今日学术视野(2021.2.17)

cs.AI - 人工智能 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.MA - 多代理系统 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.PF - 计算性能 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 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.FA - 泛函演算 math.NA - 数值分析 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.bio-ph - 生物物理 physics.flu-dyn - 流体动力学 physics.geo-ph - 地球物理学 physics.soc-ph - 物理学与社会 q-bio.NC - 神经元与认知 q-bio.PE - 人口与发展 q-fin.ST - 统计金融学 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

• [cs.AI]A Reference Model for IoT Embodied Agents Controlled by Neural Networks
• [cs.AI]AI Ethics Needs Good Data
• [cs.AI]Consistency-based Merging of Variability Models
• [cs.AI]Cross-modal Adversarial Reprogramming
• [cs.AI]Crowdsourcing Parallel Corpus for English-Oromo Neural Machine Translation using Community Engagement Platform
• [cs.AI]Data-driven Analysis for Understanding Team Sports Behaviors
• [cs.AI]Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems
• [cs.AI]Edge Minimizing the Student Conflict Graph
• [cs.AI]Goods Transportation Problem Solving via Routing Algorithm
• [cs.AI]How RL Agents Behave When Their Actions Are Modified
• [cs.AI]Jira: a Kurdish Speech Recognition System Designing and Building Speech Corpus and Pronunciation Lexicon
• [cs.AI]LTL2Action: Generalizing LTL Instructions for Multi-Task RL
• [cs.AI]Mitigating Negative Side Effects via Environment Shaping
• [cs.AI]New methods for metastimuli: architecture, embeddings, and neural network optimization
• [cs.AI]OntoZSL: Ontology-enhanced Zero-shot Learning
• [cs.AI]Player-Centered AI for Automatic Game Personalization: Open Problems
• [cs.AI]Reasoning Over Virtual Knowledge Bases With Open Predicate Relations
• [cs.AI]Responsibility Management through Responsibility Networks
• [cs.AI]Seeing by haptic glance: reinforcement learning-based 3D object Recognition
• [cs.AI]Sequential Recommendation in Online Games with Multiple Sequences, Tasks and User Levels
• [cs.AI]State-Visitation Fairness in Average-Reward MDPs
• [cs.AI]The corruptive force of AI-generated advice
• [cs.AI]Why Talking about ethics is not enough: a proposal for Fintech’s AI ethics
• [cs.CL]Beyond the English Web: Zero-Shot Cross-Lingual and Lightweight Monolingual Classification of Registers
• [cs.CL]Capturing Label Distribution: A Case Study in NLI
• [cs.CL]Characterizing English Variation across Social Media Communities with BERT
• [cs.CL]DOBF: A Deobfuscation Pre-Training Objective for Programming Languages
• [cs.CL]Do as I mean, not as I say: Sequence Loss Training for Spoken Language Understanding
• [cs.CL]Error-driven Pruning of Language Models for Virtual Assistants
• [cs.CL]Exploring Classic and Neural Lexical Translation Models for Information Retrieval: Interpretability, Effectiveness, and Efficiency Benefits
• [cs.CL]Fast End-to-End Speech Recognition via Non-Autoregressive Models and Cross-Modal Knowledge Transferring from BERT
• [cs.CL]Generating Diversified Comments via Reader-Aware Topic Modeling and Saliency Detection
• [cs.CL]Improved Customer Transaction Classification using Semi-Supervised Knowledge Distillation
• [cs.CL]Interactive Learning from Activity Description
• [cs.CL]Leveraging Acoustic and Linguistic Embeddings from Pretrained speech and language Models for Intent Classification
• [cs.CL]MAPGN: MAsked Pointer-Generator network for sequence-to-sequence pre-training
• [cs.CL]MATCH: Metadata-Aware Text Classification in A Large Hierarchy
• [cs.CL]PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them
• [cs.CL]Personalization Strategies for End-to-End Speech Recognition Systems
• [cs.CL]Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm
• [cs.CL]Query-by-Example Keyword Spotting system using Multi-head Attention and Softtriple Loss
• [cs.CL]Structural Information Preserving for Graph-to-Text Generation
• [cs.CL]The first large scale collection of diverse Hausa language datasets
• [cs.CL]They, Them, Theirs: Rewriting with Gender-Neutral English
• [cs.CL]indicnlp@kgp at DravidianLangTech-EACL2021: Offensive Language Identification in Dravidian Languages
• [cs.CR]GPSPiChain-Blockchain based Self-Contained Family Security System in Smart Home
• [cs.CR]Multi-class Classification Based Anomaly Detection of Insider Activities
• [cs.CR]Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPS
• [cs.CR]Towards reliable and transparent vaccine phase III trials with smart contracts
• [cs.CV]3D Fully Convolutional Neural Networks with Intersection Over Union Loss for Crop Mapping from Multi-Temporal Satellite Images
• [cs.CV]A Gated Fusion Network for Dynamic Saliency Prediction
• [cs.CV]A Global to Local Double Embedding Method for Multi-person Pose Estimation
• [cs.CV]A novel method for object detection using deep learning and CAD models
• [cs.CV]Adversarial Unsupervised Domain Adaptation Guided with Deep Clustering for Face Presentation Attack Detection
• [cs.CV]CPP-Net: Context-aware Polygon Proposal Network for Nucleus Segmentation
• [cs.CV]Capturing Detailed Deformations of Moving Human Bodies
• [cs.CV]DeepRA: Predicting Joint Damage From Radiographs Using CNN with Attention
• [cs.CV]FAT: Learning Low-Bitwidth Parametric Representation via Frequency-Aware Transformation
• [cs.CV]Fast, Accurate Barcode Detection in Ultra High-Resolution Images
• [cs.CV]Generation for adaption: a Gan-based approach for 3D Domain Adaption inPoint Cloud
• [cs.CV]INSTA-YOLO: Real-Time Instance Segmentation
• [cs.CV]Improving Automated Visual Fault Detection by Combining a Biologically Plausible Model of Visual Attention with Deep Learning
• [cs.CV]Learning Intra-Batch Connections for Deep Metric Learning
• [cs.CV]Learning Speech-driven 3D Conversational Gestures from Video
• [cs.CV]Multi-class Generative Adversarial Nets for Semi-supervised Image Classification
• [cs.CV]Naturalizing Neuromorphic Vision Event Streams Using GANs
• [cs.CV]OmniDet: Surround View Cameras based Multi-task Visual Perception Network for Autonomous Driving
• [cs.CV]QuickBrowser: A Unified Model to Detect and Read Simple Object in Real-time
• [cs.CV]RMS-Net: Regression and Masking for Soccer Event Spotting
• [cs.CV]Rotation-Equivariant Deep Learning for Diffusion MRI
• [cs.CV]Saliency-Aware Class-Agnostic Food Image Segmentation
• [cs.CV]Segmenting two-dimensional structures with strided tensor networks
• [cs.CV]Spatio-temporal Graph-RNN for Point Cloud Prediction
• [cs.CV]Video Analytics on IoT devices
• [cs.CV]Win-Fail Action Recognition
• [cs.CY]On the Value of Wikipedia as a Gateway to the Web
• [cs.CY]Sociotechnical Challenges of eHealth Technology for Patient Self-Management: A Systematic Review
• [cs.CY]Vehicle to Vehicle (V2V) Communication Protocol: Components, Benefits, Challenges, Safety and Machine Learning Applications
• [cs.DC]Asynchronous Gossip in Smartphone Peer-to-Peer Networks
• [cs.DC]Byzantine Dispersion on Graphs
• [cs.DC]Good-case Latency of Byzantine Broadcast: a Complete Categorization
• [cs.DC]Hugo: A Cluster Scheduler that Efficiently Learns to Select Complementary Data-Parallel Jobs
• [cs.DC]MATCH: An MPI Fault Tolerance Benchmark Suite
• [cs.DC]MOARD: Modeling Application Resilience to Transient Faults on Data Objects
• [cs.DC]Near-Optimal Scheduling in the Congested Clique
• [cs.DC]Reinit++: Evaluating the Performance of Global-Restart Recovery Methods For MPI Fault Tolerance
• [cs.DC]Simulation-based Optimization and Sensibility Analysis of MPI Applications: Variability Matters
• [cs.DL]Impact of h-index on authors ranking: A comparative analysis of Scopus and WoS
• [cs.DS]Fair and Optimal Cohort Selection for Linear Utilities
• [cs.GT]Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games
• [cs.GT]Mixed Nash Equilibria in the Adversarial Examples Game
• [cs.GT]Multi-Stage Decentralized Matching Markets: Uncertain Preferences and Strategic Behaviors
• [cs.GT]ScrofaZero: Mastering Trick-taking Poker Game Gongzhu by Deep Reinforcement Learning
• [cs.HC]CHARET: Character-centered Approach to Emotion Tracking in Stories
• [cs.HC]Confidence-Aware Learning Assistant
• [cs.IR]Distillation based Multi-task Learning: A Candidate Generation Model for Improving Reading Duration
• [cs.IR]Learning Intents behind Interactions with Knowledge Graph for Recommendation
• [cs.IR]Learning a Product Relevance Model from Click-Through Data in E-Commerce
• [cs.IR]Leveraging User Behavior History for Personalized Email Search
• [cs.IR]Model Synthesis for Communication Traces of System-on-Chip Designs
• [cs.IR]Overview of the TREC 2020 deep learning track
• [cs.IR]Supporting search engines with knowledge and context
• [cs.IR]User Embedding based Neighborhood Aggregation Method for Inductive Recommendation
• [cs.IR]UserReg: A Simple but Strong Model for Rating Prediction
• [cs.IT]A Deterministic Algorithm for Computing the Weight Distribution of Polar Codes
• [cs.IT]A Further Note on an Innovations Approach to Viterbi Decoding of Convolutional Codes
• [cs.IT]A Theoretical Performance Bound for Joint Beamformer Design of Wireless Fronthaul and Access Links in Downlink C-RAN
• [cs.IT]Alternative Detectors for Spectrum Sensing by Exploiting Excess Bandwidth
• [cs.IT]Beamformer Design with Smooth Constraint-Free Approximation in Downlink Cloud Radio Access Networks
• [cs.IT]CQNet: Complex Input Quantized Neural Network designed for Massive MIMO CSI Feedback
• [cs.IT]DNA codes over two noncommutative rings of order four
• [cs.IT]Fluctuation-response theorem for Kullback-Leibler divergences to quantify causation
• [cs.IT]Galois hulls of cyclic serial codes over a finite chain ring
• [cs.IT]Intermittent Status Updating Through Joint Scheduling of Sensing and Retransmissions
• [cs.IT]Joint Rate Distortion Function of a Tuple of Correlated Multivariate Gaussian Sources with Individual Fidelity Criteria
• [cs.IT]MIMO Interference Channels Assisted by Reconfigurable Intelligent Surfaces: Mutual Coupling Aware Sum-Rate Optimization Based on a Mutual Impedance Channel Model
• [cs.IT]Max-Min Fair Hybrid Precoding for Multi-group Multicasting in Millimeter-Wave Channel
• [cs.IT]Multi-Class Unsourced Random Access via Coded Demixing
• [cs.IT]Multipair Two-Way DF Relaying with Cell-Free Massive MIMO
• [cs.IT]Reconfigurable Intelligent Surfaces in 6G: Reflective, Transmissive, or Both?
• [cs.IT]Scalable Vector Gaussian Information Bottleneck
• [cs.IT]Sequential prediction under log-loss with side information
• [cs.IT]Seven Defining Features of Terahertz (THz) Wireless Systems: A Fellowship of Communication and Sensing
• [cs.IT]Task-oriented Communication System Design in Cyber-Physical Systems: A Survey on Theory and Applications
• [cs.IT]Timely Transmissions Using Optimized Variable Length Coding
• [cs.IT]Undoing Causal Effects of a Causal Broadcast Channel with Cooperating Receivers using Entanglement Resources
• [cs.LG]A Data Quality-Driven View of MLOps
• [cs.LG]A Deep Adversarial Model for Suffix and Remaining Time Prediction of Event Sequences
• [cs.LG]A Forward Backward Greedy approach for Sparse Multiscale Learning
• [cs.LG]A New Algorithm for Hidden Markov Models Learning Problem
• [cs.LG]A Simple Deep Equilibrium Model Converges to Global Optima with Weight Tying
• [cs.LG]A closer look at temporal variability in dynamic online learning
• [cs.LG]A first look into the carbon footprint of federated learning
• [cs.LG]A generalized quadratic loss for SVM and Deep Neural Networks
• [cs.LG]Achieving Linear Convergence in Federated Learning under Objective and Systems Heterogeneity
• [cs.LG]Adversarial Attack on Network Embeddings via Supervised Network Poisoning
• [cs.LG]Almost Optimal Algorithms for Two-player Markov Games with Linear Function Approximation
• [cs.LG]And/or trade-off in artificial neurons: impact on adversarial robustness
• [cs.LG]Approximation to Object Conditional Validity with Conformal Predictors
• [cs.LG]Attribution Mask: Filtering Out Irrelevant Features By Recursively Focusing Attention on Inputs of DNNs
• [cs.LG]Bridging Graph Neural Networks and Statistical Relational Learning: Relational One-Class GCN
• [cs.LG]CAP-GAN: Towards_Adversarial_Robustness_with_Cycle-consistent_Attentional_Purification
• [cs.LG]CATE: Computation-aware Neural Architecture Encoding with Transformers
• [cs.LG]Comprehensive Comparative Study of Multi-Label Classification Methods
• [cs.LG]Compression phase is not necessary for generalization in representation learning
• [cs.LG]Connecting Interpretability and Robustness in Decision Trees through Separation
• [cs.LG]Costly Features Classification using Monte Carlo Tree Search
• [cs.LG]Cross-domain Time Series Forecasting with Attention Sharing
• [cs.LG]CrossLight: A Cross-Layer Optimized Silicon Photonic Neural Network Accelerator
• [cs.LG]DAC: Deep Autoencoder-based Clustering, a General Deep Learning Framework of Representation Learning
• [cs.LG]Data Profiling for Adversarial Training: On the Ruin of Problematic Data
• [cs.LG]Deep Co-Attention Network for Multi-View Subspace Learning
• [cs.LG]Demystifying Inductive Biases for -VAE Based Architectures
• [cs.LG]Developing parsimonious ensembles using predictor diversity within a reinforcement learning framework
• [cs.LG]Distilling Double Descent
• [cs.LG]Distributed Online Learning for Joint Regret with Communication Constraints
• [cs.LG]Distributed Second Order Methods with Fast Rates and Compressed Communication
• [cs.LG]Does Standard Backpropagation Forget Less Catastrophically Than Adam?
• [cs.LG]Domain Adversarial Reinforcement Learning
• [cs.LG]Doping: A technique for efficient compression of LSTM models using sparse structured additive matrices
• [cs.LG]Equilibrium Inverse Reinforcement Learning for Ride-hailing Vehicle Network
• [cs.LG]Exploiting Shared Representations for Personalized Federated Learning
• [cs.LG]Exploring Adversarial Robustness of Deep Metric Learning
• [cs.LG]FedBN: Federated Learning on Non-IID Features via Local Batch Normalization
• [cs.LG]FedU: A Unified Framework for Federated Multi-Task Learning with Laplacian Regularization
• [cs.LG]Generating Structured Adversarial Attacks Using Frank-Wolfe Method
• [cs.LG]Geometric feature performance under downsampling for EEG classification tasks
• [cs.LG]GradPIM: A Practical Processing-in-DRAM Architecture for Gradient Descent
• [cs.LG]Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization
• [cs.LG]Guided Interpolation for Adversarial Training
• [cs.LG]High-Dimensional Gaussian Process Inference with Derivatives
• [cs.LG]How Framelets Enhance Graph Neural Networks
• [cs.LG]How to Learn when Data Reacts to Your Model: Performative Gradient Descent
• [cs.LG]Hybrid Artificial Intelligence Methods for Predicting Air Demand in Dam Bottom Outlet
• [cs.LG]Improved Corruption Robust Algorithms for Episodic Reinforcement Learning
• [cs.LG]Intelligent Electric Vehicle Charging Recommendation Based on Multi-Agent Reinforcement Learning
• [cs.LG]Intermediate Layer Optimization for Inverse Problems using Deep Generative Models
• [cs.LG]Knowledge Graph Embedding using Graph Convolutional Networks with Relation-Aware Attention
• [cs.LG]Large-Scale Meta-Learning with Continual Trajectory Shifting
• [cs.LG]Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent
• [cs.LG]Learning image quality assessment by reinforcing task amenable data selection
• [cs.LG]Learning-Driven Decision Mechanisms in Physical Layer: Facts, Challenges, and Remedies
• [cs.LG]Machine Learning Methods for the Design and Operation of Liquid Rocket Engines — Research Activities at the DLR Institute of Space Propulsion
• [cs.LG]Maximizing Joint Entropy for Batch-Mode Active Learning of Perceptual Metrics
• [cs.LG]Model-Agnostic Graph Regularization for Few-Shot Learning
• [cs.LG]Model-free Representation Learning and Exploration in Low-rank MDPs
• [cs.LG]Multi-Objective Meta Learning
• [cs.LG]Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation
• [cs.LG]Network of Tensor Time Series
• [cs.LG]Neural Network Compression for Noisy Storage Devices
• [cs.LG]Neuro-algorithmic Policies enable Fast Combinatorial Generalization
• [cs.LG]On Robust Optimal Transport: Computational Complexity, Low-rank Approximation, and Barycenter Computation
• [cs.LG]On the Impact of Device and Behavioral Heterogeneity in Federated Learning
• [cs.LG]On the Inherent Regularization Effects of Noise Injection During Training
• [cs.LG]On the Last Iterate Convergence of Momentum Methods
• [cs.LG]On the convergence of group-sparse autoencoders
• [cs.LG]One-shot learning for the long term: consolidation with an artificial hippocampal algorithm
• [cs.LG]Online Apprenticeship Learning
• [cs.LG]Optimal Regret Algorithm for Pseudo-1d Bandit Convex Optimization
• [cs.LG]PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators
• [cs.LG]Perceptually Constrained Adversarial Attacks
• [cs.LG]Reconstruction-Based Membership Inference Attacks are Easier on Difficult Problems
• [cs.LG]Reinforcement Learning for IoT Security: A Comprehensive Survey
• [cs.LG]Relation-aware Graph Attention Model With Adaptive Self-adversarial Training
• [cs.LG]Reversible Action Design for Combinatorial Optimization with Reinforcement Learning
• [cs.LG]Revisiting Smoothed Online Learning
• [cs.LG]Robust Classification using Hidden Markov Models and Mixtures of Normalizing Flows
• [cs.LG]Sample Efficient Subspace-based Representations for Nonlinear Meta-Learning
• [cs.LG]Secure-UCB: Saving Stochastic Bandits from Poisoning Attacks via Limited Data Verification
• [cs.LG]Self Regulated Learning Mechanism for Data Efficient Knowledge Distillation
• [cs.LG]Self-Reorganizing and Rejuvenating CNNs for Increasing Model Capacity Utilization
• [cs.LG]Smoothness Matrices Beat Smoothness Constants: Better Communication Compression Techniques for Distributed Optimization
• [cs.LG]Sparse Attention Guided Dynamic Value Estimation for Single-Task Multi-Scene Reinforcement Learning
• [cs.LG]TI-Capsule: Capsule Network for Stock Exchange Prediction
• [cs.LG]Technical Challenges for Training Fair Neural Networks
• [cs.LG]The Predictive Normalized Maximum Likelihood for Over-parameterized Linear Regression with Norm Constraint: Regret and Double Descent
• [cs.LG]The Role of Momentum Parameters in the Optimal Convergence of Adaptive Polyak’s Heavy-ball Methods
• [cs.LG]ThetA — fast and robust clustering via a distance parameter
• [cs.LG]Tight lower bounds for Dynamic Time Warping
• [cs.LG]Transfer Learning for Future Wireless Networks: A Comprehensive Survey
• [cs.LG]Translational Equivariance in Kernelizable Attention
• [cs.LG]Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning
• [cs.LG]Understanding self-supervised Learning Dynamics without Contrastive Pairs
• [cs.LG]WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points
• [cs.LG]Wasserstein Proximal of GANs
• [cs.LG]Weak Adaptation Learning — Addressing Cross-domain Data Insufficiency with Weak Annotator
• [cs.LG]Weight Initialization Techniques for Deep Learning Algorithms in Remote Sensing: Recent Trends and Future Perspectives
• [cs.MA]Cooperation and Reputation Dynamics with Reinforcement Learning
• [cs.MA]Modelling Cooperation in Network Games with Spatio-Temporal Complexity
• [cs.MA]On the Equilibrium Elicitation of Markov Games Through Information Design
• [cs.MA]Partial Disclosure of Private Dependencies in Privacy Preserving Planning
• [cs.MA]Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing
• [cs.NE]HAWKS: Evolving Challenging Benchmark Sets for Cluster Analysis
• [cs.NE]Learning by Turning: Neural Architecture Aware Optimisation
• [cs.NI]A Tale of Three Datasets: Towards Characterizing Mobile Broadband Access in the United States
• [cs.NI]On Topology Optimization and Routing in Integrated Access and Backhaul Networks: A Genetic Algorithm-based Approach
• [cs.NI]T-RACKs: A Faster Recovery Mechanism for TCP in Data Center Networks
• [cs.PF]An In-Depth Investigation of Performance Characteristics of Hyperledger Fabric
• [cs.RO]A Differentiable Contact Model to Extend Lagrangian and Hamiltonian Neural Networks for Modeling Hybrid Dynamics
• [cs.RO]Corrective Shared Autonomy for Addressing Task Variability
• [cs.RO]DiffCo: Auto-Differentiable Proxy Collision Detection with Multi-class Labels for Safety-Aware Trajectory Optimization
• [cs.RO]Distributed Estimation, Control and Coordination of Quadcopter Swarm Robots
• [cs.RO]End-to-End Egospheric Spatial Memory
• [cs.RO]FaSTrack: a Modular Framework for Real-Time Motion Planning and Guaranteed Safe Tracking
• [cs.RO]FastHand: Fast Hand Pose Estimation From A Monocular Camera
• [cs.RO]Field Evaluations of A Deep Learning-based Intelligent Spraying Robot with Flow Control for Pear Orchards
• [cs.RO]Human-Robot Handshaking: A Review
• [cs.RO]Learning Variable Impedance Control via Inverse Reinforcement Learning for Force-Related Tasks
• [cs.RO]Learning from Demonstrations using Signal Temporal Logic
• [cs.RO]Minimum Jerk Trajectory Generation for Straight and Curved Movements: Mathematical Analysis
• [cs.RO]Point-line-based RGB-D SLAM and Bundle Adjustment Uncertainty Analysis
• [cs.RO]Speculative Path Planning
• [cs.RO]Uncovering Interpretable Internal States of Merging Tasks at Highway On-Ramps for Autonomous Driving Decision-Making
• [cs.RO]Unpacking Human Teachers’ Intentions For Natural Interactive Task Learning
• [cs.RO]Urban Metric Maps for Small Unmanned Aircraft Systems Motion Planning
• [cs.SD]Deep Convolutional and Recurrent Networks for Polyphonic Instrument Classification from Monophonic Raw Audio Waveforms
• [cs.SD]Parametric Optimization of Violin Top Plates using Machine Learning
• [cs.SD]Thank you for Attention: A survey on Attention-based Artificial Neural Networks for Automatic Speech Recognition
• [cs.SE]Automatically Matching Bug Reports With Related App Reviews
• [cs.SE]Machine Learning Model Development from a Software Engineering Perspective: A Systematic Literature Review
• [cs.SI]A Bayesian social platform for inclusive and evidence-based decision making
• [cs.SI]A Bounded-Confidence Model of Opinion Dynamics on Hypergraphs
• [cs.SI]Exploring the Public Reaction to COVID-19 News on Social Media in Portugal
• [cs.SI]Learning low-rank latent mesoscale structures in networks
• [cs.SI]Pulse of the Pandemic: Iterative Topic Filtering for Clinical Information Extraction from Social Media
• [cs.SI]Radflow: A Recurrent, Aggregated, and Decomposable Model for Networks of Time Series
• [cs.SI]STruD: Truss Decomposition of Simplicial Complexes
• [eess.AS]Adversarial defense for automatic speaker verification by cascaded self-supervised learning models
• [eess.AS]Bi-APC: Bidirectional Autoregressive Predictive Coding for Unsupervised Pre-training and Its Application to Children’s ASR
• [eess.AS]Hybrid phonetic-neural model for correction in speech recognition systems
• [eess.IV]Attention-gated convolutional neural networks for off-resonance correction of spiral real-time MRI
• [eess.IV]Blind stain separation using model-aware generative learning and its applications on fluorescence microscopy images
• [eess.IV]Collaborative Intelligence: Challenges and Opportunities
• [eess.IV]Colored Kimia Path24 Dataset: Configurations and Benchmarks with Deep Embeddings
• [eess.IV]Detection and severity classification of COVID-19 in CT images using deep learning
• [eess.IV]Estimating Nonplanar Flow from 2D Motion-blurred Widefield Microscopy Images via Deep Learning
• [eess.IV]Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images
• [eess.IV]How Convolutional Neural Networks Deal with Aliasing
• [eess.IV]Multi-Texture GAN: Exploring the Multi-Scale Texture Translation f
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or Brain MR Images
• [eess.IV]Scan-Specific MRI Reconstruction using Zero-Shot Physics-Guided Deep Learning
• [eess.SP]Federated Dropout Learning for Hybrid Beamforming With Spatial Path Index Modulation In Multi-User mmWave-MIMO Systems
• [eess.SP]Machine Learning on Camera Images for Fast mmWave Beamforming
• [eess.SY]A Decentralized Multi-UAV Spatio-Temporal Multi-Task Allocation Approach for Perimeter Defense
• [eess.SY]High Order Control Lyapunov-Barrier Functions for Temporal Logic Specifications
• [math.FA]Strong Brascamp-Lieb Inequalities
• [math.NA]Plug-and-Play external and internal priors for image restoration
• [math.OC]A Momentum-Assis
8dc
ted Single-Timescale Stochastic Approximation Algorithm for Bilevel Optimization
• [math.OC]A hybrid variance-reduced method for decentralized stochastic non-convex optimization
• [math.OC]Communication-Efficient Distributed Optimization with Quantized Preconditioners
• [math.OC]Decentralized Distributed Optimization for Saddle Point Problems
• [math.OC]Decentralized Riemannian Gradient Descent on the Stiefel Manifold
• [math.OC]Newton Method over Networks is Fast up to the Statistical Precision
• [math.OC]Relaxation of optimal transport problem via strictly convex functions
• [math.PR]Multivariate Max-Stable Processes and Homogeneous Functionals
• [math.ST]Bayes Factors for Peri-Null Hypotheses
• [math.ST]Estimation for change point of discretely observed ergodic diffusion processes
• [math.ST]Fast Non-Asymptotic Testing And Support Recovery For Large Sparse Toeplitz Covariance Matrices
• [math.ST]Gaussian distributions on Riemannian symmetric spaces in the large N limit
• [math.ST]Improved Estimators for Semi-supervised High-dimensional Regression Model
• [math.ST]One Hundred Probability and Statistics Inequalities
• [math.ST]Optimal designs for the development of personalized treatment rules
• [math.ST]Reconstructing measures on manifolds: an optimal transport approach
• [physics.bio-ph]Holographic Cell Stiffness Mapping Using Acoustic Stimulation
• [physics.flu-dyn]Short- and long-term prediction of a chaotic flow: A physics-constrained reservoir computing approach
• [physics.geo-ph]”Shaking in 5 seconds!” A Voluntary Smartphone-based Earthquake Early Warning System
• [physics.soc-ph]Differences in the spatial landscape of urban mobility: gender and socioeconomic perspectives
• [q-bio.NC]Representing Alzheimer’s Disease Progression via Deep Prototype Tree
• [q-bio.PE]A stochastic SIR model for the analysis of the COVID-19 Italian epidemic
• [q-fin.ST]REST: Relational Event-driven Stock Trend Forecasting
• [quant-ph]Private learning implies quantum stability
• [quant-ph]Refined Belief-Propagation Decoding of Quantum Codes with Scalar Messages
• [stat.AP]A Bayesian cohort component projection model to estimate adult populations at the subnational level in data-sparse settings
• [stat.AP]Efficient Selection Between Hierarchical Cognitive Models: Cross-validation With Variational Bayes
• [stat.AP]Model-Independent Detection of New Physics Signals Using Interpretable Semi-Supervised Classifier Tests
• [stat.ME]A modified closed-form maximum likelihood estimator
• [stat.ME]Contrastive latent variable modeling with application to case-control sequencing experiments
• [stat.ME]Diagnostic tools for a multivariate negative binomial model for fitting correlated data with overdispersion
• [stat.ME]Goal-oriented adaptive sampling under random field modelling of response probability distributions
• [stat.ME]Horseshoe shrinkage methods for Bayesian fusion estimation
• [stat.ME]Modeling Spatial Data with Cauchy Convolution Processes
• [stat.ME]Nonintrusive Uncertainty Quantification for automotive crash problems with VPS/Pamcrash
• [stat.ME]Robust Model-Based Clustering
• [stat.ME]Statistical Power for Estimating Treatment Effects Using Difference-in-Differences and Comparative Interrupted Time Series Designs with Variation in Treatment Timing
• [stat.ME]Stochastic Convergence Rates and Applications of Adaptive Quadrature in Bayesian Inference
• [stat.ME]The Importance of Being a Band: Finite-Sample Exact Distribution-Free Prediction Sets for Functional Data
• [stat.ML]Achieving Efficiency in Black Box Simulation of Distribution Tails with Self-structuring Importance Samplers
• [stat.ML]Annealed Flow Transport Monte Carlo
• [stat.ML]Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections
• [stat.ML]Asymptotically Optimal Strategies For Combinatorial Semi-Bandits in Polynomial Time
• [stat.ML]Causal Markov Decision Processes: Learning Good Interventions Efficiently
• [stat.ML]Certifiably Robust Variational Autoencoders
• [stat.ML]Clustering Left-Censored Multivariate Time-Series
• [stat.ML]Diffusion Approximations for a Class of Sequential Testing Problems
• [stat.ML]Double-descent curves in neural networks: a new perspective using Gaussian processes
• [stat.ML]Efficient Designs of SLOPE Penalty Sequences in Finite Dimension
• [stat.ML]Fast and accurate optimization on the orthogonal manifold without retraction
• [stat.ML]Healing Products of Gaussian Processes
• [stat.ML]Learning from Similarity-Confidence Data
• [stat.ML]Manifold Density Estimation via Generalized Dequantization
• [stat.ML]On Riemannian Stochastic Approximation Schemes with Fixed Step-Size
• [stat.ML]Scalable nonparametric Bayesian learning for heterogeneous and dynamic velocity fields
• [stat.ML]Sliced Multi-Marginal Optimal Transport
• [stat.ML]Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces
• [stat.ML]Tractable structured natural gradient descent using local parameterizations

·····································

• [cs.AI]A Reference Model for IoT Embodied Agents Controlled by Neural Networks
Nathalia Nascimento, Paulo Alencar, Donald Cowan, Carlos Lucena
http://arxiv.org/abs/2102.07589v1

• [cs.AI]AI Ethics Needs Good Data
Angela Daly, S Kate Devitt, Monique Mann
http://arxiv.org/abs/2102.07333v1

• [cs.AI]Consistency-based Merging of Variability Models
Mathias Uta, Alexander Felfernig, Gottfried Schenner, Johannes Spoecklberger
http://arxiv.org/abs/2102.07643v1

• [cs.AI]Cross-modal Adversarial Reprogramming
Paarth Neekhara, Shehzeen Hussain, Jinglong Du, Shlomo Dubnov, Farinaz Koushanfar, Julian McAuley
http://arxiv.org/abs/2102.07325v1

• [cs.AI]Crowdsourcing Parallel Corpus for English-Oromo Neural Machine Translation using Community Engagement Platform
Sisay Chala, Bekele Debisa, Amante Diriba, Silas Getachew, Chala Getu, Solomon Shiferaw
http://arxiv.org/abs/2102.07539v1

• [cs.AI]Data-driven Analysis for Understanding Team Sports Behaviors
Keisuke Fujii
http://arxiv.org/abs/2102.07545v1

• [cs.AI]Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems
Yaodong Yang, Jun Luo, Ying Wen, Oliver Slumbers, Daniel Graves, Haitham Bou Ammar, Jun Wang, Matthew E. Taylor
http://arxiv.org/abs/2102.07659v1

• [cs.AI]Edge Minimizing the Student Conflict Graph
Joshua S. Friedman
http://arxiv.org/abs/2102.06743v1

• [cs.AI]Goods Transportation Problem Solving via Routing Algorithm
Mikhail Shchukin, Aymen Ben Said, Andre Lobo Teixeira
http://arxiv.org/abs/2102.06943v1

• [cs.AI]How RL Agents Behave When Their Actions Are Modified
Eric D. Langlois, Tom Everitt
http://arxiv.org/abs/2102.07716v1

• [cs.AI]Jira: a Kurdish Speech Recognition System Designing and Building Speech Corpus and Pronunciation Lexicon
Hadi Veisi, Hawre Hosseini, Mohammad Mohammadamini, Wirya Fathy, Aso Mahmudi
http://arxiv.org/abs/2102.07412v1

• [cs.AI]LTL2Action: Generalizing LTL Instructions for Multi-Task RL
Pashootan Vaezipoor, Andrew Li, Rodrigo Toro Icarte, Sheila McIlraith
http://arxiv.org/abs/2102.06858v1

• [cs.AI]Mitigating Negative Side Effects via Environment Shaping
Sandhya Saisubramanian, Shlomo Zilberstein
http://arxiv.org/abs/2102.07017v1

• [cs.AI]New methods for metastimuli: architecture, embeddings, and neural network optimization
Rico A. R. Picone, Dane Webb, Finbarr Obierefu, Jotham Lentz
http://arxiv.org/abs/2102.07090v1

• [cs.AI]OntoZSL: Ontology-enhanced Zero-shot Learning
Yuxia Geng, Jiaoyan Chen, Zhuo Chen, Jeff Z. Pan, Zhiquan Ye, Zonggang Yuan, Yantao Jia, Huajun Chen
http://arxiv.org/abs/2102.07339v1

• [cs.AI]Player-Centered AI for Automatic Game Personalization: Open Problems
Jichen Zhu, Santiago Ontañón
http://arxiv.org/abs/2102.07548v1

• [cs.AI]Reasoning Over Virtual Knowledge Bases With Open Predicate Relations
Haitian Sun, Pat Verga, Bhuwan Dhingra, Ruslan Salakhutdinov, William W. Cohen
http://arxiv.org/abs/2102.07043v1

• [cs.AI]Responsibility Management through Responsibility Networks
Ruijun Chen, Jiong Qiu, Xuejiao Tang
http://arxiv.org/abs/2102.07246v1

• [cs.AI]Seeing by haptic glance: reinforcement learning-based 3D object Recognition
Kevin Riou, Suiyi Ling, Guillaume Gallot, Patrick Le Callet
http://arxiv.org/abs/2102.07599v1

• [cs.AI]Sequential Recommendation in Online Games with Multiple Sequences, Tasks and User Levels
Si Chen, Yuqiu Qian, Hui Li, Chen Lin
http://arxiv.org/abs/2102.06950v1

• [cs.AI]State-Visitation Fairness in Average-Reward MDPs
Ganesh Ghalme, Vineet Nair, Vishakha Patil, Yilun Zhou
http://arxiv.org/abs/2102.07120v1

• [cs.AI]The corruptive force of AI-generated advice
Margarita Leib, Nils C. Köbis, Rainer Michael Rilke, Marloes Hagens, Bernd Irlenbusch
http://arxiv.org/abs/2102.07536v1

• [cs.AI]Why Talking about ethics is not enough: a proposal for Fintech’s AI ethics
Cristina Godoy Bernardo de Oliveira, Evandro Eduardo Seron Ruiz
http://arxiv.org/abs/2102.07213v1

• [cs.CL]Beyond the English Web: Zero-Shot Cross-Lingual and Lightweight Monolingual Classification of Registers
Liina Repo, Valtteri Skantsi, Samuel Rönnqvist, Saara Hellström, Miika Oinonen, Anna Salmela, Douglas Biber, Jesse Egbert, Sampo Pyysalo, Veronika Laippala
http://arxiv.org/abs/2102.07396v1

• [cs.CL]Capturing Label Distribution: A Case Study in NLI
Shujian Zhang, Chengyue Gong, Eunsol Choi
http://arxiv.org/abs/2102.06859v1

• [cs.CL]Characterizing English Variation across Social Media Communities with BERT
Li Lucy, David Bamman
http://arxiv.org/abs/2102.06820v1

• [cs.CL]DOBF: A Deobfuscation Pre-Training Objective for Programming Languages
Baptiste Roziere, Marie-Anne Lachaux, Marc Szafraniec, Guillaume Lample
http://arxiv.org/abs/2102.07492v1

• [cs.CL]Do as I mean, not as I say: Sequence Loss Training for Spoken Language Understanding
Milind Rao, Pranav Dheram, Gautam Tiwari, Anirudh Raju, Jasha Droppo, Ariya Rastrow, Andreas Stolcke
http://arxiv.org/abs/2102.06750v1

• [cs.CL]Error-driven Pruning of Language Models for Virtual Assistants
Sashank Gondala, Lyan Verwimp, Ernest Pusateri, Manos Tsagkias, Christophe Van Gysel
http://arxiv.org/abs/2102.07219v1

• [cs.CL]Exploring Classic and Neural Lexical Translation Models for Information Retrieval: Interpretability, Effectiveness, and Efficiency Benefits
Leonid Boytsov, Zico Kolter
http://arxiv.org/abs/2102.06815v1

• [cs.CL]Fast End-to-End Speech Recognition via Non-Autoregressive Models and Cross-Modal Knowledge Transferring from BERT
Ye Bai, Jiangyan Yi, Jianhua Tao, Zhengkun Tian, Zhengqi Wen, Shuai Zhang
http://arxiv.org/abs/2102.07594v1

• [cs.CL]Generating Diversified Comments via Reader-Aware Topic Modeling and Saliency Detection
Wei Wang, Piji Li, Hai-Tao Zheng
http://arxiv.org/abs/2102.06856v1

• [cs.CL]Improved Customer Transaction Classification using Semi-Supervised Knowledge Distillation
Rohan Sukumaran
http://arxiv.org/abs/2102.07635v1

• [cs.CL]Interactive Learning from Activity Description
Khanh Nguyen, Dipendra Misra, Robert Schapire, Miro Dudík, Patrick Shafto
http://arxiv.org/abs/2102.07024v1

• [cs.CL]Leveraging Acoustic and Linguistic Embeddings from Pretrained speech and language Models for Intent Classification
Bidisha Sharma, Maulik Madhavi, Haizhou Li
http://arxiv.org/abs/2102.07370v1

• [cs.CL]MAPGN: MAsked Pointer-Generator network for sequence-to-sequence pre-training
Mana Ihori, Naoki Makishima, Tomohiro Tanaka, Akihiko Takashima, Shota Orihashi, Ryo Masumura
http://arxiv.org/abs/2102.07380v1

• [cs.CL]MATCH: Metadata-Aware Text Classification in A Large Hierarchy
Yu Zhang, Zhihong Shen, Yuxiao Dong, Kuansan Wang, Jiawei Han
http://arxiv.org/abs/2102.07349v1

• [cs.CL]PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them
Patrick Lewis, Yuxiang Wu, Linqing Liu, Pasquale Minervini, Heinrich Küttler, Aleksandra Piktus, Pontus Stenetorp, Sebastian Riedel
http://arxiv.org/abs/2102.07033v1

• [cs.CL]Personalization Strategies for End-to-End Speech Recognition Systems
Aditya Gourav, Linda Liu, Ankur Gandhe, Yile Gu, Guitang Lan, Xiangyang Huang, Shashank Kalmane, Gautam Tiwari, Denis Filimonov, Ariya Rastrow, Andreas Stolcke, Ivan Bulyko
http://arxiv.org/abs/2102.07739v1

• [cs.CL]Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm
Laria Reynolds, Kyle McDonell
http://arxiv.org/abs/2102.07350v1

• [cs.CL]Query-by-Example Keyword Spotting system using Multi-head Attention and Softtriple Loss
Jinmiao Huang, Waseem Gharbieh, Han Suk Shim, Eugene Kim
http://arxiv.org/abs/2102.07061v1

• [cs.CL]Structural Information Preserving for Graph-to-Text Generation
Linfeng Song, Ante Wang, Jinsong Su, Yue Zhang, Kun Xu, Yubin Ge, Dong Yu
http://arxiv.org/abs/2102.06749v1

• [cs.CL]The first large scale collection of diverse Hausa language datasets
Isa Inuwa-Dutse
http://arxiv.org/abs/2102.06991v1

• [cs.CL]They, Them, Theirs: Rewriting with Gender-Neutral English
Tony Sun, Kellie Webster, Apu Shah, William Yang Wang, Melvin Johnson
http://arxiv.org/abs/2102.06788v1

• [cs.CL]indicnlp@kgp at DravidianLangTech-EACL2021: Offensive Language Identification in Dravidian Languages
Kushal Kedia, Abhilash Nandy
http://arxiv.org/abs/2102.07150v1

• [cs.CR]GPSPiChain-Blockchain based Self-Contained Family Security System in Smart Home
Ali Raza, Lachlan Hardy, Erin Roehrer, Soonja Yeom, Byeong ho Kang
http://arxiv.org/abs/2102.06884v1

• [cs.CR]Multi-class Classification Based Anomaly Detection of Insider Activities
R G Gayathri, Atul Sajjanhar, Yong Xiang, Xingjun Ma
http://arxiv.org/abs/2102.07277v1

• [cs.CR]Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPS
Felix Olowononi, Danda B. Rawat, Chunmei Liu
http://arxiv.org/abs/2102.07244v1

• [cs.CR]Towards reliable and transparent vaccine phase III trials with smart contracts
Ivan da Silva Sendin, Rodrigo Sanches Miani
http://arxiv.org/abs/2102.07022v1

• [cs.CV]3D Fully Convolutional Neural Networks with Intersection Over Union Loss for Crop Mapping from Multi-Temporal Satellite Images
Sina Mohammadi, Mariana Belgiu, Alfred Stein
http://arxiv.org/abs/2102.07280v1

• [cs.CV]A Gated Fusion Network for Dynamic Saliency Prediction
Aysun Kocak, Erkut Erdem, Aykut Erdem
http://arxiv.org/abs/2102.07682v1

• [cs.CV]A Global to Local Double Embedding Method for Multi-person Pose Estimation
Yiming Xu, Jiaxin Li, Yiheng Peng, Yan Ding, Hua-Liang Wei
http://arxiv.org/abs/2102.07318v1

• [cs.CV]A novel method for object detection using deep learning and CAD models
Igor Garcia Ballhausen Sampaio, Luigy Machaca, José Viterbo, Joris Guérin
http://arxiv.org/abs/2102.06729v1

• [cs.CV]Adversarial Unsupervised Domain Adaptation Guided with Deep Clustering for Face Presentation Attack Detection
Yomna Safaa El-Din, Mohamed N. Moustafa, Hani Mahdi
http://arxiv.org/abs/2102.06864v1

• [cs.CV]CPP-Net: Context-aware Polygon Proposal Network for Nucleus Segmentation
Shengcong Chen, Changxing Ding, Minfeng Liu, Dacheng Tao
http://arxiv.org/abs/2102.06867v1

• [cs.CV]Capturing Detailed Deformations of Moving Human Bodies
He Chen, Hyojoon Park, Kutay Macit, Ladislav Kavan
http://arxiv.org/abs/2102.07343v1

• [cs.CV]DeepRA: Predicting Joint Damage From Radiographs Using CNN with Attention
Neelambuj Chaturvedi
http://arxiv.org/abs/2102.06982v1

• [cs.CV]FAT: Learning Low-Bitwidth Parametric Representation via Frequency-Aware Transformation
Chaofan Tao, Rui Lin, Quan Chen, Zhaoyang Zhang, Ping Luo, Ngai Wong
http://arxiv.org/abs/2102.07444v1

• [cs.CV]Fast, Accurate Barcode Detection in Ultra High-Resolution Images
Jerome Quenum, Kehan Wang, Avideh Zakhor
http://arxiv.org/abs/2102.06868v1

• [cs.CV]Generation for adaption: a Gan-based approach for 3D Domain Adaption inPoint Cloud
Junxuan Huang, Chunming Qiao
http://arxiv.org/abs/2102.07373v1

• [cs.CV]INSTA-YOLO: Real-Time Instance Segmentation
Eslam Mohamed, Abdelrahman Shaker, Hazem Rashed, Ahmad El-Sallab, Mayada Hadhoud
http://arxiv.org/abs/2102.06777v1

• [cs.CV]Improving Automated Visual Fault Detection by Combining a Biologically Plausible Model of Visual Attention with Deep Learning
Frederik Beuth, Tobias Schlosser, Michael Friedrich, Danny Kowerko
http://arxiv.org/abs/2102.06955v1

• [cs.CV]Learning Intra-Batch Connections for Deep Metric Learning
Jenny Seidenschwarz, Ismail Elezi, Laura Leal-Taixé
http://arxiv.org/abs/2102.07753v1

• [cs.CV]Learning Speech-driven 3D Conversational Gestures from Video
Ikhsanul Habibie, Weipeng Xu, Dushyant Mehta, Lingjie Liu, Hans-Peter Seidel, Gerard Pons-Moll, Mohamed Elgharib, Christian Theobalt
http://arxiv.org/abs/2102.06837v1

• [cs.CV]Multi-class Generative Adversarial Nets for Semi-supervised Image Classification
Saman Motamed, Farzad Khalvati
http://arxiv.org/abs/2102.06944v1

• [cs.CV]Naturalizing Neuromorphic Vision Event Streams Using GANs
Dennis Robey, Wesley Thio, Herbert Iu, Jason Eshraghian
http://arxiv.org/abs/2102.07243v1

• [cs.CV]OmniDet: Surround View Cameras based Multi-task Visual Perception Network for Autonomous Driving
Varun Ravi Kumar, Senthil Yogamani, Hazem Rashed, Ganesh Sitsu, Christian Witt, Isabelle Leang, Stefan Milz, Patrick Mäder
http://arxiv.org/abs/2102.07448v1

• [cs.CV]QuickBrowser: A Unified Model to Detect and Read Simple Object in Real-time
Thao Do, Daeyoung Kim
http://arxiv.org/abs/2102.07354v1

• [cs.CV]RMS-Net: Regression and Masking for Soccer Event Spotting
Matteo Tomei, Lorenzo Baraldi, Simone Calderara, Simone Bronzin, Rita Cucchiara
http://arxiv.org/abs/2102.07624v1

• [cs.CV]Rotation-Equivariant Deep Learning for Diffusion MRI
Philip Müller, Vladimir Golkov, Valentina Tomassini, Daniel Cremers
http://arxiv.org/abs/2102.06942v1

• [cs.CV]Saliency-Aware Class-Agnostic Food Image Segmentation
Sri Kalyan Yarlagadda, Daniel Mas Montserrat, David Guerra, Carol J. Boushey, Deborah A. Kerr, Fengqing Zhu
http://arxiv.org/abs/2102.06882v1

• [cs.CV]Segmenting two-dimensional structures with strided tensor networks
Raghavendra Selvan, Erik B Dam, Jens Petersen
http://arxiv.org/abs/2102.06900v1

• [cs.CV]Spatio-temporal Graph-RNN for Point Cloud Prediction
Pedro Gomes, Silvia Rossi, Laura Toni
http://arxiv.org/abs/2102.07482v1

• [cs.CV]Video Analytics on IoT devices
Sree Premkumar, Vimal Premkumar, Rakesh Dhakshinamurthy
http://arxiv.org/abs/2102.07455v1

• [cs.CV]Win-Fail Action Recognition
Paritosh Parmar, Brendan Morris
http://arxiv.org/abs/2102.07355v1

• [cs.CY]On the Value of Wikipedia as a Gateway to the Web
Tiziano Piccardi, Miriam Redi, Giovanni Colavizza, Robert West
http://arxiv.org/abs/2102.07385v1

• [cs.CY]Sociotechnical Challenges of eHealth Technology for Patient Self-Management: A Systematic Review
Stefan Hochwarter
http://arxiv.org/abs/2102.07119v1

• [cs.CY]Vehicle to Vehicle (V2V) Communication Protocol: Components, Benefits, Challenges, Safety and Machine Learning Applications
Ramya Daddanala, Vekata Mannava, Lo’ai Tawlbeh, Mohammad Al-Ramahi
http://arxiv.org/abs/2102.07306v1

• [cs.DC]Asynchronous Gossip in Smartphone Peer-to-Peer Networks
Calvin Newport, Alex Weaver, Chaodong Zheng
http://arxiv.org/abs/2102.06804v1

• [cs.DC]Byzantine Dispersion on Graphs
Anisur Rahaman Molla, Kaushik Mondal, William K. Moses Jr
http://arxiv.org/abs/2102.07528v1

• [cs.DC]Good-case Latency of Byzantine Broadcast: a Complete Categorization
Ittai Abraham, Kartik Nayak, Ling Ren, Zhuolun Xiang
http://arxiv.org/abs/2102.07240v1

• [cs.DC]Hugo: A Cluster Scheduler that Efficiently Learns to Select Complementary Data-Parallel Jobs
Lauritz Thamsen, Ilya Verbitskiy, Sasho Nedelkoski, Vinh Thuy Tran, Vinicius Meyer, Miguel G. Xavier, Odej Kao, Cesar A. F. De Rose
http://arxiv.org/abs/2102.07199v1

• [cs.DC]MATCH: An MPI Fault Tolerance Benchmark Suite
Luanzheng Guo, Giorgis Georgakoudis, Konstantinos Parasyris, Ignacio Laguna, Dong Li
http://arxiv.org/abs/2102.06894v1

• [cs.DC]MOARD: Modeling Application Resilience to Transient Faults on Data Objects
Luanzheng Guo, Dong Li
http://arxiv.org/abs/2102.06899v1

• [cs.DC]Near-Optimal Scheduling in the Congested Clique
Keren Censor-Hillel, Yannic Maus, Volodymyr Polosukhin
http://arxiv.org/abs/2102.07221v1

• [cs.DC]Reinit++: Evaluating the Performance of Global-Restart Recovery Methods For MPI Fault Tolerance
Giorgis Georgakoudis, Luanzheng Guo, Ignacio Laguna
http://arxiv.org/abs/2102.06896v1

• [cs.DC]Simulation-based Optimization and Sensibility Analysis of MPI Applications: Variability Matters
Tom Cornebize, Arnaud Legrand
http://arxiv.org/abs/2102.07674v1

• [cs.DL]Impact of h-index on authors ranking: A comparative analysis of Scopus and WoS
Parul Khurana, Kiran Sharma
http://arxiv.org/abs/2102.06964v1

• [cs.DS]Fair and Optimal Cohort Selection for Linear Utilities
Konstantina Bairaktari, Huy Le Nguyen, Jonathan Ullman
http://arxiv.org/abs/2102.07684v1

• [cs.GT]Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games
Dustin Morrill, Ryan D’Orazio, Marc Lanctot, James R. Wright, Michael Bowling, Amy Greenwald
http://arxiv.org/abs/2102.06973v1

• [cs.GT]Mixed Nash Equilibria in the Adversarial Examples Game
Laurent Meunier, Meyer Scetbon, Rafael Pinot, Jamal Atif, Yann Chevaleyre
http://arxiv.org/abs/2102.06905v1

• [cs.GT]Multi-Stage Decentralized Matching Markets: Uncertain Preferences and Strategic Behaviors
Xiaowu Dai, Michael I. Jordan
http://arxiv.org/abs/2102.06988v1

• [cs.GT]ScrofaZero: Mastering Trick-taking Poker Game Gongzhu by Deep Reinforcement Learning
Naichen Shi, Ruichen Li, Sun Youran
http://arxiv.org/abs/2102.07495v1

• [cs.HC]CHARET: Character-centered Approach to Emotion Tracking in Stories
Diogo S. Carvalho, Joana Campos, Manuel Guimarães, Ana Antunes, João Dias, Pedro A. Santos
http://arxiv.org/abs/2102.07537v1

• [cs.HC]Confidence-Aware Learning Assistant
Shoya Ishimaru, Takanori Maruichi, Andreas Dengel, Koichi Kise
http://arxiv.org/abs/2102.07312v1

• [cs.IR]Distillation based Multi-task Learning: A Candidate Generation Model for Improving Reading Duration
Zhong Zhao, Yanmei Fu, Hanming Liang, Li Ma, Guangyao Zhao, Hongwei Jiang
http://arxiv.org/abs/2102.07142v1

• [cs.IR]Learning Intents behind Interactions with Knowledge Graph for Recommendation
Xiang Wang, Tinglin Huang, Dingxian Wang, Yancheng Yuan, Zhenguang Liu, Xiangnan He, Tat-Seng Chua
http://arxiv.org/abs/2102.07057v1

• [cs.IR]Learning a Product Relevance Model from Click-Through Data in E-Commerce
Shaowei Yao, Jiwei Tan, Xi Chen, Keping Yang, Rong Xiao, Hongbo Deng, Xiaojun Wan
http://arxiv.org/abs/2102.07098v1

• [cs.IR]Leveraging User Behavior History for Personalized Email Search
Keping Bi, Pavel Metrikov, Chunyuan Li, Byungki Byun
http://arxiv.org/abs/2102.07279v1

• [cs.IR]Model Synthesis for Communication Traces of System-on-Chip Designs
Hao Zheng, Md Rubel Ahmed, Parijat Mukherjee, Mahesh C. Ketkar, Jin Yang
http://arxiv.org/abs/2102.06989v1

• [cs.IR]Overview of the TREC 2020 deep learning track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos
http://arxiv.org/abs/2102.07662v1

• [cs.IR]Supporting search engines with knowledge and context
Nikos Voskarides
http://arxiv.org/abs/2102.06762v1

• [cs.IR]User Embedding based Neighborhood Aggregation Method for Inductive Recommendation
Rahul Ragesh, Sundararajan Sellamanickam, Vijay Lingam, Arun Iyer, Ramakrishna Bairi
http://arxiv.org/abs/2102.07575v1

• [cs.IR]UserReg: A Simple but Strong Model for Rating Prediction
Haiyang Zhang, Ivan Ganchev, Nikola S. Nikolov, Mark Stevenson
http://arxiv.org/abs/2102.07601v1

• [cs.IT]A Deterministic Algorithm for Computing the Weight Distribution of Polar Codes
Hanwen Yao, Arman Fazeli, Alexander Vardy
http://arxiv.org/abs/2102.07362v1

• [cs.IT]A Further Note on an Innovations Approach to Viterbi Decoding of Convolutional Codes
Masato Tajima
http://arxiv.org/abs/2102.07315v1

• [cs.IT]A Theoretical Performance Bound for Joint Beamformer Design of Wireless Fronthaul and Access Links in Downlink C-RAN
Fehmi Emre Kadan, Ali Özgür Yılmaz
http://arxiv.org/abs/2102.06922v1

• [cs.IT]Alternative Detectors for Spectrum Sensing by Exploiting Excess Bandwidth
Sirvan Gharib, Abolfazl Falahati, Vahid Ahmadi
http://arxiv.org/abs/2102.06969v1

• [cs.IT]Beamformer Design with Smooth Constraint-Free Approximation in Downlink Cloud Radio Access Networks
Fehmi Emre Kadan, Ali Özgür Yılmaz
http://arxiv.org/abs/2102.06916v1

• [cs.IT]CQNet: Complex Input Quantized Neural Network designed for Massive MIMO CSI Feedback
Sijie Ji, Weiping Sun, Mo Li
http://arxiv.org/abs/2102.07507v1

• [cs.IT]DNA codes over two noncommutative rings of order four
Jon-Lark Kim, Dong Eun Ohk
http://arxiv.org/abs/2102.06981v1

• [cs.IT]Fluctuation-response theorem for Kullback-Leibler divergences to quantify causation
Andrea Auconi, Benjamin M. Friedrich, Andrea Giansanti
http://arxiv.org/abs/2102.06839v1

• [cs.IT]Galois hulls of cyclic serial codes over a finite chain ring
Sarra Talbi, Aicha Batoul, Alexandre Fotue Tabue, Edgar Martínez-Moro
http://arxiv.org/abs/2102.06995v1

• [cs.IT]Intermittent Status Updating Through Joint Scheduling of Sensing and Retransmissions
Omur Ozel, Parisa Rafiee
http://arxiv.org/abs/2102.07075v1

• [cs.IT]Joint Rate Distortion Function of a Tuple of Correlated Multivariate Gaussian Sources with Individual Fidelity Criteria
Evagoras Stylianou, Charalambos D. Charalambous, Themistoklis Charalambous
http://arxiv.org/abs/2102.07236v1

• [cs.IT]MIMO Interference Channels Assisted by Reconfigurable Intelligent Surfaces: Mutual Coupling Aware Sum-Rate Optimization Based on a Mutual Impedance Channel Model
Andrea Abrardo, Davide Dardari, Marco Di Renzo, Xuewen Qian
http://arxiv.org/abs/2102.07155v1

• [cs.IT]Max-Min Fair Hybrid Precoding for Multi-group Multicasting in Millimeter-Wave Channel
Fawwaz Alsubaie
http://arxiv.org/abs/2102.07174v1

• [cs.IT]Multi-Class Unsourced Random Access via Coded Demixing
Vamsi K. Amalladinne, Allen Hao, Stefano Rini, Jean-Francois Chamberland
http://arxiv.org/abs/2102.07704v1

• [cs.IT]Multipair Two-Way DF Relaying with Cell-Free Massive MIMO
Anastasios K. Papazafeiropoulos, Pandelis Kourtessis, Symeon Chatzinotas, John M. Senior
http://arxiv.org/abs/2102.07144v1

• [cs.IT]Reconfigurable Intelligent Surfaces in 6G: Reflective, Transmissive, or Both?
Shuhao Zeng, Hongliang Zhang, Boya Di, Yunhua Tan, Zhu Han, H. Vincent Poor, Lingyang Song
http://arxiv.org/abs/2102.06910v1

• [cs.IT]Scalable Vector Gaussian Information Bottleneck
Mohammad Mahdi Mahvari, Mari Kobayashi, Abdellatif Zaidi
http://arxiv.org/abs/2102.07525v1

• [cs.IT]Sequential prediction under log-loss with side information
Alankrita Bhatt, Young-Han Kim
http://arxiv.org/abs/2102.06855v1

• [cs.IT]Seven Defining Features of Terahertz (THz) Wireless Systems: A Fellowship of Communication and Sensing
Christina Chaccour, Mehdi Naderi Soorki, Walid Saad, Mehdi Bennis, Petar Popovski, Merouane Debbah
http://arxiv.org/abs/2102.07668v1

• [cs.IT]Task-oriented Communication System Design in Cyber-Physical Systems: A Survey on Theory and Applications
Arsham Mostaani, Thang X. Vu, Symeon Chatzinotas
http://arxiv.org/abs/2102.07166v1

• [cs.IT]Timely Transmissions Using Optimized Variable Length Coding
Ahmed Arafa, Richard D. Wesel
http://arxiv.org/abs/2102.07756v1

• [cs.IT]Undoing Causal Effects of a Causal Broadcast Channel with Cooperating Receivers using Entanglement Resources
Stephen DiAdamo, Janis Nötzel
http://arxiv.org/abs/2102.07427v1

• [cs.LG]A Data Quality-Driven View of MLOps
Cedric Renggli, Luka Rimanic, Nezihe Merve Gürel, Bojan Karlaš, Wentao Wu, Ce Zhang
http://arxiv.org/abs/2102.07750v1

• [cs.LG]A Deep Adversarial Model for Suffix and Remaining Time Prediction of Event Sequences
Farbod Taymouri, Marcello La Rosa, Sarah M. Erfani
http://arxiv.org/abs/2102.07298v1

• [cs.LG]A Forward Backward Greedy approach for Sparse Multiscale Learning
Prashant Shekhar, Abani Patra
http://arxiv.org/abs/2102.07068v1

• [cs.LG]A New Algorithm for Hidden Markov Models Learning Problem
Taha Mansouri, Mohamadreza Sadeghimoghadam, Iman Ghasemian Sahebi
http://arxiv.org/abs/2102.07112v1

• [cs.LG]A Simple Deep Equilibrium Model Converges to Global Optima with Weight Tying
Kenji Kawaguchi
http://arxiv.org/abs/2102.07346v1

• [cs.LG]A closer look at temporal variability in dynamic online learning
Nicolò Campolongo, Francesco Orabona
http://arxiv.org/abs/2102.07666v1

• [cs.LG]A first look into the carbon footprint of federated learning
Xinchi Qiu, Titouan Parcollet, Javier Fernandez-Marques, Pedro Porto Buarque de Gusmao, Daniel J. Beutel, Taner Topal, Akhil Mathur, Nicholas D. Lane
http://arxiv.org/abs/2102.07627v1

• [cs.LG]A generalized quadratic loss for SVM and Deep Neural Networks
Filippo Portera
http://arxiv.org/abs/2102.07606v1

• [cs.LG]Achieving Linear Convergence in Federated Learning under Objective and Systems Heterogeneity
Aritra Mitra, Rayana Jaafar, George J. Pappas, Hamed Hassani
http://arxiv.org/abs/2102.07053v1

• [cs.LG]Adversarial Attack on Network Embeddings via Supervised Network Poisoning
Viresh Gupta, Tanmoy Chakraborty
http://arxiv.org/abs/2102.07164v1

• [cs.LG]Almost Optimal Algorithms for Two-player Markov Games with Linear Function Approximation
Zixiang Chen, Dongruo Zhou, Quanquan Gu
http://arxiv.org/abs/2102.07404v1

• [cs.LG]And/or trade-off in artificial neurons: impact on adversarial robustness
Alessandro Fontana
http://arxiv.org/abs/2102.07389v1

• [cs.LG]Approximation to Object Conditional Validity with Conformal Predictors
Anthony Bellotti
http://arxiv.org/abs/2102.07436v1

• [cs.LG]Attribution Mask: Filtering Out Irrelevant Features By Recursively Focusing Attention on Inputs of DNNs
Jae-Hong Lee, Joon-Hyuk Chang
http://arxiv.org/abs/2102.07332v1

• [cs.LG]Bridging Graph Neural Networks and Statistical Relational Learning: Relational One-Class GCN
Devendra Singh Dhami, Siwen Yan, Sriraam Natarajan
http://arxiv.org/abs/2102.07007v1

• [cs.LG]CAP-GAN: Towards_Adversarial_Robustness_with_Cycle-consistent_Attentional_Purification
Mingu Kang, Trung Quang Tran, Seungju Cho, Daeyoung Kim
http://arxiv.org/abs/2102.07304v1

• [cs.LG]CATE: Computation-aware Neural Architecture Encoding with Transformers
Shen Yan, Kaiqiang Song, Fei Liu, Mi Zhang
http://arxiv.org/abs/2102.07108v1

• [cs.LG]Comprehensive Comparative Study of Multi-Label Classification Methods
Jasmin Bogatinovski, Ljupčo Todorovski, Sašo Džeroski, Dragi Kocev
http://arxiv.org/abs/2102.07113v1

• [cs.LG]Compression phase is not necessary for generalization in representation learning
Sungyeop Lee, Junghyo Jo
http://arxiv.org/abs/2102.07402v1

• [cs.LG]Connecting Interpretability and Robustness in Decision Trees through Separation
Michal Moshkovitz, Yao-Yuan Yang, Kamalika Chaudhuri
http://arxiv.org/abs/2102.07048v1

• [cs.LG]Costly Features Classification using Monte Carlo Tree Search
Ziheng Chen, Jin Huang, Hongshik Ahn, Xin Ning
http://arxiv.org/abs/2102.07073v1

• [cs.LG]Cross-domain Time Series Forecasting with Attention Sharing
Xiaoyong Jin, Youngsuk Park, Danielle Maddix, Bernie Wang, Xifeng Yan
http://arxiv.org/abs/2102.06828v1

• [cs.LG]CrossLight: A Cross-Layer Optimized Silicon Photonic Neural Network Accelerator
Febin Sunny, Asif Mirza, Mahdi Nikdast, Sudeep Pasricha
http://arxiv.org/abs/2102.06960v1

• [cs.LG]DAC: Deep Autoencoder-based Clustering, a General Deep Learning Framework of Representation Learning
Si Lu, Ruisi Li
http://arxiv.org/abs/2102.07472v1

• [cs.LG]Data Profiling for Adversarial Training: On the Ruin of Problematic Data
Chengyu Dong, Liyuan Liu, Jingbo Shang
http://arxiv.org/abs/2102.07437v1

• [cs.LG]Deep Co-Attention Network for Multi-View Subspace Learning
Lecheng Zheng, Yu Cheng, Hongxia Yang, Nan Cao, Jingrui He
http://arxiv.org/abs/2102.07751v1

• [cs.LG]Demystifying Inductive Biases for -VAE Based Architectures
Dominik Zietlow, Michal Rolinek, Georg Martius
http://arxiv.org/abs/2102.06822v1

• [cs.LG]Developing parsimonious ensembles using predictor diversity within a reinforcement learning framework
Ana Stanescu, Gaurav Pandey
http://arxiv.org/abs/2102.07344v1

• [cs.LG]Distilling Double Descent
Andrew Cotter, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sashank J. Reddi, Yichen Zhou
http://arxiv.org/abs/2102.06849v1

• [cs.LG]Distributed Online Learning for Joint Regret with Communication Constraints
Dirk van der Hoeven, Hédi Hadiji, Tim van Erven
http://arxiv.org/abs/2102.07521v1

• [cs.LG]Distributed Second Order Methods with Fast Rates and Compressed Communication
Rustem Islamov, Xun Qian, Peter Richtárik
http://arxiv.org/abs/2102.07158v1

• [cs.LG]Does Standard Backpropagation Forget Less Catastrophically Than Adam?
Dylan R. Ashley, Sina Ghiassian, Richard S. Sutton
http://arxiv.org/abs/2102.07686v1

• [cs.LG]Domain Adversarial Reinforcement Learning
Bonnie Li, Vincent François-Lavet, Thang Doan, Joelle Pineau
http://arxiv.org/abs/2102.07097v1

• [cs.LG]Doping: A technique for efficient compression of LSTM models using sparse structured additive matrices
Urmish Thakker, Paul N. Whatmough, Zhigang Liu, Matthew Mattina, Jesse Beu
http://arxiv.org/abs/2102.07071v1

• [cs.LG]Equilibrium Inverse Reinforcement Learning for Ride-hailing Vehicle Network
Takuma Oda
http://arxiv.org/abs/2102.06854v1

• [cs.LG]Exploiting Shared Representations for Personalized Federated Learning
Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai
http://arxiv.org/abs/2102.07078v1

• [cs.LG]Exploring Adversarial Robustness of Deep Metric Learning
Thomas Kobber Panum, Zi Wang, Pengyu Kan, Earlence Fernandes, Somesh Jha
http://arxiv.org/abs/2102.07265v1

• [cs.LG]FedBN: Federated Learning on Non-IID Features via Local Batch Normalization
Xiaoxiao Li, Meirui Jiang, Xiaofei Zhang, Michael Kamp, Qi Dou
http://arxiv.org/abs/2102.07623v1

• [cs.LG]FedU: A Unified Framework for Federated Multi-Task Learning with Laplacian Regularization
Canh T. Dinh, Tung T. Vu, Nguyen H. Tran, Minh N. Dao, Hongyu Zhang
http://arxiv.org/abs/2102.07148v1

• [cs.LG]Generating Structured Adversarial Attacks Using Frank-Wolfe Method
Ehsan Kazemi, Thomas Kerdreux, Liquang Wang
http://arxiv.org/abs/2102.07360v1

• [cs.LG]Geometric feature performance under downsampling for EEG classification tasks
Bryan Bischof, Eric Bunch
http://arxiv.org/abs/2102.07669v1

• [cs.LG]GradPIM: A Practical Processing-in-DRAM Architecture for Gradient Descent
Heesu Kim, Hanmin Park, Taehyun Kim, Kwanheum Cho, Eojin Lee, Soojung Ryu, Hyuk-Jae Lee, Kiyoung Choi, Jinho Lee
http://arxiv.org/abs/2102.07511v1

• [cs.LG]Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization
Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath
http://arxiv.org/abs/2102.06966v1

• [cs.LG]Guided Interpolation for Adversarial Training
Chen Chen, Jingfeng Zhang, Xilie Xu, Tianlei Hu, Gang Niu, Gang Chen, Masashi Sugiyama
http://arxiv.org/abs/2102.07327v1

• [cs.LG]High-Dimensional Gaussian Process Inference with Derivatives
Filip de Roos, Alexandra Gessner, Philipp Hennig
http://arxiv.org/abs/2102.07542v1

• [cs.LG]How Framelets Enhance Graph Neural Networks
Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yu Guang Wang, Pietro Lio, Ming Li, Guido Montufar
http://arxiv.org/abs/2102.06986v1

• [cs.LG]How to Learn when Data Reacts to Your Model: Performative Gradient Descent
Zachary Izzo, Lexing Ying, James Zou
http://arxiv.org/abs/2102.07698v1

• [cs.LG]Hybrid Artificial Intelligence Methods for Predicting Air Demand in Dam Bottom Outlet
Aliakbar Narimani, Mahdi Moghimi, Amir Mosavi
http://arxiv.org/abs/2102.06929v1

• [cs.LG]Improved Corruption Robust Algorithms for Episodic Reinforcement Learning
Yifang Chen, Simon S. Du, Kevin Jamieson
http://arxiv.org/abs/2102.06875v1

• [cs.LG]Intelligent Electric Vehicle Charging Recommendation Based on Multi-Agent Reinforcement Learning
Weijia Zhang, Hao Liu, Fan Wang, Tong Xu, Haoran Xin, Dejing Dou, Hui Xiong
http://arxiv.org/abs/2102.07359v1

• [cs.LG]Intermediate Layer Optimization for Inverse Problems using Deep Generative Models
Giannis Daras, Joseph Dean, Ajil Jalal, Alexandros G. Dimakis
http://arxiv.org/abs/2102.07364v1

• [cs.LG]Knowledge Graph Embedding using Graph Convolutional Networks with Relation-Aware Attention
Nasrullah Sheikh, Xiao Qin, Berthold Reinwald, Christoph Miksovic, Thomas Gschwind, Paolo
cc7
Scotton
http://arxiv.org/abs/2102.07200v1

• [cs.LG]Large-Scale Meta-Learning with Continual Trajectory Shifting
Jaewoong Shin, Hae Beom Lee, Boqing Gong, Sung Ju Hwang
http://arxiv.org/abs/2102.07215v1

• [cs.LG]Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent
Ajaykrishna Karthikeyan, Naman Jain, Nagarajan Natarajan, Prateek Jain
http://arxiv.org/abs/2102.07567v1

• [cs.LG]Learning image quality assessment by reinforcing task amenable data selection
Shaheer U. Saeed, Yunguan Fu, Zachary M. C. Baum, Qianye Yang, Mirabela Rusu, Richard E. Fan, Geoffrey A. Sonn, Dean C. Barratt, Yipeng Hu
http://arxiv.org/abs/2102.07615v1

• [cs.LG]Learning-Driven Decision Mechanisms in Physical Layer: Facts, Challenges, and Remedies
Selen Gecgel, Caner Goztepe, Gunes Karabulut Kurt, Halim Yanikomeroglu
http://arxiv.org/abs/2102.07258v1

• [cs.LG]Machine Learning Methods for the Design and Operation of Liquid Rocket Engines — Research Activities at the DLR Institute of Space Propulsion
Günther Waxenegger-Wilfing, Kai Dresia, Jan Deeken, Michael Oschwald
http://arxiv.org/abs/2102.07109v1

• [cs.LG]Maximizing Joint Entropy for Batch-Mode Active Learning of Perceptual Metrics
Priyadarshini Kumari, Sidhdhartha Chaudhuri, Vivek Borkar, Subhasis Chaudhuri
http://arxiv.org/abs/2102.07365v1

• [cs.LG]Model-Agnostic Graph Regularization for Few-Shot Learning
Ethan Shen, Maria Brbic, Nicholas Monath, Jiaqi Zhai, Manzil Zaheer, Jure Leskovec
http://arxiv.org/abs/2102.07077v1

• [cs.LG]Model-free Representation Learning and Exploration in Low-rank MDPs
Aditya Modi, Jinglin Chen, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal
http://arxiv.org/abs/2102.07035v1

• [cs.LG]Multi-Objective Meta Learning
Feiyang Ye, Baijiong Lin, Zhixiong Yue, Pengxin Guo, Qiao Xiao, Yu Zhang
http://arxiv.org/abs/2102.07121v1

• [cs.LG]Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation
Yue Wu, Dongruo Zhou, Quanquan Gu
http://arxiv.org/abs/2102.07301v1

• [cs.LG]Network of Tensor Time Series
Baoyu Jing, Hanghang Tong, Yada Zhu
http://arxiv.org/abs/2102.07736v1

• [cs.LG]Neural Network Compression for Noisy Storage Devices
Berivan Isik, Kristy Choi, Xin Zheng, Tsachy Weissman, Stefano Ermon, H. -S. Philip Wong, Armin Alaghi
http://arxiv.org/abs/2102.07725v1

• [cs.LG]Neuro-algorithmic Policies enable Fast Combinatorial Generalization
Marin Vlastelica, Michal Rolínek, Georg Martius
http://arxiv.org/abs/2102.07456v1

• [cs.LG]On Robust Optimal Transport: Computational Complexity, Low-rank Approximation, and Barycenter Computation
Khang Le, Huy Nguyen, Quang Nguyen, Nhat Ho, Tung Pham, Hung Bui
http://arxiv.org/abs/2102.06857v1

• [cs.LG]On the Impact of Device and Behavioral Heterogeneity in Federated Learning
Ahmed M. Abdelmoniem, Chen-Yu Ho, Pantelis Papageorgiou, Muhammad Bilal, Marco Canini
http://arxiv.org/abs/2102.07500v1

• [cs.LG]On the Inherent Regularization Effects of Noise Injection During Training
Oussama Dhifallah, Yue M. Lu
http://arxiv.org/abs/2102.07379v1

• [cs.LG]On the Last Iterate Convergence of Momentum Methods
Xiaoyu Li, Mingrui Liu, Francesco Orabona
http://arxiv.org/abs/2102.07002v1

• [cs.LG]On the convergence of group-sparse autoencoders
Emmanouil Theodosis, Bahareh Tolooshams, Pranay Tankala, Abiy Tasissa, Demba Ba
http://arxiv.org/abs/2102.07003v1

• [cs.LG]One-shot learning for the long term: consolidation with an artificial hippocampal algorithm
Gideon Kowadlo, Abdelrahman Ahmed, David Rawlinson
http://arxiv.org/abs/2102.07503v1

• [cs.LG]Online Apprenticeship Learning
Lior Shani, Tom Zahavy, Shie Mannor
http://arxiv.org/abs/2102.06924v1

• [cs.LG]Optimal Regret Algorithm for Pseudo-1d Bandit Convex Optimization
Aadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli, Prateek Jain
http://arxiv.org/abs/2102.07387v1

• [cs.LG]PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators
Anish Agarwal, Abdullah Alomar, Varkey Alumootil, Devavrat Shah, Dennis Shen, Zhi Xu, Cindy Yang
http://arxiv.org/abs/2102.06961v1

• [cs.LG]Perceptually Constrained Adversarial Attacks
Muhammad Zaid Hameed, Andras Gyorgy
http://arxiv.org/abs/2102.07140v1

• [cs.LG]Reconstruction-Based Membership Inference Attacks are Easier on Difficult Problems
Avital Shafran, Shmuel Peleg, Yedid Hoshen
http://arxiv.org/abs/2102.07762v1

• [cs.LG]Reinforcement Learning for IoT Security: A Comprehensive Survey
Aashma Uprety, Danda B. Rawat
http://arxiv.org/abs/2102.07247v1

• [cs.LG]Relation-aware Graph Attention Model With Adaptive Self-adversarial Training
Xiao Qin, Nasrullah Sheikh, Berthold Reinwald, Lingfei Wu
http://arxiv.org/abs/2102.07186v1

• [cs.LG]Reversible Action Design for Combinatorial Optimization with Reinforcement Learning
Fan Yao, Renqin Cai, Hongning Wang
http://arxiv.org/abs/2102.07210v1

• [cs.LG]Revisiting Smoothed Online Learning
Lijun Zhang, Wei Jiang, Shiyin Lu, Tianbao Yang
http://arxiv.org/abs/2102.06933v1

• [cs.LG]Robust Classification using Hidden Markov Models and Mixtures of Normalizing Flows
Anubhab Ghosh, Antoine Honoré, Dong Liu, Gustav Eje Henter, Saikat Chatterjee
http://arxiv.org/abs/2102.07284v1

• [cs.LG]Sample Efficient Subspace-based Representations for Nonlinear Meta-Learning
Halil Ibrahim Gulluk, Yue Sun, Samet Oymak, Maryam Fazel
http://arxiv.org/abs/2102.07206v1

• [cs.LG]Secure-UCB: Saving Stochastic Bandits from Poisoning Attacks via Limited Data Verification
Anshuka Rangi, Long Tran-Thanh, Haifeng Xu, Massimo Franceschetti
http://arxiv.org/abs/2102.07711v1

• [cs.LG]Self Regulated Learning Mechanism for Data Efficient Knowledge Distillation
Sourav Mishra, Suresh Sundaram
http://arxiv.org/abs/2102.07125v1

• [cs.LG]Self-Reorganizing and Rejuvenating CNNs for Increasing Model Capacity Utilization
Wissam J. Baddar, Seungju Han, Seonmin Rhee, Jae-Joon Han
http://arxiv.org/abs/2102.06870v1

• [cs.LG]Smoothness Matrices Beat Smoothness Constants: Better Communication Compression Techniques for Distributed Optimization
Mher Safaryan, Filip Hanzely, Peter Richtárik
http://arxiv.org/abs/2102.07245v1

• [cs.LG]Sparse Attention Guided Dynamic Value Estimation for Single-Task Multi-Scene Reinforcement Learning
Jaskirat Singh, Liang Zheng
http://arxiv.org/abs/2102.07266v1

• [cs.LG]TI-Capsule: Capsule Network for Stock Exchange Prediction
Ramin Mousa, Sara Nazari, Ali Karhe Abadi, Reza Shoukhcheshm, Mohammad Niknam Pirzadeh, Leila Safari
http://arxiv.org/abs/2102.07718v1

• [cs.LG]Technical Challenges for Training Fair Neural Networks
Valeriia Cherepanova, Vedant Nanda, Micah Goldblum, John P. Dickerson, Tom Goldstein
http://arxiv.org/abs/2102.06764v1

• [cs.LG]The Predictive Normalized Maximum Likelihood for Over-parameterized Linear Regression with Norm Constraint: Regret and Double Descent
Koby Bibas, Meir Feder
http://arxiv.org/abs/2102.07181v1

• [cs.LG]The Role of Momentum Parameters in the Optimal Convergence of Adaptive Polyak’s Heavy-ball Methods
Wei Tao, Sheng Long, Gaowei Wu, Qing Tao
http://arxiv.org/abs/2102.07314v1

• [cs.LG]ThetA — fast and robust clustering via a distance parameter
Eleftherios Garyfallidis, Shreyas Fadnavis, Jong Sung Park, Bramsh Qamar Chandio, Javier Guaje, Serge Koudoro, Nasim Anousheh
http://arxiv.org/abs/2102.07028v1

• [cs.LG]Tight lower bounds for Dynamic Time Warping
Geoffrey I. Webb, Francois Petitjean
http://arxiv.org/abs/2102.07076v1

• [cs.LG]Transfer Learning for Future Wireless Networks: A Comprehensive Survey
Cong T. Nguyen, Nguyen Van Huynh, Nam H. Chu, Yuris Mulya Saputra, Dinh Thai Hoang, Diep N. Nguyen, Quoc-Viet Pham, Dusit Niyato, Eryk Dutkiewicz, Won-Joo Hwang
http://arxiv.org/abs/2102.07572v1

• [cs.LG]Translational Equivariance in Kernelizable Attention
Max Horn, Kumar Shridhar, Elrich Groenewald, Philipp F. M. Baumann
http://arxiv.org/abs/2102.07680v1

• [cs.LG]Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning
Kento Nozawa, Issei Sato
http://arxiv.org/abs/2102.06866v1

• [cs.LG]Understanding self-supervised Learning Dynamics without Contrastive Pairs
Yuandong Tian, Xinlei Chen, Surya Ganguli
http://arxiv.org/abs/2102.06810v1

• [cs.LG]WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points
Albert No, Taeho Yoon, Se-Hyeon Kwon, Ernest K. Ryu
http://arxiv.org/abs/2102.07541v1

• [cs.LG]Wasserstein Proximal of GANs
Alex Tong Lin, Wuchen Li, Stanley Osher, Guido Montufar
http://arxiv.org/abs/2102.06862v1

• [cs.LG]Weak Adaptation Learning — Addressing Cross-domain Data Insufficiency with Weak Annotator
Shichao Xu, Lixu Wang, Yixuan Wang, Qi Zhu
http://arxiv.org/abs/2102.07358v1

• [cs.LG]Weight Initialization Techniques for Deep Learning Algorithms in Remote Sensing: Recent Trends and Future Perspectives
Wadii Boulila, Maha Driss, Mohamed Al-Sarem, Faisal Saeed, Moez Krichen
http://arxiv.org/abs/2102.07004v1

• [cs.MA]Cooperation and Reputation Dynamics with Reinforcement Learning
Nicolas Anastassacos, Julian García, Stephen Hailes, Mirco Musolesi
http://arxiv.org/abs/2102.07523v1

• [cs.MA]Modelling Cooperation in Network Games with Spatio-Temporal Complexity
Michiel A. Bakker, Richard Everett, Laura Weidinger, Iason Gabriel, William S. Isaac, Joel Z. Leibo, Edward Hughes
http://arxiv.org/abs/2102.06911v1

• [cs.MA]On the Equilibrium Elicitation of Markov Games Through Information Design
Tao Zhang, Quanyan Zhu
http://arxiv.org/abs/2102.07152v1

• [cs.MA]Partial Disclosure of Private Dependencies in Privacy Preserving Planning
Rotem Lev Lehman, Guy Shani, Roni Stern
http://arxiv.org/abs/2102.07185v1

• [cs.MA]Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing
Filippos Christianos, Georgios Papoudakis, Arrasy Rahman, Stefano V. Albrecht
http://arxiv.org/abs/2102.07475v1

• [cs.NE]HAWKS: Evolving Challenging Benchmark Sets for Cluster Analysis
Cameron Shand, Richard Allmendinger, Julia Handl, Andrew Webb, John Keane
http://arxiv.org/abs/2102.06940v1

• [cs.NE]Learning by Turning: Neural Architecture Aware Optimisation
Yang Liu, Jeremy Bernstein, Markus Meister, Yisong Yue
http://arxiv.org/abs/2102.07227v1

• [cs.NI]A Tale of Three Datasets: Towards Characterizing Mobile Broadband Access in the United States
Tarun Mangla, Esther Showalter, Vivek Adarsh, Kipp Jones, Morgan Vigil-Hayes, Elizabeth Belding, Ellen Zegura
http://arxiv.org/abs/2102.07288v1

• [cs.NI]On Topology Optimization and Routing in Integrated Access and Backhaul Networks: A Genetic Algorithm-based Approach
Charitha Madapatha, Behrooz Makki, Ajmal Muhammad, Erik Dahlman, Mohamed-Slim Alouini, Tommy Svensson
http://arxiv.org/abs/2102.07252v1

• [cs.NI]T-RACKs: A Faster Recovery Mechanism for TCP in Data Center Networks
Ahmed M. Abdelmoniem, Brahim Bensaou
http://arxiv.org/abs/2102.07477v1

• [cs.PF]An In-Depth Investigation of Performance Characteristics of Hyperledger Fabric
Tobias Guggenberger, Johannes Sedlmeir, Gilbert Fridgen, André Luckow
http://arxiv.org/abs/2102.07731v1

• [cs.RO]A Differentiable Contact Model to Extend Lagrangian and Hamiltonian Neural Networks for Modeling Hybrid Dynamics
Yaofeng Desmond Zhong, Biswadip Dey, Amit Chakraborty
http://arxiv.org/abs/2102.06794v1

• [cs.RO]Corrective Shared Autonomy for Addressing Task Variability
Michael Hagenow, Emmanuel Senft, Robert Radwin, Michael Gleicher, Bilge Mutlu, Michael Zinn
http://arxiv.org/abs/2102.07165v1

• [cs.RO]DiffCo: Auto-Differentiable Proxy Collision Detection with Multi-class Labels for Safety-Aware Trajectory Optimization
Yuheng Zhi, Nikhil Das, Michael Yip
http://arxiv.org/abs/2102.07413v1

• [cs.RO]Distributed Estimation, Control and Coordination of Quadcopter Swarm Robots
Zheng Jia, Michael Hamer, Raffaello D’Andrea
http://arxiv.org/abs/2102.07107v1

• [cs.RO]End-to-End Egospheric Spatial Memory
Daniel Lenton, Stephen James, Ronald Clark, Andrew J. Davison
http://arxiv.org/abs/2102.07764v1

• [cs.RO]FaSTrack: a Modular Framework for Real-Time Motion Planning and Guaranteed Safe Tracking
Mo Chen, Sylvia L. Herbert, Haimin Hu, Ye Pu, Jaime F. Fisac, Somil Bansal, SooJean Han, Claire J. Tomlin
http://arxiv.org/abs/2102.07039v1

• [cs.RO]FastHand: Fast Hand Pose Estimation From A Monocular Camera
Shan
382
An, Xiajie Zhang, Dong Wei, Haogang Zhu, Jianyu Yang, Konstantinos A. Tsintotas
http://arxiv.org/abs/2102.07067v1

• [cs.RO]Field Evaluations of A Deep Learning-based Intelligent Spraying Robot with Flow Control for Pear Orchards
Jaehwi Seol, Jeongeun Kim, Hyoung Il Son
http://arxiv.org/abs/2102.07313v1

• [cs.RO]Human-Robot Handshaking: A Review
Vignesh Prasad, Ruth Stock-Homburg, Jan Peters
http://arxiv.org/abs/2102.07193v1

• [cs.RO]Learning Variable Impedance Control via Inverse Reinforcement Learning for Force-Related Tasks
Xiang Zhang, Liting Sun, Zhian Kuang, Masayoshi Tomizuka
http://arxiv.org/abs/2102.06838v1

• [cs.RO]Learning from Demonstrations using Signal Temporal Logic
Aniruddh G. Puranic, Jyotirmoy V. Deshmukh, Stefanos Nikolaidis
http://arxiv.org/abs/2102.07730v1

• [cs.RO]Minimum Jerk Trajectory Generation for Straight and Curved Movements: Mathematical Analysis
Abdel-Nasser Sharkawy
http://arxiv.org/abs/2102.07459v1

• [cs.RO]Point-line-based RGB-D SLAM and Bundle Adjustment Uncertainty Analysis
Xin Ma, Xinwu Liang
http://arxiv.org/abs/2102.07110v1

• [cs.RO]Speculative Path Planning
Mohammad Bakhshalipour, Mohamad Qadri, Dominic Guri
http://arxiv.org/abs/2102.06261v2

• [cs.RO]Uncovering Interpretable Internal States of Merging Tasks at Highway On-Ramps for Autonomous Driving Decision-Making
Huanjie Wang, Wenshuo Wang, Shihua Yuan, Xueyuan Li
http://arxiv.org/abs/2102.07530v1

• [cs.RO]Unpacking Human Teachers’ Intentions For Natural Interactive Task Learning
Preeti Ramaraj, Charles L. Ortiz Jr, Matthew Klenk, Shiwali Mohan
http://arxiv.org/abs/2102.06755v1

• [cs.RO]Urban Metric Maps for Small Unmanned Aircraft Systems Motion Planning
Cosme A. Ochoa, Ella M. Atkins
http://arxiv.org/abs/2102.07218v1

• [cs.SD]Deep Convolutional and Recurrent Networks for Polyphonic Instrument Classification from Monophonic Raw Audio Waveforms
Kleanthis Avramidis, Agelos Kratimenos, Christos Garoufis, Athanasia Zlatintsi, Petros Maragos
http://arxiv.org/abs/2102.06930v1

• [cs.SD]Parametric Optimization of Violin Top Plates using Machine Learning
Davide Salvi, Sebastian Gonzalez, Fabio Antonacci, Augusto Sarti
http://arxiv.org/abs/2102.07133v1

• [cs.SD]Thank you for Attention: A survey on Attention-based Artificial Neural Networks for Automatic Speech Recognition
Priyabrata Karmakar, Shyh Wei Teng, Guojun Lu
http://arxiv.org/abs/2102.07259v1

• [cs.SE]Automatically Matching Bug Reports With Related App Reviews
Marlo Häring, Christoph Stanik, Walid Maalej
http://arxiv.org/abs/2102.07134v1

• [cs.SE]Machine Learning Model Development from a Software Engineering Perspective: A Systematic Literature Review
Giuliano Lorenzoni, 898
Paulo Alencar, Nathalia Nascimento, Donald Cowan
http://arxiv.org/abs/2102.07574v1

• [cs.SI]A Bayesian social platform for inclusive and evidence-based decision making
Susannah Kate Devitt, Tamara Rose Pearce, Alok Kumar Chowdhury, Kerrie Mengersen
http://arxiv.org/abs/2102.06893v1

• [cs.SI]A Bounded-Confidence Model of Opinion Dynamics on Hypergraphs
Abigail Hickok, Yacoub Kureh, Heather Z. Brooks, Michelle Feng, Mason A. Porter
http://arxiv.org/abs/2102.06825v1

• [cs.SI]Exploring the Public Reaction to COVID-19 News on Social Media in Portugal
Luciana Oliveira, Arminda Sequeira, Adriana Oliveira, Paulino Silva, Anabela Mesquita
http://arxiv.org/abs/2102.07689v1

• [cs.SI]Learning low-rank latent mesoscale structures in networks
Hanbaek Lyu, Yacoub H. Kureh, Joshua Vendrow, Mason A. Porter
http://arxiv.org/abs/2102.06984v1

• [cs.SI]Pulse of the Pandemic: Iterative Topic Filtering for Clinical Information Extraction from Social Media
Julia Wu, Venkatesh Sivaraman, Dheekshita Kumar, Juan M. Banda, David Sontag
http://arxiv.org/abs/2102.06836v1

• [cs.SI]Radflow: A Recurrent, Aggregated, and Decomposable Model for Networks of Time Series
Alasdair Tran, Alexander Mathews, Cheng Soon Ong, Lexing Xie
http://arxiv.org/abs/2102.07289v1

• [cs.SI]STruD: Truss Decomposition of Simplicial Complexes
Giulia Preti, Gianmarco De Francisci Morales, Francesco Bonchi
http://arxiv.org/abs/2102.07564v1

• [eess.AS]Adversarial defense for automatic speaker verification by cascaded self-supervised learning models
Haibin Wu, Xu Li, Andy T. Liu, Zhiyong Wu, Helen Meng, Hung-yi Lee
http://arxiv.org/abs/2102.07047v1

• [eess.AS]Bi-APC: Bidirectional Autoregressive Predictive Coding for Unsupervised Pre-training and Its Application to Children’s ASR
Ruchao Fan, Amber Afshan, Abeer Alwan
http://arxiv.org/abs/2102.06816v1

• [eess.AS]Hybrid phonetic-neural model for correction in speech recognition systems
Rafael Viana-Cámara, Mario Campos-Soberanis, Diego Campos-Sobrino
http://arxiv.org/abs/2102.06744v1

• [eess.IV]Attention-gated convolutional neural networks for off-resonance correction of spiral real-time MRI
Yongwan Lim, Shrikanth S. Narayanan, Krishna S. Nayak
http://arxiv.org/abs/2102.07271v1

• [eess.IV]Blind stain separation using model-aware generative learning and its applications on fluorescence microscopy images
Xingyu Li
http://arxiv.org/abs/2102.06802v1

• [eess.IV]Collaborative Intelligence: Challenges and Opportunities
Ivan V. Bajić, Weisi Lin, Yonghong Tian
http://arxiv.org/abs/2102.06841v1

• [eess.IV]Colored Kimia Path24 Dataset: Configurations and Benchmarks with Deep Embeddings
Sobhan Shafiei, Morteza Babaie, Shivam Kalra, H. R. Tizhoosh
http://arxiv.org/abs/2102.07611v1

• [eess.IV]Detection and severity classification of COVID-19 in CT images using deep learning
Yazan Qiblawey, Anas Tahir, Muhammad E. H. Chowdhury, Amith Khandakar, Serkan Kiranyaz, Tawsifur Rahman, Nabil Ibtehaz, Sakib Mahmud, Somaya Al-Madeed, Farayi Musharavati
http://arxiv.org/abs/2102.07726v1

• [eess.IV]Estimating Nonplanar Flow from 2D Motion-blurred Widefield Microscopy Images via Deep Learning
Adrian Shajkofci, Michael Liebling
http://arxiv.org/abs/2102.07228v1

• [eess.IV]Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images
Danial Sharifrazi, Roohallah Alizadehsani, Mohamad Roshanzamir, Javad Hassannataj Joloudari, Afshin Shoeibi, Mahboobeh Jafari, Sadiq Hussain, Zahra Alizadeh Sani, Fereshteh Hasanzadeh, Fahime Khozeimeh, Abbas Khosravi, Saeid Nahavandi, Maryam Panahiazar, Assef Zare, Sheikh Mohammed Shariful Islam, U Rajendra Acharya
http://arxiv.org/abs/2102.06883v1

• [eess.IV]How Convolutional Neural Networks Deal with Aliasing
Antônio H. Ribeiro, Thomas B. Schön
http://arxiv.org/abs/2102.07757v1

• [eess.IV]Multi-Texture GAN: Exploring the Multi-Scale Texture Translation f
8ef
or Brain MR Images
Xiaobin Hu
http://arxiv.org/abs/2102.07225v1

• [eess.IV]Scan-Specific MRI Reconstruction using Zero-Shot Physics-Guided Deep Learning
Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Mehmet Akçakaya
http://arxiv.org/abs/2102.07737v1

• [eess.SP]Federated Dropout Learning for Hybrid Beamforming With Spatial Path Index Modulation In Multi-User mmWave-MIMO Systems
Ahmet M. Elbir, Sinem Coleri, Kumar Vijay Mishra
http://arxiv.org/abs/2102.07450v1

• [eess.SP]Machine Learning on Camera Images for Fast mmWave Beamforming
Batool Salehi, Mauro Belgiovine, Sara Garcia Sanchez, Jennifer Dy, Stratis Ioannidis, Kaushik Chowdhury
http://arxiv.org/abs/2102.07337v1

• [eess.SY]A Decentralized Multi-UAV Spatio-Temporal Multi-Task Allocation Approach for Perimeter Defense
Shridhar Velhal, Suresh Sundaram, Narasimhan Sundararajan
http://arxiv.org/abs/2102.07381v1

• [eess.SY]High Order Control Lyapunov-Barrier Functions for Temporal Logic Specifications
Wei Xiao, Calin A. Belta, Christos G. Cassandras
http://arxiv.org/abs/2102.06787v1

• [math.FA]Strong Brascamp-Lieb Inequalities
Lei Yu
http://arxiv.org/abs/2102.06935v1

• [math.NA]Plug-and-Play external and internal priors for image restoration
Pasquale Cascarano, Elena Loli Piccolomini, Elena Morotti, Andrea Sebastiani
http://arxiv.org/abs/2102.07510v1

• [math.OC]A Momentum-Assis
8dc
ted Single-Timescale Stochastic Approximation Algorithm for Bilevel Optimization
Prashant Khanduri, Siliang Zeng, Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang
http://arxiv.org/abs/2102.07367v1

• [math.OC]A hybrid variance-reduced method for decentralized stochastic non-convex optimization
Ran Xin, Usman A. Khan, Soummya Kar
http://arxiv.org/abs/2102.06752v1

• [math.OC]Communication-Efficient Distributed Optimization with Quantized Preconditioners
Foivos Alimisis, Peter Davies, Dan Alistarh
http://arxiv.org/abs/2102.07214v1

• [math.OC]Decentralized Distributed Optimization for Saddle Point Problems
Alexander Rogozin, Pavel Dvurechensky, Darina Dvinkikh, Alexander Beznosikov, Dmitry Kovalev, Alexander Gasnikov
http://arxiv.org/abs/2102.07758v1

• [math.OC]Decentralized Riemannian Gradient Descent on the Stiefel Manifold
Shixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour
http://arxiv.org/abs/2102.07091v1

• [math.OC]Newton Method over Networks is Fast up to the Statistical Precision
Amir Daneshmand, Gesualdo Scutari, Pavel Dvurechensky, Alexander Gasnikov
http://arxiv.org/abs/2102.06780v1

• [math.OC]Relaxation of optimal transport problem via strictly convex functions
Asuka Takatsu
http://arxiv.org/abs/2102.07336v1

• [math.PR]Multivariate Max-Stable Processes and Homogeneous Functionals
Enkelejd Hashorva, Alfred Kume
http://arxiv.org/abs/2102.06736v1

• [math.ST]Bayes Factors for Peri-Null Hypotheses
Alexander Ly, Eric-Jan Wagenmakers
http://arxiv.org/abs/2102.07162v1

• [math.ST]Estimation for change point of discretely observed ergodic diffusion processes
Yozo Tonaki, Yusuke Kaino, Masayuki Uchida
http://arxiv.org/abs/2102.06871v1

• [math.ST]Fast Non-Asymptotic Testing And Support Recovery For Large Sparse Toeplitz Covariance Matrices
Nayel Bettache, Cristina Butucea, Marianne Sorba
http://arxiv.org/abs/2102.06817v1

• [math.ST]Gaussian distributions on Riemannian symmetric spaces in the large N limit
Simon Heuveline, Salem Said, Cyrus Mostajeran
http://arxiv.org/abs/2102.07556v1

• [math.ST]Improved Estimators for Semi-supervised High-dimensional Regression Model
Ilan Livne, David Azriel, Yair Goldberg
http://arxiv.org/abs/2102.07203v1

• [math.ST]One Hundred Probability and Statistics Inequalities
CNP Slagle
http://arxiv.org/abs/2102.07234v1

• [math.ST]Optimal designs for the development of personalized treatment rules
David Azriel, Yosef Rinott, Martin Posch
http://arxiv.org/abs/2102.07093v1

• [math.ST]Reconstructing measures on manifolds: an optimal transport approach
Vincent Divol
http://arxiv.org/abs/2102.07595v1

• [physics.bio-ph]Holographic Cell Stiffness Mapping Using Acoustic Stimulation
Rahmetullah Varol, Sevde Omeroglu, Zeynep Karavelioglu, Gizem Aydemir, Aslihan Karadag, Hanife Ecenur Meco, Gizem Calibasi Kocal, Muhammed Enes Oruc, Gokhan Bora Esmer, Yasemin Basbinar, Huseyin Uvet
http://arxiv.org/abs/2102.07480v1

• [physics.flu-dyn]Short- and long-term prediction of a chaotic flow: A physics-constrained reservoir computing approach
Nguyen Anh Khoa Doan, Wolfgang Polifke, Luca Magri
http://arxiv.org/abs/2102.07514v1

• [physics.geo-ph]“Shaking in 5 seconds!” A Voluntary Smartphone-based Earthquake Early Warning System
Rémy Bossu, Francesco Finazzi, Robert Steed, Laure Fallou, István Bondár
http://arxiv.org/abs/2102.06739v1

• [physics.soc-ph]Differences in the spatial landscape of urban mobility: gender and socioeconomic perspectives
Mariana Macedo, Laura Lotero, Alessio Cardillo, Ronaldo Menezes, Hugo Barbosa
http://arxiv.org/abs/2102.06619v1

• [q-bio.NC]Representing Alzheimer’s Disease Progression via Deep Prototype Tree
Lu Zhang, Li Wang, Dajiang Zhu
http://arxiv.org/abs/2102.06847v1

• [q-bio.PE]A stochastic SIR model for the analysis of the COVID-19 Italian epidemic
Sara Pasquali, Antonio Pievatolo, Antonella Bodini, Fabrizio Ruggeri
http://arxiv.org/abs/2102.07566v1

• [q-fin.ST]REST: Relational Event-driven Stock Trend Forecasting
Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu
http://arxiv.org/abs/2102.07372v1

• [quant-ph]Private learning implies quantum stability
Srinivasan Arunachalam, Yihui Quek, John Smolin
http://arxiv.org/abs/2102.07171v1

• [quant-ph]Refined Belief-Propagation Decoding of Quantum Codes with Scalar Messages
Kao-Yueh Kuo, Ching-Yi Lai
http://arxiv.org/abs/2102.07122v1

• [stat.AP]A Bayesian cohort component projection model to estimate adult populations at the subnational level in data-sparse settings
Monica Alexander, Leontine Alkema
http://arxiv.org/abs/2102.06121v2

• [stat.AP]Efficient Selection Between Hierarchical Cognitive Models: Cross-validation With Variational Bayes
Viet-Hung Dao, David Gunawan, Minh-Ngoc Tran, Robert Kohn, Guy E. Hawkins, Scott D. Brown
http://arxiv.org/abs/2102.06814v1

• [stat.AP]Model-Independent Detection of New Physics Signals Using Interpretable Semi-Supervised Classifier Tests
Purvasha Chakravarti, Mikael Kuusela, Jing Lei, Larry Wasserman
http://arxiv.org/abs/2102.07679v1

• [stat.ME]A modified closed-form maximum likelihood estimator
Pedro L. Ramos, Eduardo Ramos, Francisco A. Rodrigues, Francisco Louzada
http://arxiv.org/abs/2102.07356v1

• [stat.ME]Contrastive latent variable modeling with application to case-control sequencing experiments
Andrew Jones, F. William Townes, Didong Li, Barbara E. Engelhardt
http://arxiv.org/abs/2102.06731v1

• [stat.ME]Diagnostic tools for a multivariate negative binomial model for fitting correlated data with overdispersion
Lizandra Castilho Fabio, Cristian Villegas, Jalmar M. F. Carrasco, Mário de Castro
http://arxiv.org/abs/2102.07752v1

• [stat.ME]Goal-oriented adaptive sampling under random field modelling of response probability distributions
Athénaïs Gautier, David Ginsbourger, Guillaume Pirot
http://arxiv.org/abs/2102.07612v1

• [stat.ME]Horseshoe shrinkage methods for Bayesian fusion estimation
Sayantan Banerjee
http://arxiv.org/abs/2102.07378v1

• [stat.ME]Modeling Spatial Data with Cauchy Convolution Processes
Pavel Krupskii, Raphaël Huser
http://arxiv.org/abs/2102.07094v1

• [stat.ME]Nonintrusive Uncertainty Quantification for automotive crash problems with VPS/Pamcrash
Marc Rocas, Alberto García-González, Sergio Zlotnik, Xabier Larráyoz, Pedro Díez
http://arxiv.org/abs/2102.07673v1

• [stat.ME]Robust Model-Based Clustering
Juan D. Gonzalez, Ricardo Maronna, Victor J. Yohai, Ruben H. Zamar
http://arxiv.org/abs/2102.06851v1

• [stat.ME]Statistical Power for Estimating Treatment Effects Using Difference-in-Differences and Comparative Interrupted Time Series Designs with Variation in Treatment Timing
Peter Z. Schochet
http://arxiv.org/abs/2102.06770v1

• [stat.ME]Stochastic Convergence Rates and Applications of Adaptive Quadrature in Bayesian Inference
Blair Bilodeau, Alex Stringer, Yanbo Tang
http://arxiv.org/abs/2102.06801v1

• [stat.ME]The Importance of Being a Band: Finite-Sample Exact Distribution-Free Prediction Sets for Functional Data
Jacopo Diquigiovanni, Matteo Fontana, Simone Vantini
http://arxiv.org/abs/2102.06746v1

• [stat.ML]Achieving Efficiency in Black Box Simulation of Distribution Tails with Self-structuring Importance Samplers
Anand Deo, Karthyek Murthy
http://arxiv.org/abs/2102.07060v1

• [stat.ML]Annealed Flow Transport Monte Carlo
Michael Arbel, Alexander G. D. G. Matthews, Arnaud Doucet
http://arxiv.org/abs/2102.07501v1

• [stat.ML]Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections
Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris Holmes, Mert Gürbüzbalaban, Umut Şimşekli
http://arxiv.org/abs/2102.07006v1

• [stat.ML]Asymptotically Optimal Strategies For Combinatorial Semi-Bandits in Polynomial Time
Thibaut Cuvelier, Richard Combes, Eric Gourdin
http://arxiv.org/abs/2102.07254v1

• [stat.ML]Causal Markov Decision Processes: Learning Good Interventions Efficiently
Yangyi Lu, Amirhossein Meisami, Ambuj Tewari
http://arxiv.org/abs/2102.07663v1

• [stat.ML]Certifiably Robust Variational Autoencoders
Ben Barrett, Alexander Camuto, Matthew Willetts, Tom Rainforth
http://arxiv.org/abs/2102.07559v1

• [stat.ML]Clustering Left-Censored Multivariate Time-Series
Irene Y. Chen, Rahul G. Krishnan, David Sontag
http://arxiv.org/abs/2102.07005v1

• [stat.ML]Diffusion Approximations for a Class of Sequential Testing Problems
Victor F. Araman, Rene Caldentey
http://arxiv.org/abs/2102.07030v1

• [stat.ML]Double-descent curves in neural networks: a new perspective using Gaussian processes
Ouns El Harzli, Guillermo Valle-Pérez, Ard A. Louis
http://arxiv.org/abs/2102.07238v1

• [stat.ML]Efficient Designs of SLOPE Penalty Sequences in Finite Dimension
Yiliang Zhang, Zhiqi Bu
http://arxiv.org/abs/2102.07211v1

• [stat.ML]Fast and accurate optimization on the orthogonal manifold without retraction
Pierre Ablin, Gabriel Peyré
http://arxiv.org/abs/2102.07432v1

• [stat.ML]Healing Products of Gaussian Processes
Samuel Cohen, Rendani Mbuvha, Tshilidzi Marwala, Marc Peter Deisenroth
http://arxiv.org/abs/2102.07106v1

• [stat.ML]Learning from Similarity-Confidence Data
Yuzhou Cao, Lei Feng, Yitian Xu, Bo An, Gang Niu, Masashi Sugiyama
http://arxiv.org/abs/2102.06879v1

• [stat.ML]Manifold Density Estimation via Generalized Dequantization
James A. Brofos, Marcus A. Brubaker, Roy R. Lederman
http://arxiv.org/abs/2102.07143v1

• [stat.ML]On Riemannian Stochastic Approximation Schemes with Fixed Step-Size
Alain Durmus, Pablo Jiménez, Éric Moulines, Salem Said
http://arxiv.org/abs/2102.07586v1

• [stat.ML]Scalable nonparametric Bayesian learning for heterogeneous and dynamic velocity fields
Sunrit Chakraborty, Aritra Guha, Rayleigh Lei, XuanLong Nguyen
http://arxiv.org/abs/2102.07695v1

• [stat.ML]Sliced Multi-Marginal Optimal Transport
Samuel Cohen, K S Sesh Kumar, Marc Peter Deisenroth
http://arxiv.org/abs/2102.07115v1

• [stat.ML]Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces
Xingchen Wan, Vu Nguyen, Huong Ha, Binxin Ru, Cong Lu, Michael A. Osborne
http://arxiv.org/abs/2102.07188v1

• [stat.ML]Tractable structured natural gradient descent using local parameterizations
Wu Lin, Frank Nielsen, Mohammad Emtiyaz Khan, Mark Schmidt
http://arxiv.org/abs/2102.07405v1