietro Totis, Angelika Kimmig, Luc De Raedt
http://arxiv.org/abs/2110.01990v1
• [cs.AI]The Artificial Scientist: Logicist, Emergentist, and Universalist Approaches to Artificial General Intelligence
Michael Timothy Bennett, Yoshihiro Maruyama
http://arxiv.org/abs/2110.01831v1
• [cs.AI]Thinking Fast and Slow in AI: the Role of Metacognition
Marianna Bergamaschi Ganapini, Murray Campbell, Francesco Fabiano, Lior Horesh, Jon Lenchner, Andrea Loreggia, Nicholas Mattei, Francesca Rossi, Biplav Srivastava, Kristen Brent Venable
http://arxiv.org/abs/2110.01834v1
• [cs.AR]Benchmarking Memory-Centric Computing Systems: Analysis of Real Processing-in-Memory Hardware
Juan Gómez-Luna, Izzat El Hajj, Ivan Fernandez, Christina Giannoula, Geraldo F. Oliveira, Onur Mutlu
http://arxiv.org/abs/2110.01709v1
• [cs.AR]RASA: Efficient Register-Aware Systolic Array Matrix Engine for CPU
Geonhwa Jeong, Eric Qin, Ananda Samajdar, Christopher J. Hughes, Sreenivas Subramoney, Hyesoon Kim, Tushar Krishna
http://arxiv.org/abs/2110.01752v1
• [cs.CL]A Survey On Neural Word Embeddings
Erhan Sezerer, Selma Tekir
http://arxiv.org/abs/2110.01804v1
• [cs.CL]ASR Rescoring and Confidence Estimation with ELECTRA
Hayato Futami, Hirofumi Inaguma, Masato Mimura, Shinsuke Sakai, Tatsuya Kawahara
http://arxiv.org/abs/2110.01857v1
• [cs.CL]Analyzing the Impact of COVID-19 on Economy from the Perspective of Users Reviews
Fatemeh Salmani, Hamed Vahdat-Nejad, Hamideh Hajiabadi
http://arxiv.org/abs/2110.02198v1
• [cs.CL]AraCOVID19-SSD: Arabic COVID-19 Sentiment and Sarcasm Detection Dataset
Mohamed Seghir Hadj Ameur, Hassina Aliane
http://arxiv.org/abs/2110.01948v1
• [cs.CL]ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts
Yuta Koreeda, Christopher D. Manning
http://arxiv.org/abs/2110.01799v1
• [cs.CL]Data Augmentation Approaches in Natural Language Processing: A Survey
Bohan Li, Yutai Hou, Wanxiang Che
http://arxiv.org/abs/2110.01852v1
• [cs.CL]DistilHuBERT: Speech Representation Learning by Layer-wise Distillation of Hidden-unit BERT
Heng-Jui Chang, Shu-wen Yang, Hung-yi Lee
http://arxiv.org/abs/2110.01900v1
• [cs.CL]Exploiting Twitter as Source of Large Corpora of Weakly Similar Pairs for Semantic Sentence Embeddings
Marco Di Giovanni, Marco Brambilla
http://arxiv.org/abs/2110.02030v1
• [cs.CL]FoodChem: A food-chemical relation extraction model
Gjorgjina Cenikj, Barbara Koroušić Seljak, Tome Eftimov
http://arxiv.org/abs/2110.02019v1
• [cs.CL]Investigating the Impact of Pre-trained Language Models on Dialog Evaluation
Chen Zhang, Luis Fernando D’Haro, Yiming Chen, Thomas Friedrichs, Haizhou Li
http://arxiv.org/abs/2110.01895v1
• [cs.CL]LawSum: A weakly supervised approach for Indian Legal Document Summarization
Vedant Parikh, Vidit Mathur, Parth Metha, Namita Mittal, Prasenjit Majumder
http://arxiv.org/abs/2110.01188v2
• [cs.CL]Learning Sense-Specific Static Embeddings using Contextualised Word Embeddings as a Proxy
Yi Zhou, Danushka Bollegala
http://arxiv.org/abs/2110.02204v1
• [cs.CL]MoEfication: Conditional Computation of Transformer Models for Efficient Inference
Zhengyan Zhang, Yankai Lin, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou
http://arxiv.org/abs/2110.01786v1
• [cs.CL]NaRLE: Natural Language Models using Reinforcement Learning with Emotion Feedback
Ruijie Zhou, Soham Deshmukh, Jeremiah Greer, Charles Lee
http://arxiv.org/abs/2110.02148v1
• [cs.CL]Neural Transition System for End-to-End Opinion Role Labeling
Shengqiong Wu, Donghong Ji
http://arxiv.org/abs/2110.02001v1
• [cs.CL]On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation
Xuebo Liu, Longyue Wang, Derek F. Wong, Liang Ding, Lidia S. Chao, Shuming Shi, Zhaopeng Tu
http://arxiv.org/abs/2110.01811v1
• [cs.CL]Privacy enabled Financial Text Classification using Differential Privacy and Federated Learning
Priyam Basu, Tiasa Singha Roy, Rakshit Naidu, Zumrut Muftuoglu
http://arxiv.org/abs/2110.01643v1
• [cs.CL]Rerunning OCR — A Machine Learning Approach to Quality Assessment and Enhancement Prediction
Pit Schneider
http://arxiv.org/abs/2110.01661v1
• [cs.CL]Revisiting Self-Training for Few-Shot Learning of Language Model
Yiming Chen, Yan Zhang, Chen Zhang, Grandee Lee, Ran Cheng, Haizhou Li
http://arxiv.org/abs/2110.01256v1
• [cs.CL]Sicilian Translator: A Recipe for Low-Resource NMT
Eryk Wdowiak
http://arxiv.org/abs/2110.01938v1
• [cs.CL]TENT: Text Classification Based on ENcoding Tree Learning
Chong Zhang, Junran Wu, He Zhu, Ke Xu
http://arxiv.org/abs/2110.02047v1
• [cs.CL]TLDR9+: A Large Scale Resource for Extreme Summarization of Social Media Posts
Sajad Sotudeh, Hanieh Deilamsalehy, Franck Dernoncourt, Nazli Goharian
http://arxiv.org/abs/2110.01159v2
• [cs.CL]Teach Me What to Say and I Will Learn What to Pick: Unsupervised Knowledge Selection Through Response Generation with Pretrained Generative Models
Ehsan Lotfi, Maxime De Bruyn, Jeska Buhmann, Walter Daelemans
http://arxiv.org/abs/2110.02067v1
• [cs.CL]Truth-Conditional Captioning of Time Series Data
Harsh Jhamtani, Taylor Berg-Kirkpatrick
http://arxiv.org/abs/2110.01839v1
• [cs.CL]Using Psuedolabels for training Sentiment Classifiers makes the model generalize better across datasets
Natesh Reddy, Muktabh Mayank Srivastava
http://arxiv.org/abs/2110.02200v1
• [cs.CL]ur-iw-hnt at GermEval 2021: An Ensembling Strategy with Multiple BERT Models
Hoai Nam Tran, Udo Kruschwitz
http://arxiv.org/abs/2110.02042v1
• [cs.CR]Adversarial Robustness Verification and Attack Synthesis in Stochastic Systems
Lisa Oakley, Alina Oprea, Stavros Tripakis
http://arxiv.org/abs/2110.02125v1
• [cs.CR]Blockchain-based Federated Learning: A Comprehensive Survey
Zhilin Wang, Qin Hu
http://arxiv.org/abs/2110.02182v1
• [cs.CR]Dataset: Large-scale Urban IoT Activity Data for DDoS Attack Emulation
Arvin Hekmati, Eugenio Grippo, Bhaskar Krishnamachari
http://arxiv.org/abs/2110.01842v1
• [cs.CR]Differential Privacy of Dirichlet Posterior Sampling
Donlapark Ponnoprat
http://arxiv.org/abs/2110.01984v1
• [cs.CR]Machine learning attack on copy detection patterns: are 1x1 patterns cloneable?
Roman Chaban, Olga Taran, Joakim Tutt, Taras Holotyak, Slavi Bonev, Slava Voloshynovskiy
http://arxiv.org/abs/2110.02176v1
• [cs.CV]: High-resolution multi-shot video editing
Bharath Bhushan Damodaran, Emmanuel Jolly, Gilles Puy, Philippe Henri Gosselin, Cédric Thébault, Junghyun Ahn, Tim Christensen, Paul Ghezzo, Pierre Hellier
http://arxiv.org/abs/2110.02124v1
• [cs.CV]A Methodology to Identify Cognition Gaps in Visual Recognition Applications Based on Convolutional Neural Networks
Hannes Vietz, Tristan Rauch, Andreas Löcklin, Nasser Jazdi, Michael Weyrich
http://arxiv.org/abs/2110.02080v1
• [cs.CV]Adversarial Attacks on Black Box Video Classifiers: Leveraging the Power of Geometric Transformations
Shasha Li, Abhishek Aich, Shitong Zhu, M. Salman Asif, Chengyu Song, Amit K. Roy-Chowdhury, Srikanth Krishnamurthy
http://arxiv.org/abs/2110.01823v1
• [cs.CV]An Experimental Evaluation on Deepfake Detection using Deep Face Recognition
Sreeraj Ramachandran, Aakash Varma Nadimpalli, Ajita Rattani
http://arxiv.org/abs/2110.01640v1
• [cs.CV]An Integrated System for Mobile Image-Based Dietary Assessment
Zeman Shao, Yue Han, Jiangpeng He, Runyu Mao, Janine Wright, Deborah Kerr, Carol Boushey, Fengqing Zhu
http://arxiv.org/abs/2110.01754v1
• [cs.CV]Anchor-free Oriented Proposal Generator for Object Detection
Gong Cheng, Jiabao Wang, Ke Li, Xingxing Xie, Chunbo Lang, Yanqing Yao, Junwei Han
http://arxiv.org/abs/2110.01931v1
• [cs.CV]De-rendering Stylized Texts
Wataru Shimoda, Daichi Haraguchi, Seiichi Uchida, Kota Yamaguchi
http://arxiv.org/abs/2110.01890v1
• [cs.CV]Deep Instance Segmentation with High-Resolution Automotive Radar
Jianan Liu, Weiyi Xiong, Liping Bai, Yuxuan Xia, Bing Zhu
http://arxiv.org/abs/2110.01775v1
• [cs.CV]Deep Learning Approach Protecting Privacy in Camera-Based Critical Applications
Gautham Ramajayam, Tao Sun, Chiu C. Tan, Lannan Luo, Haibin Ling
http://arxiv.org/abs/2110.01676v1
• [cs.CV]Efficient Modelling Across Time of Human Actions and Interactions
Alexandros Stergiou
http://arxiv.org/abs/2110.02120v1
• [cs.CV]FooDI-ML: a large multi-language dataset of food, drinks and groceries images and descriptions
David Amat Olóndriz, Ponç Palau Puigdevall, Adrià Salvador Palau
http://arxiv.org/abs/2110.02035v1
• [cs.CV]Frequency Aware Face Hallucination Generative Adversarial Network with Semantic Structural Constraint
Shailza Sharma, Abhinav Dhall, Vinay Kumar
http://arxiv.org/abs/2110.01880v1
• [cs.CV]HDR-cGAN: Single LDR to HDR Image Translation using Conditional GAN
Prarabdh Raipurkar, Rohil Pal, Shanmuganathan Raman
http://arxiv.org/abs/2110.01660v1
• [cs.CV]HighlightMe: Detecting Highlights from Human-Centric Videos
Uttaran Bhattacharya, Gang Wu, Stefano Petrangeli, Viswanathan Swaminathan, Dinesh Manocha
http://arxiv.org/abs/2110.01774v1
• [cs.CV]How You Move Your Head Tells What You Do: Self-supervised Video Representation Learning with Egocentric Cameras and IMU Sensors
Satoshi Tsutsui, Ruta Desai, Karl Ridgeway
http://arxiv.org/abs/2110.01680v1
• [cs.CV]Investigating Fairness of Ocular Biometrics Among Young, Middle-Aged, and Older Adults
Anoop Krishnan, Ali Almadan, Ajita Rattani
http://arxiv.org/abs/2110.01641v1
• [cs.CV]Let there be a clock on the beach: Reducing Object Hallucination in Image Captioning
Ali Furkan Biten, Lluis Gomez, Dimosthenis Karatzas
http://arxiv.org/abs/2110.01705v1
• [cs.CV]MetaPix: Domain Transfer for Semantic Segmentation by Meta Pixel Weighting
Yiren Jian, Chongyang Gao
http://arxiv.org/abs/2110.01777v1
• [cs.CV]Mix3D: Out-of-Context Data Augmentation for 3D Scenes
Alexey Nekrasov, Jonas Schult, Or Litany, Bastian Leibe, Francis Engelmann
http://arxiv.org/abs/2110.02210v1
• [cs.CV]MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer
Sachin Mehta, Mohammad Rastegari
http://arxiv.org/abs/2110.02178v1
• [cs.CV]Multi-Object Tracking with Deep Learning Ensemble for Unmanned Aerial System Applications
Wanlin Xie, Jaime Ide, Daniel Izadi, Sean Banger, Thayne Walker, Ryan Ceresani, Dylan Spagnuolo, Christopher Guagliano, Henry Diaz, Jason Twedt
http://arxiv.org/abs/2110.02044v1
• [cs.CV]Pixel-Level Bijective Matching for Video Object Segmentation
Suhwan Cho, Heansung Lee, Minjung Kim, Sungjun Jang, Sangyoun Lee
http://arxiv.org/abs/2110.01644v1
• [cs.CV]Procedure Planning in Instructional Videosvia Contextual Modeling and Model-based Policy Learning
Jing Bi, Jiebo Luo, Chenliang Xu
http://arxiv.org/abs/2110.01770v1
• [cs.CV]Quantified Facial Expressiveness for Affective Behavior Analytics
Md Taufeeq Uddin, Shaun Canavan
http://arxiv.org/abs/2110.01758v1
• [cs.CV]RapidAI4EO: A Corpus for Higher Spatial and Temporal Reasoning
Giovanni Marchisio, Patrick Helber, Benjamin Bischke, Timothy Davis, Caglar Senaras, Daniele Zanaga, Ruben Van De Kerchove, Annett Wania
http://arxiv.org/abs/2110.01919v1
• [cs.CV]Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation
Devavrat Tomar, Behzad Bozorgtabar, Manana Lortkipanidze, Guillaume Vray, Mohammad Saeed Rad, Jean-Philippe Thiran
http://arxiv.org/abs/2110.02117v1
• [cs.CV]Spatial Context Awareness for Unsupervised Change Detection in Optical Satellite Images
Lukas Kondmann, Aysim Toker, Sudipan Saha, Bernhard Schölkopf, Laura Leal-Taixé, Xiao Xiang Zhu
http://arxiv.org/abs/2110.02068v1
• [cs.CV]Structured Bird’s-Eye-View Traffic Scene Understanding from Onboard Images
Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc Van Gool
http://arxiv.org/abs/2110.01997v1
• [cs.CV]UHP-SOT: An Unsupervised High-Performance Single Object Tracker
Zhiruo Zhou, Hongyu Fu, Suya You, Christoph C. Borel-Donohue, C. -C. Jay Kuo
http://arxiv.org/abs/2110.01812v1
• [cs.CV]VTAMIQ: Transformers for Attention Modulated Image Quality Assessment
Andrei Chubarau, James Clark
http://arxiv.org/abs/2110.01655v1
• [cs.CV]Waypoint Models for Instruction-guided Navigation in Continuous Environments
Jacob Krantz, Aaron Gokaslan, Dhruv Batra, Stefan Lee, Oleksandr Maksymets
http://arxiv.org/abs/2110.02207v1
• [cs.CY]Multimodal datasets: misogyny, pornography, and malignant stereotypes
Abeba Birhane, Vinay Uday Prabhu, Emmanuel Kahembwe
http://arxiv.org/abs/2110.01963v1
• [cs.CY]Social Co-OS: Cyber-Human Social Co-Operating System
Takeshi Kato, Yasuyuki Kudo, Junichi Miyakoshi, Misa Owa, Yasuhiro Asa, Takashi Numata, Ryuji Mine, Hiroyuki Mizuno
http://arxiv.org/abs/2110.01861v1
• [cs.CY]Traffic control Management System and Collision Avoidance System
Gangadhar, Parimala Prabhakar, Abhishek S, Prajwal, Suraj Naik
http://arxiv.org/abs/2110.01830v1
• [cs.DC]A Community Roadmap for Scientific Workflows Research and Development
Rafael Ferreira da Silva, Henri Casanova, Kyle Chard, Ilkay Altintas, Rosa M Badia, Bartosz Balis, Tainã Coleman, Frederik Coppens, Frank Di Natale, Thomas Fahringer, Rosa Filgueira, Grigori Fursin, Daniel Garijo, Carole Goble, Dorran Howell, Shantenu Jha, Daniel S. Katz, Daniel Laney, Ulf Leser, Maciej Malawski, Kshitij Mehta, Loïc Pottier, Jonathan Ozik, J. Luc Peterson, Lavanya Ramakrishnan, Stian Soiland-Reyes, Douglas Thain, Matthew Wolf
http://arxiv.org/abs/2110.02168v1
• [cs.DC]Crashworthiness design of 3D lattice-structure filled thin-walled tubes based on data mining
Jiyuan Lv, Zhonghao Bai, Xianping Du, Feng Zhu, Clifford C. Chou, Binhui Jiang, Shiwei Xu
http://arxiv.org/abs/2110.01444v1
• [cs.DC]Cuttlefish: Library for Achieving Energy Efficiency in Multicore Parallel Programs
Sunil Kumar, Akshat Gupta, Vivek Kumar, Sridutt Bhalachandra
http://arxiv.org/abs/2110.00617v1
• [cs.DC]Learning, Computing, and Trustworthiness in Intelligent IoT Environments: Performance-Energy Tradeoffs
Beatriz Soret, Lam D. Nguyen, Jan Seeger, Arne Bröring, Chaouki Ben Issaid, Sumudu Samarakoon, Anis El Gabli, Vivek Kulkarni, Mehdi Bennis, Petar Popovski
http://arxiv.org/abs/2110.01686v1
• [cs.DC]Local certification of MSO properties for bounded treedepth graphs
Nicolas Bousquet, Laurent Feuilloley, Théo Pierron
http://arxiv.org/abs/2110.01936v1
• [cs.DC]S2 Reducer: High-Performance Sparse Communication to Accelerate Distributed Deep Learning
Keshi Ge, Yongquan Fu, Zhiquan Lai, Xiaoge Deng, Dongsheng Li
http://arxiv.org/abs/2110.02140v1
• [cs.DL]Emerging trends and collaboration patterns unveil the scientific production in blockchain technology: A bibliometric and network analysis from 2014-2020
Kiran Sharma, Parul Khurana
http://arxiv.org/abs/2110.01871v1
• [cs.DS]Inferring Hidden Structures in Random Graphs
Wasim Huleihel
http://arxiv.org/abs/2110.01901v1
• [cs.DS]Random Subgraph Detection Using Queries
Wasim Huleihel, Arya Mazumdar, Soumyabrata Pal
http://arxiv.org/abs/2110.00744v2
• [cs.GT]Differentiable Equilibrium Computation with Decision Diagrams for Stackelberg Models of Combinatorial Congestion Games
Shinsaku Sakaue, Kengo Nakamura
http://arxiv.org/abs/2110.01773v1
• [cs.HC]AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts
Tongshuang Wu, Michael Terry, Carrie J. Cai
http://arxiv.org/abs/2110.01691v1
• [cs.HC]Analysis of the relation between smartphone usage changes during the COVID-19 pandemic and usage preferences on apps
Yuxuan Yang, Maiko Shigeno
http://arxiv.org/abs/2110.01331v2
• [cs.IR]OPAD: An Optimized Policy-based Active Learning Framework for Document Content Analysis
Sumit Shekhar, Bhanu Prakash Reddy Guda, Ashutosh Chaubey, Ishan Jindal, Avanish Jain
http://arxiv.org/abs/2110.02069v1
• [cs.IR]Reddit-TUDFE: practical tool to explore Reddit usability in data science and knowledge processing
Jan Sawicki, Maria Ganzha, Marcin Paprzycki
http://arxiv.org/abs/2110.02158v1
• [cs.IR]SDR: Efficient Neural Re-ranking using Succinct Document Representation
Nachshon Cohen, Amit Portnoy, Besnik Fetahu, Amir Ingber
http://arxiv.org/abs/2110.02065v1
• [cs.IR]Voice Information Retrieval In Collaborative Information Seeking
Sulaiman Adesegun Kukoyi, O. F. W Onifade, Kamorudeen A. Amuda
http://arxiv.org/abs/2110.01788v1
• [cs.IT]A Modified Q-Learning Algorithm for Rate-Profiling of Polarization Adjusted Convolutional (PAC) Codes
Samir Kumar Mishra, Digvijay Katyal, Sarvesha Anegundi Ganapathi
http://arxiv.org/abs/2110.01563v2
• [cs.IT]Analysis and Optimization of HARQ for URLLC
Faisal Nadeem, Yonghui Li, Branka Vucetic, Mahyar Shirvanimoghaddam
http://arxiv.org/abs/2110.02163v1
• [cs.IT]Cellular Network Radio Propagation Modeling with Deep Convolutional Neural Networks
Xin Zhang, Xiujun Shu, Bingwen Zhang, Jie Ren, Lizhou Zhou, Xin Chen
http://arxiv.org/abs/2110.01848v1
• [cs.IT]Enabling Cell-Free Massive MIMO Systems with Wireless Millimeter Wave Fronthaul
Umut Demirhan, Ahmed Alkhateeb
http://arxiv.org/abs/2110.01798v1
• [cs.IT]Lifted Reed-Solomon Codes and Lifted Multiplicity Codes
Lukas Holzbaur, Rina Polyanskaya, Nikita Polyanskii, Ilya Vorobyev, Eitan Yaakobi
http://arxiv.org/abs/2110.02008v1
• [cs.IT]On bases and the dimensions of twisted centralizer codes
Ahmad Muchlis, Galih Pradananta, Pudji Astuti, Djoko Suprijanto
http://arxiv.org/abs/2110.01826v1
• [cs.IT]On the Maximum Achievable Sum-rate of the RIS-aided MIMO Broadcast Channel
Nemanja Stefan Perović, Le-Nam Tran, Marco Di Renzo, Mark F. Flanagan
http://arxiv.org/abs/2110.01700v1
• [cs.IT]On the Properties of Error Patterns in the Constant Lee Weight Channel
Jessica Bariffi, Hannes Bartz, Gianluigi Liva, Joachim Rosenthal
http://arxiv.org/abs/2110.01878v1
• [cs.IT]Pilot Decontamination Processing in Cell-Free Massive MIMO
Alberto Alvarez Polegre, Luca Sanguinetti, Ana Garcia Armada
http://arxiv.org/abs/2110.01915v1
• [cs.IT]Rate Splitting Multiple Access for Semi-Grant-Free Transmissions
Hongwu Liu, Theodoros A. Tsiftsis, Bruno Clerckx, Kyeong Jin Kim, Kyung Sup Kwak, H. Vincent Poor
http://arxiv.org/abs/2110.02127v1
• [cs.IT]Simultaneous Information and Energy Transmission with Finite Constellations
Sadaf ul Zuhra, Samir M. Perlaza, Eitan Altman
http://arxiv.org/abs/2110.01882v1
• [cs.IT]Time-Based Quantization for FRI and Bandlimited signals
Hila Naaman, Satish Mulleti, Yonina C. Eldar, Alejandro Cohen
http://arxiv.org/abs/2110.01928v1
• [cs.LG]-UQ: Accurate Uncertainty Quantification via Anchor Marginalization
Rushil Anirudh, Jayaraman J. Thiagarajan
http://arxiv.org/abs/2110.02197v1
• [cs.LG]A Critique of Strictly Batch Imitation Learning
Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu
http://arxiv.org/abs/2110.02063v1
• [cs.LG]A manifold learning approach for gesture identification from micro-Doppler radar measurements
Eric Mason, Hrushikesh Mhaskar, Adam Guo
http://arxiv.org/abs/2110.01670v1
• [cs.LG]A new harmonium for pattern recognition in survival data
Hylke C. Donker, Harry J. M. Groen
http://arxiv.org/abs/2110.01960v1
• [cs.LG]AdjointBackMapV2: Precise Reconstruction of Arbitrary CNN Unit’s Activation via Adjoint Operators
Qing Wan, Yoonsuck Choe
http://arxiv.org/abs/2110.01736v1
• [cs.LG]An Efficient Anomaly Detection Approach using Cube Sampling with Streaming Data
Seemandhar Jain, Prarthi Jain, Abhishek Srivastava
http://arxiv.org/abs/2110.01813v1
• [cs.LG]An energy-based model for neuro-symbolic reasoning on knowledge graphs
Dominik Dold, Josep Soler Garrido
http://arxiv.org/abs/2110.01639v1
• [cs.LG]Attaining Interpretability in Reinforcement Learning via Hierarchical Primitive Composition
Jeong-Hoon Lee, Jongeun Choi
http://arxiv.org/abs/2110.01833v1
• [cs.LG]Attention Augmented Convolutional Transformer for Tabular Time-series
Sharath M Shankaranarayana, Davor Runje
http://arxiv.org/abs/2110.01825v1
• [cs.LG]Autoregressive Diffusion Models
Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, Tim Salimans
http://arxiv.org/abs/2110.02037v1
• [cs.LG]Bottom-up Hierarchical Classification Using Confusion-based Logit Compression
Tong Liang, Jim Davis, Roman Ilin
http://arxiv.org/abs/2110.01756v1
• [cs.LG]CARL: A Benchmark for Contextual and Adaptive Reinforcement Learning
Carolin Benjamins, Theresa Eimer, Frederik Schubert, André Biedenkapp, Bodo Rosenhahn, Frank Hutter, Marius Lindauer
http://arxiv.org/abs/org/abs/2110.02102v1
• [cs.LG]Combining Physics and Deep Learning to learn Continuous-Time Dynamics Models
Michael Lutter, Jan Peters
http://arxiv.org/abs/2110.01894v1
• [cs.LG]Cross-Modal Virtual Sensing for Combustion Instability Monitoring
Tryambak Gangopadhyay, Vikram Ramanan, Satyanarayanan R Chakravarthy, Soumik Sarkar
http://arxiv.org/abs/2110.01659v1
• [cs.LG]Deep Neural Networks and Tabular Data: A Survey
Vadim Borisov, Tobias Leemann, Kathrin Seßler, Johannes Haug, Martin Pawelczyk, Gjergji Kasneci
http://arxiv.org/abs/2110.01889v1
• [cs.LG]Distribution Mismatch Correction for Improved Robustness in Deep Neural Networks
Alexander Fuchs, Christian Knoll, Franz Pernkopf
http://arxiv.org/abs/2110.01955v1
• [cs.LG]Dropout Q-Functions for Doubly Efficient Reinforcement Learning
Takuya Hiraoka, Takahisa Imagawa, Taisei Hashimoto, Takashi Onishi, Yoshimasa Tsuruoka
http://arxiv.org/abs/2110.02034v1
• [cs.LG]Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication
Lu Cheng, Ruocheng Guo, Kasim Selcuk Candan, Huan Liu
http://arxiv.org/abs/2110.01746v1
• [cs.LG]Exploring the Limits of Large Scale Pre-training
Samira Abnar, Mostafa Dehghani, Behnam Neyshabur, Hanie Sedghi
http://arxiv.org/abs/2110.02095v1
• [cs.LG]Federating for Learning Group Fair Models
Afroditi Papadaki, Natalia Martinez, Martin Bertran, Guillermo Sapiro, Miguel Rodrigues
http://arxiv.org/abs/2110.01999v1
• [cs.LG]Global Convergence and Stability of Stochastic Gradient Descent
Vivak Patel, Bowen Tian, Shushu Zhang
http://arxiv.org/abs/2110.01663v1
• [cs.LG]Graph Coloring: Comparing Cluster Graphs to Factor Graphs
Simon Streicher, Johan du Preez
http://arxiv.org/abs/2110.02048v1
• [cs.LG]HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization
Vincent Dumont, Casey Garner, Anuradha Trivedi, Chelsea Jones, Vidya Ganapati, Juliane Mueller, Talita Perciano, Mariam Kiran, Marc Day
http://arxiv.org/abs/2110.01698v1
• [cs.LG]Hypernetworks for Continual Semi-Supervised Learning
Dhanajit Brahma, Vinay Kumar Verma, Piyush Rai
http://arxiv.org/abs/2110.01856v1
• [cs.LG]Improved architectures and training algorithms for deep operator networks
Sifan Wang, Hanwen Wang, Paris Perdikaris
http://arxiv.org/abs/2110.01654v1
• [cs.LG]Inductive learning for product assortment graph completion
Haris Dukic, Georgios Deligiorgis, Pierpaolo Sepe, Davide Bacciu, Marco Trincavelli
http://arxiv.org/abs/2110.01677v1
• [cs.LG]Information-theoretic generalization bounds for black-box learning algorithms
Hrayr Harutyunyan, Maxim Raginsky, Greg Ver Steeg, Aram Galstyan
http://arxiv.org/abs/2110.01584v2
• [cs.LG]Label differential privacy via clustering
Hossein Esfandiari, Vahab Mirrokni, Umar Syed, Sergei Vassilvitskii
http://arxiv.org/abs/2110.02159v1
• [cs.LG]Learning to shortcut and shortlist order fulfillment deciding
Brian Quanz, Ajay Deshpande, Dahai Xing, Xuan Liu
http://arxiv.org/abs/2110.01668v1
• [cs.LG]Multi-Objective Few-shot Learning for Fair Classification
Ishani Mondal, Procheta Sen, Debasis Ganguly
http://arxiv.org/abs/2110.01951v1
• [cs.LG]Multi-axis Attentive Prediction for Sparse EventData: An Application to Crime Prediction
Yi Sui, Ga Wu, Scott Sanner
http://arxiv.org/abs/2110.01794v1
• [cs.LG]NeurWIN: Neural Whittle Index Network For Restless Bandits Via Deep RL
Khaled Nakhleh, Santosh Ganji, Ping-Chun Hsieh, I-Hong Hou, Srinivas Shakkottai
http://arxiv.org/abs/2110.02128v1
• [cs.LG]Noisy Feature Mixup
Soon Hoe Lim, N. Benjamin Erichson, Francisco Utrera, Winnie Xu, Michael W. Mahoney
http://arxiv.org/abs/2110.02180v1
• [cs.LG]Optimal N-ary ECOC Matrices for Ensemble Classification
Hieu D. Nguyen, Lucas J. Lavalva, Shen-Shyang Ho, Mohammed Sarosh Khan, Nicholas Kaegi
http://arxiv.org/abs/2110.02161v1
• [cs.LG]Optimization with Constraint Learning: A Framework and Survey
Adejuyigbe Fajemisin, Donato Maragno, Dick den Hertog
http://arxiv.org/abs/2110.02121v1
• [cs.LG]Pre-Quantized Deep Learning Models Codified in ONNX to Enable Hardware/Software Co-Design
Ulf Hanebutte, Andrew Baldwin, Senad Durakovic, Igor Filipovich, Chien-Chun, Chou, Damian Adamowicz, Derek Chickles, David Hawkes
http://arxiv.org/abs/2110.01730v1
• [cs.LG]Rapid training of deep neural networks without skip connections or normalization layers using Deep Kernel Shaping
James Martens, Andy Ballard, Guillaume Desjardins, Grzegorz Swirszcz, Valentin Dalibard, Jascha Sohl-Dickstein, Samuel S. Schoenholz
http://arxiv.org/abs/2110.01765v1
• [cs.LG]Robust Linear Classification from Limited Training Data
Deepayan Chakrabarti
http://arxiv.org/abs/2110.01648v1
• [cs.LG]Secure Aggregation for Buffered Asynchronous Federated Learning
Jinhyun So, Ramy E. Ali, Başak Güler, A. Salman Avestimehr
http://arxiv.org/abs/2110.02177v1
• [cs.LG]Semi-Supervised Deep Learning for Multiplex Networks
Anasua Mitra, Priyesh Vijayan, Ranbir Sanasam, Diganta Goswami, Srinivasan Parthasarathy, Balaraman Ravindran
http://arxiv.org/abs/2110.02038v1
• [cs.LG]Short-term precipitation prediction using deep learning
Guoxing Chen, Wei-Chyung Wang
http://arxiv.org/abs/2110.01843v1
• [cs.LG]TensorPlan and the Few Actions Lower Bound for Planning in MDPs under Linear Realizability of Optimal Value Functions
Gellért Weisz, Csaba Szepesvári, András György
http://arxiv.org/abs/2110.02195v1
• [cs.LG]Top-N: Equivariant set and graph generation without exchangeability
Clement Vignac, Pascal Frossard
http://arxiv.org/abs/2110.02096v1
• [cs.LG]Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble
Gaon An, Seungyong Moon, Jang-Hyun Kim, Hyun Oh Song
http://arxiv.org/abs/2110.01548v2
• [cs.LG]When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint
Yoav Freund, Yi-An Ma, Tong Zhang
http://arxiv.org/abs/2110.01827v1
• [cs.NE]Neural Network Adversarial Attack Method Based on Improved Genetic Algorithm
Dingming Yang, Yanrong Cui, Hongqiang Yuan
http://arxiv.org/abs/2110.01818v1
• [cs.NE]Solving even-parity problems using traceless genetic programming
Mihai Oltean
http://arxiv.org/abs/2110.02014v1
• [cs.NI]DeepEdge: A Deep Reinforcement Learning based Task Orchestrator for Edge Computing
Baris Yamansavascilar, Ahmet Cihat Baktir, Cagatay Sonmez, Atay Ozgovde, Cem Ersoy
http://arxiv.org/abs/2110.01863v1
• [cs.NI]On-Demand Networking for Ubiquitous Connectivity and Network Resilience: A Network-in-a-Box Solution
Ki-Hong Park, Mohamed-Slim Alouini, Yunfei Chen
http://arxiv.org/abs/2110.01726v1
• [cs.RO]AEROS: Adaptive RObust least-Squares for Graph-Based SLAM
Milad Ramezani, Matias Mattamala, Maurice Fallon
http://arxiv.org/abs/2110.02018v1
• [cs.RO]AquaVis: A Perception-Aware Autonomous Navigation Framework for Underwater Vehicles
Marios Xanthidis, Michail Kalaitzakis, Nare Karapetyan, James Johnson, Nikolaos Vitzilaios, Jason M. O’Kane, Ioannis Rekleitis
http://arxiv.org/abs/2110.01646v1
• [cs.RO]CNN-based Human Detection for UAVs in Search and Rescue
Nikite Mesvan
http://arxiv.org/abs/2110.01930v1
• [cs.RO]Continuous-Time Fitted Value Iteration for Robust Policies
Michael Lutter, Boris Belousov, Shie Mannor, Dieter Fox, Animesh Garg, Jan Peters
http://arxiv.org/abs/2110.01954v1
• [cs.RO]Deep Reinforcement Learning for Decentralized Multi-Robot Exploration with Macro Actions
Aaron Hao Tan, Federico Pizarro Bejarano, Goldie Nejat
http://arxiv.org/abs/2110.02181v1
• [cs.RO]Deep reinforcement learning for guidewire navigation in coronary artery phantom
Jihoon Kweon, Kyunghwan Kim, Chaehyuk Lee, Hwi Kwon, Jinwoo Park, Kyoseok Song, Young In Kim, Jeeone Park, Inwook Back, Jae-Hyung Roh, Youngjin Moon, Jaesoon Choi, Young-Hak Kim
http://arxiv.org/abs/2110.01840v1
• [cs.RO]Design and Characterization of a 3D-printed Pneumatically-driven Bistable Valve with Tunable Characteristics
Sihan Wang, Liang He, Perla Maiolino
http://arxiv.org/abs/2110.01743v1
• [cs.RO]Fessonia: a Method for Real-Time Estimation of Human Operator Workload Using Behavioural Entropy
Paraskevas Chatzithanos, Grigoris Nikolaou, Rustam Stolkin, Manolis Chiou
http://arxiv.org/abs/2110.01940v1
• [cs.RO]Fully Self-Supervised Class Awareness in Dense Object Descriptors
Denis Hadjivelichkov, Dimitrios Kanoulas
http://arxiv.org/abs/2110.01957v1
• [cs.RO]Guiding Evolutionary Strategies by Differentiable Robot Simulators
Vladislav Kurenkov, Bulat Maksudov
http://arxiv.org/abs/2110.00438v2
• [cs.RO]Hybrid Event Shaping to Stabilize Periodic Hybrid Orbits
James Zhu, Nathan J. Kong, George Council, Aaron M. Jonhson
http://arxiv.org/abs/2110.01123v2
• [cs.RO]Improved Reinforcement Learning Coordinated Control of a Mobile Manipulator using Joint Clamping
Denis Hadjivelichkov, Kostas Vlachos, Dimitrios Kanoulas
http://arxiv.org/abs/2110.01926v1
• [cs.RO]Inverse Kinematics and Dexterous Workspace Formulation for 2-Segment Continuum Robots with Inextensible Segments
Yifan Wang, Zhonghao Wu, Longfei Wang, Bo Feng, Kai Xu
http://arxiv.org/abs/2110.01851v1
• [cs.RO]LLOL: Low-Latency Odometry for Spinning Lidars
Chao Qu, Shreyas S. Shivakumar, Wenxin Liu, Camillo J. Taylor
http://arxiv.org/abs/2110.01725v1
• [cs.RO]Learned Uncertainty Calibration for Visual Inertial Localization
Stephanie Tsuei, Stefano Soatto, Paulo Tabuada, Mark B. Milam
http://arxiv.org/abs/2110.02136v1
• [cs.RO]Mapless Navigation: Learning UAVs Motion forExploration of Unknown Environments
Sunggoo Jung, David Hyunchul Shim
http://arxiv.org/abs/2110.01747v1
• [cs.RO]Motion Control of Redundant Robots with Generalised Inequality Constraints
Amirhossein Kazemipour, Maram Khatib, Khaled Al Khudir, Alessandro De Luca
http://arxiv.org/abs/2110.01689v1
• [cs.RO]Season-invariant GNSS-denied visual localization for UAVs
Jouko Kinnari, Francesco Verdoja, Ville Kyrki
http://arxiv.org/abs/2110.01967v1
• [cs.RO]Set-theoretic Localization for Mobile Robots with Infrastructure-based Sensing
Xiao Li, Yutong Li, Anouck Girard, Ilya Kolmanovsky
http://arxiv.org/abs/2110.01749v1
• [cs.SD]Sound Event Detection Transformer: An Event-based End-to-End Model for Sound Event Detection
Zhirong Ye, Xiangdong Wang, Hong Liu, Yueliang Qian, Rui Tao, Long Yan, Kazushige Ouchi
http://arxiv.org/abs/2110.02011v1
• [cs.SE]LogDP: Combining Dependency and Proximity for Log-based Anomaly Detection
Yongzheng Xie, Hongyu Zhang, Bo Zhang, Muhammad Ali Babar, Sha Lu
http://arxiv.org/abs/2110.01927v1
• [cs.SI]Extracting Major Topics of COVID-19 Related Tweets
Faezeh Azizi, Hamed Vahdat-Nejad, Hamideh Hajiabadi, Mohammad Hossein Khosravi
http://arxiv.org/abs/2110.01876v1
• [cs.SI]Structural Models of Human Social Interactions in Online Smart Communities: the Case of Region-based Journalists on Twitter
Mustafa Toprak, Chiara Boldrini, Andrea Passarella, Marco Conti
http://arxiv.org/abs/2110.01925v1
• [econ.EM]A New Multivariate Predictive Model for Stock Returns
Jianying Xie
http://arxiv.org/abs/2110.01873v1
• [eess.AS]Speech Technology for Everyone: Automatic Speech Recognition for Non-Native English with Transfer Learning
Toshiko Shibano, Xinyi Zhang, Mia Taige Li, Haejin Cho, Peter Sullivan, Muhammad Abdul-Mageed
http://arxiv.org/abs/2110.00678v1
• [eess.IV]DA-DRN: Degradation-Aware Deep Retinex Network for Low-Light Image Enhancement
Xinxu Wei, Xianshi Zhang, Shisen Wang, Cheng Cheng, Yanlin Huang, Kaifu Yang, Yongjie Li
http://arxiv.org/abs/2110.01809v1
• [eess.IV]Deep Subspace analysing for Semi-Supervised multi-label classification of Diabetic Foot Ulcer
Azadeh Alavi
http://arxiv.org/abs/2110.01795v1
• [eess.IV]Double Encoder-Decoder Networks for Gastrointestinal Polyp Segmentation
Adrian Galdran, Gustavo Carneiro, Miguel A. González Ballester
http://arxiv.org/abs/2110.01939v1
• [eess.IV]Proxy-bridged Image Reconstruction Network for Anomaly Detection in Medical Images
Kang Zhou, Jing Li, Weixin Luo, Zhengxin Li, Jianlong Yang, Huazhu Fu, Jun Cheng, Jiang Liu, Shenghua Gao
http://arxiv.org/abs/2110.01761v1
• [eess.IV]Self-Supervised Learning of Perceptually Optimized Block Motion Estimates for Video Compression
Somdyuti Paul, Andrey Norkin, Alan C. Bovik
http://arxiv.org/abs/2110.01805v1
• [eess.IV]Transfer Learning U-Net Deep Learning for Lung Ultrasound Segmentation
Dorothy Cheng, Edmund Y. Lam
http://arxiv.org/abs/2110.02196v1
• [eess.SP]Seizure Classification Using Parallel Genetic Naive Bayes Classifiers
Scot Davidson, Niamh McCallan, Kok Yew Ng, Pardis Biglarbeigi, Dewar Finlay, Boon Leong Lan, James McLaughlin
http://arxiv.org/abs/2110.01742v1
• [eess.SP]Wireless Link Scheduling via Graph Representation Learning: A Comparative Study of Different Supervision Levels
Navid Naderializadeh
http://arxiv.org/abs/2110.01722v1
• [eess.SY]Controlled-Variable Selection based on Chaos Theory for the Tennessee Eastman Plant
S. F. Yapur
http://arxiv.org/abs/2110.01759v1
• [eess.SY]Learning to Solve the AC Optimal Power Flow via a Lagrangian Approach
Ling Zhang, Baosen Zhang
http://arxiv.org/abs/2110.01653v1
• [math.DS]Data-driven Nonlinear Model Reduction to Spectral Submanifolds in Mechanical Systems
Mattia Cenedese, Joar Axås, Haocheng Yang, Melih Eriten, George Haller
http://arxiv.org/abs/2110.01929v1
• [math.OC]A study of first-passage time minimization via Q-learning in heated gridworlds
M. A. Larchenko, P. Osinenko, G. Yaremenko, V. V. Palyulin
http://arxiv.org/abs/2110.02129v1
• [math.OC]Joint optimization of sales-mix and generation plan for a large electricity producer
Paolo Falbo, Carlos Ruiz
http://arxiv.org/abs/2110.02016v1
• [math.OC]KKT Conditions, First-Order and Second-Order Optimization, and Distributed Optimization: Tutorial and Survey
Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley
http://arxiv.org/abs/2110.01858v1
• [math.PR]The Rescaled Polya Urn and the Wright-Fisher process with mutation
Giacomo Aletti, Irene Crimaldi
http://arxiv.org/abs/2110.01853v1
• [math.ST]A Review of Brown 1971 (in)admissibility results under scale mixtures of Gaussian priors
Yuzo Maruyama, William, E. Strawderman
http://arxiv.org/abs/2110.01945v1
• [math.ST]Estimation and Concentration of Missing Mass of Functions of Discrete Probability Distributions
Prafulla Chandra, Andrew Thangaraj
http://arxiv.org/abs/2110.01968v1
• [math.ST]Exponential confidence region based on the projection density estimate. Recursivity of these estimations
M. R. Formica, E. Ostrovsky, L. Sirota
http://arxiv.org/abs/2110.01983v1
• [math.ST]Robust censored regression with l1-norm regularization
Jad Beyhum, Ingrid Van Keilegom
http://arxiv.org/abs/2110.01923v1
• [physics.flu-dyn]Applying Machine Learning to Study Fluid Mechanics
Steven L. Brunton
http://arxiv.org/abs/2110.02083v1
• [physics.flu-dyn]The Potential of Machine Learning to Enhance Computational Fluid Dynamics
Ricardo Vinuesa, Steven L. Brunton
http://arxiv.org/abs/2110.02085v1
• [physics.plasm-ph]Inference and De-Noising of Non-Gaussian Particle Distribution Functions: A Generative Modeling Approach
John Donaghy, Kai Germaschewski
http://arxiv.org/abs/2110.02153v1
• [q-bio.QM]Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation
Soojung Yang, Doyeong Hwang, Seul Lee, Seongok Ryu, Sung Ju Hwang
http://arxiv.org/abs/2110.01219v2
• [q-fin.RM]Predicting Credit Risk for Unsecured Lending: A Machine Learning Approach
K. S. Naik
http://arxiv.org/abs/2110.02206v1
• [quant-ph]Feasible Architecture for Quantum Fully Convolutional Networks
Yusui Chen, Wenhao Hu, Xiang Li
http://arxiv.org/abs/2110.01771v1
• [quant-ph]Lossy compression of statistical data using quantum annealer
Boram Yoon, Nga T. T. Nguyen, Chia Cheng Chang, Ermal Rrapaj
http://arxiv.org/abs/2110.02142v1
• [stat.AP]Evaluating the impact of local tracing partnerships on the performance of contact tracing for COVID-19 in England
Pantelis Samartsidis, Shaun R. Seaman, Abbie Harrison, Angelos Alexopoulos, Gareth J. Hughes, Christopher Rawlinson, Charlotte Anderson, Andre Charlett, Isabel Oliver, Daniela De Angelis
http://arxiv.org/abs/2110.02005v1
• [stat.AP]Multilevel models with random residual variances for joint modelling school value-added effects on the mean and variance of student achievement
George Leckie, Richard Parker, Harvey Goldstein, Kate Tilling
http://arxiv.org/abs/2110.02079v1
• [stat.AP]Parametric study of E. coli incidence with reference to the New Zealand freshwater standards and the Manawatū-Whanganui region
Stephen R Marsland, Robert I McLachlan, Christopher Tuffley
http://arxiv.org/abs/2110.01808v1
• [stat.AP]The Quality of the 2020 Census: An Independent Assessment of Census Bureau Activities Critical to Data Quality
Paul Biemer, Joseph Salvo, Jonathan Auerbach
http://arxiv.org/abs/2110.02135v1
• [stat.ME]Beware the Gini Index! A New Inequality Measure
Sabiou Inoua
http://arxiv.org/abs/2110.01741v1
• [stat.ME]When can relative risks provide causal estimates?
A. J. Webster
http://arxiv.org/abs/2110.01688v1
• [stat.ML]Classification of high-dimensional data with spiked covariance matrix structure
Yin-Jen Chen, Minh Tang
http://arxiv.org/abs/2110.01950v1
• [stat.ML]Estimating Potential Outcome Distributions with Collaborating Causal Networks
Tianhui Zhou, David Carlson
http://arxiv.org/abs/2110.01664v1
• [stat.ML]Permute Me Softly: Learning Soft Permutations for Graph Representations
Giannis Nikolentzos, George Dasoulas, Michalis Vazirgiannis
http://arxiv.org/abs/2110.01872v1
• [stat.ML]Random matrices in service of ML footprint: ternary random features with no performance loss
Hafiz Tiomoko Ali, Zhenyu Liao, Romain Couillet
http://arxiv.org/abs/2110.01899v1
• [stat.ML]Stochastic functional analysis with applications to robust machine learning
Julio Enrique Castrillon-Candas, Dingning Liu, Mark Kon
http://arxiv.org/abs/2110.01729v1