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]今日学术视野(2021.10.7) - 图1: 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]今日学术视野(2021.10.7) - 图2-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]今日学术视野(2021.10.7) - 图3: 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]今日学术视野(2021.10.7) - 图4-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