astro-ph.IM - 仪器仪表和天体物理学方法

    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.DS - 数据结构与算法 cs.GR - 计算机图形学 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.LO - 计算逻辑 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 hep-th - 高能物理理论 math.CO - 组合数学 math.DS - 动力系统 math.MG -公制几何 math.NA - 数值分析 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.comp-ph - 计算物理学 physics.med-ph - 医学物理学 physics.plasm-ph - 等离子体物理 q-bio.NC - 神经元与认知 q-bio.QM - 定量方法 q-fin.ST - 统计金融学 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [astro-ph.IM]Active deep learning method for the discovery of objects of interest in large spectroscopic surveys
    • [cs.AI]A General Framework for Fairness in Multistakeholder Recommendations
    • [cs.AI]Active Learning of Causal Structures with Deep Reinforcement Learning
    • [cs.AI]Blockchain-based Federated Learning for Failure Detection in Industrial IoT
    • [cs.AI]Collaborative Management of Benchmark Instances and their Attributes
    • [cs.AI]Driving Tasks Transfer in Deep Reinforcement Learning for Decision-making of Autonomous Vehicles
    • [cs.AI]Online Disease Self-diagnosis with Inductive Heterogeneous Graph Convolutional Networks
    • [cs.AI]Predicting Requests in Large-Scale Online P2P Ridesharing
    • [cs.AI]sunny-as2: Enhancing SUNNY for Algorithm Selection
    • [cs.CL]Accenture at CheckThat! 2020: If you say so: Post-hoc fact-checking of claims using transformer-based models
    • [cs.CL]Automatic Dialect Adaptation in Finnish and its Effect on Perceived Creativity
    • [cs.CL]BANANA at WNUT-2020 Task 2: Identifying COVID-19 Information on Twitter by Combining Deep Learning and Transfer Learning Models
    • [cs.CL]Bio-inspired Structure Identification in Language Embeddings
    • [cs.CL]COVCOR20 at WNUT-2020 Task 2: An Attempt to Combine Deep Learning and Expert rules
    • [cs.CL]Duluth at SemEval-2020 Task 7: Using Surprise as a Key to Unlock Humorous Headlines
    • [cs.CL]E-BERT: A Phrase and Product Knowledge Enhanced Language Model for E-commerce
    • [cs.CL]MIDAS at SemEval-2020 Task 10: Emphasis Selection using Label Distribution Learning and Contextual Embeddings
    • [cs.CL]Once Upon A Time In Visualization: Understanding the Use of Textual Narratives for Causality
    • [cs.CL]QiaoNing at SemEval-2020 Task 4: Commonsense Validation and Explanation system based on ensemble of language model
    • [cs.CL]Recent Trends in the Use of Deep Learning Models for Grammar Error Handling
    • [cs.CL]Robust Spoken Language Understanding with RL-based Value Error Recovery
    • [cs.CL]Romanian Diacritics Restoration Using Recurrent Neural Networks
    • [cs.CL]SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles
    • [cs.CL]Team Alex at CLEF CheckThat! 2020: Identifying Check-Worthy Tweets With Transformer Models
    • [cs.CL]TorchKGE: Knowledge Graph Embedding in Python and PyTorch
    • [cs.CL]TransModality: An End2End Fusion Method with Transformer for Multimodal Sentiment Analysis
    • [cs.CL]UIT-HSE at WNUT-2020 Task 2: Exploiting CT-BERT for Identifying COVID-19 Information on the Twitter Social Network
    • [cs.CL]UPB at SemEval-2020 Task 8: Joint Textual and Visual Modeling in a Multi-Task Learning Architecture for Memotion Analysis
    • [cs.CL]UPB at SemEval-2020 Task 9: Identifying Sentiment in Code-Mixed Social Media Texts using Transformers and Multi-Task Learning
    • [cs.CL]Uncovering the Corona Virus Map Using Deep Entities and Relationship Models
    • [cs.CL]Why Not Simply Translate? A First Swedish Evaluation Benchmark for Semantic Similarity
    • [cs.CR]Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data Hiding
    • [cs.CR]Attribute-Based Access Control for Smart Cities: A Smart Contract-Driven Framework
    • [cs.CV]3D Room Layout Estimation Beyond the Manhattan World Assumption
    • [cs.CV]A Deep Learning Approach to Tongue Detection for Pediatric Population
    • [cs.CV]A Genetic Feature Selection Based Two-stream Neural Network for Anger Veracity Recognition
    • [cs.CV]A Light-Weight Object Detection Framework with FPA Module for Optical Remote Sensing Imagery
    • [cs.CV]A Review on Near Duplicate Detection of Images using Computer Vision Techniques
    • [cs.CV]A novel action recognition system for smart monitoring of elderly people using Action Pattern Image and Series CNN with transfer learning
    • [cs.CV]ACDC: Weight Sharing in Atom-Coefficient Decomposed Convolution
    • [cs.CV]An Efficient Technique for Image Captioning using Deep Neural Network
    • [cs.CV]Approaches, Challenges, and Applications for Deep Visual Odometry: Toward to Complicated and Emerging Areas
    • [cs.CV]Are Deep Neural Architectures Losing Information? Invertibility Is Indispensable
    • [cs.CV]Benchmarking off-the-shelf statistical shape modeling tools in clinical applications
    • [cs.CV]Channel-wise Alignment for Adaptive Object Detection
    • [cs.CV]Class Interference Regularization
    • [cs.CV]DV-ConvNet: Fully Convolutional Deep Learning on Point Clouds with Dynamic Voxelization and 3D Group Convolution
    • [cs.CV]DeePSD: Automatic Deep Skinning And Pose Space Deformation For 3D Garment Animation
    • [cs.CV]Deep Longitudinal Modeling of Infant Cortical Surfaces
    • [cs.CV]Deep Sparse Light Field Refocusing
    • [cs.CV]Deepfake detection: humans vs. machines
    • [cs.CV]Don’t miss the Mismatch: Investigating the Objective Function Mismatch for Unsupervised Representation Learning
    • [cs.CV]Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks
    • [cs.CV]Efficient Pedestrian Detection in Top-View Fisheye Images Using Compositions of Perspective View Patches
    • [cs.CV]End-to-End Deep Learning Model for Cardiac Cycle Synchronization from Multi-View Angiographic Sequences
    • [cs.CV]Explanation of Unintended Radiated Emission Classification via LIME
    • [cs.CV]Frontier Detection and Reachability Analysis for Efficient 2D Graph-SLAM Based Active Exploration
    • [cs.CV]GazeMAE: General Representations of Eye Movements using a Micro-Macro Autoencoder
    • [cs.CV]Generalization on the Enhancement of Layerwise Relevance Interpretability of Deep Neural Network
    • [cs.CV]Improved Modeling of 3D Shapes with Multi-view Depth Maps
    • [cs.CV]Improving colonoscopy lesion classification using semi-supervised deep learning
    • [cs.CV]Integrating Egocentric Localization for More Realistic Point-Goal Navigation Agents
    • [cs.CV]Interpretable Deep Multimodal Image Super-Resolution
    • [cs.CV]Learning from Multiple Datasets with Heterogeneous and Partial Labels for Universal Lesion Detection in CT
    • [cs.CV]Light Field View Synthesis via Aperture Flow and Propagation Confidence Map
    • [cs.CV]MFL_COVID19: Quantifying Country-based Factors affecting Case Fatality Rate in Early Phase of COVID-19 Epidemic via Regularised Multi-task Feature Learning
    • [cs.CV]Multimodal Memorability: Modeling Effects of Semantics and Decay on Video Memorability
    • [cs.CV]Player Identification in Hockey Broadcast Videos
    • [cs.CV]Progressive Bilateral-Context Driven Model for Post-Processing Person Re-Identification
    • [cs.CV]Quantifying Explainability of Saliency Methods in Deep Neural Networks
    • [cs.CV]Real-Time Segmentation of Non-Rigid Surgical Tools based on Deep Learning and Tracking
    • [cs.CV]Reverse-engineering Bar Charts Using Neural Networks
    • [cs.CV]Stem-leaf segmentation and phenotypic trait extraction of maize shoots from three-dimensional point cloud
    • [cs.CV]Stochastic-YOLO: Efficient Probabilistic Object Detection under Dataset Shifts
    • [cs.CV]TRANSPR: Transparency Ray-Accumulating Neural 3D Scene Point Renderer
    • [cs.CV]Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges
    • [cs.CV]Uncertainty Inspired RGB-D Saliency Detection
    • [cs.CV]Unsupervised Wasserstein Distance Guided Domain Adaptation for 3D Multi-Domain Liver Segmentation
    • [cs.CV]User-Guided Domain Adaptation for Rapid Annotation from User Interactions: A Study on Pathological Liver Segmentation
    • [cs.CV]User-assisted Video Reflection Removal
    • [cs.CV]Video Moment Retrieval via Natural Language Queries
    • [cs.CV]Visual Object Tracking by Segmentation with Graph Convolutional Network
    • [cs.CV]Visual Sentiment Analysis from Disaster Images in Social Media
    • [cs.CY]Critical Business Decision Making for Technology Startups — A PerceptIn Case Study
    • [cs.CY]Detecting Informal Organization Through Data Mining Techniques
    • [cs.CY]Hawkes-modeled telecommunication patterns reveal relationship dynamics and personality traits
    • [cs.CY]IVACS: Intelligent Voice Assistant for Coronavirus Disease (COVID-19) Self-Assessment
    • [cs.CY]Improving Maritime Traffic Emission Estimations on Missing Data with CRBMs
    • [cs.CY]Intelligent Luminaire based Real-time Indoor Positioning for Assisted Living
    • [cs.CY]Measuring Massive Multitask Language Understanding
    • [cs.CY]Motivated Reasoning and Blame: Responses to Performance Framing and Outgroup Triggers during COVID-19
    • [cs.CY]Report on the 2019 Workshop on Smart Farming and Data Analytics (SFDAI)
    • [cs.CY]Respect for Human Autonomy in Recommender Systems
    • [cs.CY]SilkViser:A Visual Explorer of Blockchain-based Cryptocurrency Transaction Data
    • [cs.CY]Technological Platform for the Prevention and Management of Healthcare Associated Infections and Outbreaks
    • [cs.CY]Text Mining over Curriculum Vitae of Peruvian Professionals using Official Scientific Site DINA
    • [cs.CY]Towards an Interoperable Data Protocol Aimed at Linking the Fashion Industry with AI Companies
    • [cs.DC]”Reduction of Monetary Cost in Cloud Storage System by Using Extended Strict Timed Causal Consistency”
    • [cs.DC]An SMDP-Based Approach to Thermal-Aware Task Scheduling in NoC-based MPSoC platforms
    • [cs.DC]Asynchronous Runtime with Distributed Manager for Task-based Programming Models
    • [cs.DC]Design and Evaluation of a Simple Data Interface for Efficient Data Transfer Across Diverse Storage
    • [cs.DC]Hierarchical Roofline Analysis: How to Collect Data using Performance Tools on Intel CPUs and NVIDIA GPUs
    • [cs.DC]Infrastructure de Services Cloud FaaS sur noeuds IoT
    • [cs.DC]Running Neural Networks on the NIC
    • [cs.DS]Multi-Way Number Partitioning: an Information-Theoretic View
    • [cs.GR]Interactive Visualization of Terascale Data in the Browser: Fact or Fiction?
    • [cs.GT]PAC Reinforcement Learning Algorithm for General-Sum Markov Games
    • [cs.HC]Visually Analyzing Contextualized Embeddings
    • [cs.IR]”And the Winner Is…”: Dynamic Lotteries for Multi-group Fairness-Aware Recommendation
    • [cs.IR]An Improved Algorithm for Fast K-Word Proximity Search Based on Multi-Component Key Indexes
    • [cs.IR]CAVA: A Visual Analytics System for Exploratory Columnar Data Augmentation Using Knowledge Graphs
    • [cs.IR]Contextual Personalized Re-Ranking of Music Recommendations through Audio Features
    • [cs.IR]Detecting User Community in Sparse Domain via Cross-Graph Pairwise Learning
    • [cs.IR]Efficient Personalized Community Detection via Genetic Evolution
    • [cs.IR]Personalized Review Ranking for Improving Shopper’s Decision Making: A Term Frequency based Approach
    • [cs.IR]Vapur: A Search Engine to Find Related Protein — Compound Pairs in COVID-19 Literature
    • [cs.IT]A Class of Optimal Structures for Node Computations in Message Passing Algorithms
    • [cs.IT]Alternating Beamforming with Intelligent Reflecting Surface Element Allocation
    • [cs.IT]Analysis of Uplink IRS-Assisted NOMA under Nakagami-m Fading via Moments Matching
    • [cs.IT]Centralized & Distributed Deep Reinforcement Learning Methods for Downlink Sum-Rate Optimization
    • [cs.IT]Deep Ensemble of Weighted Viterbi Decoders for Tail-Biting Convolutional Codes
    • [cs.IT]End-to-End Mutual-Coupling-Aware Communication Model for Reconfigurable Intelligent Surfaces: An Electromagnetic-Compliant Approach Based on Mutual Impedances
    • [cs.IT]Extended quasi-cyclic constructions of quantum codes and entanglement-assisted quantum codes
    • [cs.IT]Finite-Alphabet MMSE Equalization for All-Digital Massive MU-MIMO mmWave Communication
    • [cs.IT]Improved Error Performance in NOMA-based Diamond Relaying
    • [cs.IT]Multiple Private Key Generation for Continuous Memoryless Sources with A Helper
    • [cs.IT]New Upper Bounds in the Hypothesis Testing Problem with Information Constraints
    • [cs.IT]Optimal Deterministic Group Testing Algorithms to Estimate the Number of Defectives
    • [cs.IT]Optimal Scheduling Policy for Minimizing Age of Information with a Relay
    • [cs.IT]Performance Analysis and User Association Optimization for Wireless Network Aided by Multiple Intelligent Reflecting Surfaces
    • [cs.IT]Reconfigurable Intelligent Surfaces for Localization: Position and Orientation Error Bounds
    • [cs.IT]Soft-Output Finite Alphabet Equalization for mmWAVE Massive MIMO
    • [cs.IT]User Selection Approaches to Mitigate the Straggler Effect for Federated Learning on Cell-Free Massive MIMO Networks
    • [cs.IT]Weighted Information Filtering, Smoothing, and Out-of-Sequence Measurement Processing
    • [cs.LG]A Change-Detection Based Thompson Sampling Framework for Non-Stationary Bandits
    • [cs.LG]A Framework for Private Matrix Analysis
    • [cs.LG]A Generative Adversarial Approach To ECG Synthesis And Denoising
    • [cs.LG]A Hybrid PAC Reinforcement Learning Algorithm
    • [cs.LG]A Neural Network Perturbation Theory Based on the Born Series
    • [cs.LG]A Simple and General Graph Neural Network with Stochastic Message Passing
    • [cs.LG]A perturbation based out-of-sample extension framework
    • [cs.LG]An Analysis of Alternating Direction Method of Multipliers for Feed-forward Neural Networks
    • [cs.LG]An FPGA Accelerated Method for Training Feed-forward Neural Networks Using Alternating Direction Method of Multipliers and LSMR
    • [cs.LG]Anomaly Detection With Partitioning Overfitting Autoencoder Ensembles
    • [cs.LG]Automatic detection of microsleep episodes with deep learning
    • [cs.LG]Black Box to White Box: Discover Model Characteristics Based on Strategic Probing
    • [cs.LG]Bluff: Interactively Deciphering Adversarial Attacks on Deep Neural Networks
    • [cs.LG]Computational Models for Academic Performance Estimation
    • [cs.LG]Crowding Prediction of In-Situ Metro Passengers Using Smart Card Data
    • [cs.LG]Detection Defense Against Adversarial Attacks with Saliency Map
    • [cs.LG]Discovering Reliable Causal Rules
    • [cs.LG]Dynamically Computing Adversarial Perturbations for Recurrent Neural Networks
    • [cs.LG]ECOC as a Method of Constructing Deep Convolutional Neural Network Ensembles
    • [cs.LG]Efficient Projection Algorithms onto the Weighted l1 Ball
    • [cs.LG]FLFE: A Communication-Efficient and Privacy-Preserving Federated Feature Engineering Framework
    • [cs.LG]Fast and Secure Distributed Nonnegative Matrix Factorization
    • [cs.LG]FlipOut: Uncovering Redundant Weights via Sign Flipping
    • [cs.LG]GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training
    • [cs.LG]HLSGD Hierarchical Local SGD With Stale Gradients Featuring
    • [cs.LG]Hybrid Differentially Private Federated Learning on Vertically Partitioned Data
    • [cs.LG]Implicit Multidimensional Projection of Local Subspaces
    • [cs.LG]Information Theoretic Counterfactual Learning from Missing-Not-At-Random Feedback
    • [cs.LG]Information Theoretic Meta Learning with Gaussian Processes
    • [cs.LG]Iterative Correction of Sensor Degradation and a Bayesian Multi-Sensor Data Fusion Method
    • [cs.LG]LFGCN: Levitating over Graphs with Levy Flights
    • [cs.LG]Learning Inter- and Intra-manifolds for Matrix Factorization-based Multi-Aspect Data Clustering
    • [cs.LG]Learning Unbiased Representations via Rényi Minimization
    • [cs.LG]Learning from Very Few Samples: A Survey
    • [cs.LG]Learning to Rank under Multinomial Logit Choice
    • [cs.LG]Optimizing Mode Connectivity via Neuron Alignment
    • [cs.LG]Ordinal-Content VAE: Isolating Ordinal-Valued Content Factors in Deep Latent Variable Models
    • [cs.LG]Particle Swarm Optimized Federated Learning For Industrial IoT and Smart City Services
    • [cs.LG]Profiling US Restaurants from Billions of Payment Card Transactions
    • [cs.LG]PySAD: A Streaming Anomaly Detection Framework in Python
    • [cs.LG]Real-time and Large-scale Fleet Allocation of Autonomous Taxis: A Case Study in New York Manhattan Island
    • [cs.LG]Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices
    • [cs.LG]S-SGD: Symmetrical Stochastic Gradient Descent with Weight Noise Injection for Reaching Flat Minima
    • [cs.LG]Scaling up Differentially Private Deep Learning with Fast Per-Example Gradient Clipping
    • [cs.LG]Sparse Network Inversion for Key Instance Detection in Multiple Instance Learning
    • [cs.LG]Stabilizing Invertible Neural Networks Using Mixture Models
    • [cs.LG]System Identification Through Lipschitz Regularized Deep Neural Networks
    • [cs.LG]Towards Probabilistic Tensor Canonical Polyadic Decomposition 2.0: Automatic Tensor Rank Learning Using Generalized Hyperbolic Prior
    • [cs.LG]Unifying Clustered and Non-stationary Bandits
    • [cs.LG]Using Machine Teaching to Investigate Human Assumptions when Teaching Reinforcement Learners
    • [cs.LG]Why Spectral Normalization Stabilizes GANs: Analysis and Improvements
    • [cs.LO]Ambiguity Hierarchy of Regular Infinite Tree Languages
    • [cs.NI]Blockchain-based Privacy Preservation for 5G-enabled Drone Communications
    • [cs.NI]Examining Machine Learning for 5G and Beyond through an Adversarial Lens
    • [cs.NI]Summarization in Semantic Based Service Discovery in Dynamic IoT-Edge Networks
    • [cs.NI]Unleashing In-network Computing on Scientific Workloads
    • [cs.RO]A Hierarchical Architecture for Human-Robot Cooperation Processes
    • [cs.RO]A Robust Laser-Inertial Odometry and Mapping Method for Large-Scale Highway Environments
    • [cs.RO]Animated Cassie: A Dynamic Relatable Robotic Character
    • [cs.RO]BP-RRT: Barrier Pair Synthesis for Temporal Logic Motion Planning
    • [cs.RO]Learning Topological Motion Primitives for Knot Planning
    • [cs.RO]Receding Horizon Task and Motion Planning in Dynamic Environments
    • [cs.SE]Efficient Framework for Learning Code Representations through Semantic-Preserving Program Transformations
    • [cs.SE]Improving Problem Identification via Automated Log Clustering using Dimensionality Reduction
    • [cs.SE]The Integrity of Machine Learning Algorithms against Software Defect Prediction
    • [cs.SE]distr6: R6 Object-Oriented Probability Distributions Interface in R
    • [cs.SI]Analysing Twitter Semantic Networks: the case of 2018 Italian Elections
    • [cs.SI]Friend Network as Gatekeeper: A Study of WeChat Users’ Consumption of Friend-Curated Contents
    • [cs.SI]HAP-SAP: Semantic Annotation in LBSNs using Latent Spatio-Temporal Hawkes Process
    • [cs.SI]Preserving Minority Structures in Graph Sampling
    • [cs.SI]Utilizing Citation Network Structure to Predict Citation Counts: A Deep Learning Approach
    • [econ.EM]Doubly Robust Semiparametric Difference-in-Differences Estimators with High-Dimensional Data
    • [eess.AS]Any-to-Many Voice Conversion with Location-Relative Sequence-to-Sequence Modeling
    • [eess.AS]Cross-domain Adaptation with Discrepancy Minimization for Text-independent Forensic Speaker Verification
    • [eess.AS]KoSpeech: Open-Source Toolkit for End-to-End Korean Speech Recognition
    • [eess.AS]Libri-Adapt: A New Speech Dataset for Unsupervised Domain Adaptation
    • [eess.IV]Brain Tumor Survival Prediction using Radiomics Features
    • [eess.IV]Deep Learning for Automatic Spleen Length Measurement in Sickle Cell Disease Patients
    • [eess.IV]Edge-variational Graph Convolutional Networks for Uncertainty-aware Disease Prediction
    • [eess.IV]Max-Fusion U-Net for Multi-Modal Pathology Segmentation with Attention and Dynamic Resampling
    • [eess.IV]Perfusion Imaging: A Data Assimilation Approach
    • [eess.IV]Semi-supervised Pathology Segmentation with Disentangled Representations
    • [eess.IV]The 2ST-UNet for Pneumothorax Segmentation in Chest X-Rays using ResNet34 as a Backbone for U-Net
    • [eess.IV]Towards learned optimal q-space sampling in diffusion MRI
    • [eess.SP]A Survey of Deep Learning Architectures for Intelligent Reflecting Surfaces
    • [eess.SP]Adaptive and Fast Combined Waveform-Beamforming Design for mmWave Automotive Joint Communication-Radar
    • [eess.SP]Antenna Selection for Improving Energy Efficiency in XL-MIMO Systems
    • [eess.SP]CSI-Based Multi-Antenna and Multi-Point Indoor Positioning Using Probability Fusion
    • [eess.SP]Data-Driven Transferred Energy Management Strategy for Hybrid Electric Vehicles via Deep Reinforcement Learning
    • [eess.SP]Edge Learning with Unmanned Ground Vehicle: Joint Path, Energy and Sample Size Planning
    • [eess.SP]Simultaneous Energy Harvesting and Gait Recognition using Piezoelectric Energy Harvester
    • [eess.SY]Preserving Privacy of the Influence Structure in Friedkin-Johnsen Systems
    • [hep-th]Machine Learning Calabi-Yau Four-folds
    • [math.CO]Information Hiding Using Matroid Theory
    • [math.DS]OnsagerNet: Learning Stable and Interpretable Dynamics using a Generalized Onsager Principle
    • [math.MG]Area-Invariant Pedal-Like Curves Derived from the Ellipse
    • [math.NA]Higher-order Quasi-Monte Carlo Training of Deep Neural Networks
    • [math.NA]The Seven-League Scheme: Deep learning for large time step Monte Carlo simulations of stochastic differential equations
    • [math.OC]Convergence Analysis of the Hessian Estimation Evolution Strategy
    • [math.OC]Distributed Optimization, Averaging via ADMM, and Network Topology
    • [math.OC]Escaping Saddle Points in Ill-Conditioned Matrix Completion with a Scalable Second Order Method
    • [math.OC]Nearly Bounded Regret of Re-solving Heuristics in Price-based Revenue Management
    • [math.PR]An online learning approach to dynamic pricing and capacity sizing in service systems
    • [math.PR]Matched Queues with Matching Batch Pair (m, n)
    • [math.PR]New Upper Bounds for Trace Reconstruction
    • [math.PR]On estimation of quadratic variation for multivariate pure jump semimartingales
    • [math.PR]Positivity of Cumulative Sums for Multi-Index Function Components Explains the Lower Bound Formula in the Levin-Robbins-Leu Family of Sequential Subset Selection Procedures
    • [math.ST]Admissible anytime-valid sequential inference must rely on nonnegative martingales
    • [math.ST]False discovery rate control with e-values
    • [math.ST]Isotonic regression with unknown permutations: Statistics, computation, and adaptation
    • [math.ST]Permutation Testing for Dependence in Time Series
    • [physics.comp-ph]The role of feature space in atomistic learning
    • [physics.med-ph]Localization and classification of intracranialhemorrhages in CT data
    • [physics.plasm-ph]Deep Learning for the Analysis of Disruption Precursors based on Plasma Tomography
    • [q-bio.NC]CalciumGAN: A Generative Adversarial Network Model for Synthesising Realistic Calcium Imaging Data of Neuronal Populations
    • [q-bio.NC]The Resolution Matrix for Visualizing Functional Network Connectivity
    • [q-bio.QM]Bayesian information-theoretic calibration of patient-specific radiotherapy sensitivity parameters for informing effective scanning protocols in cancer
    • [q-fin.ST]Capturing dynamics of post-earnings-announcement drift using genetic algorithm-optimised supervised learning
    • [stat.AP]An industry case of large-scale demand forecasting of hierarchical components
    • [stat.AP]Bayesian shared-parameter models for analysing sardine fishing in the Mediterranean Sea
    • [stat.AP]Evaluating the relative contribution of data sources in a Bayesian analysis with the application of estimating the size of hard to reach populations
    • [stat.AP]Identifying partners at sea on contrasting fisheries around the world
    • [stat.AP]Matching Bounds: How Choice of Matching AlgorithmImpacts Treatment Effects Estimates and What to Do about It
    • [stat.AP]Optimization of High-dimensional Simulation Models Using Synthetic Data
    • [stat.AP]SARGDV: Efficient identification of groundwater-dependent vegetation using synthetic aperture radar
    • [stat.AP]Structured Sparsity Modeling for Improved Multivariate Statistical Analysis based Fault Isolation
    • [stat.AP]Suicide Risk Modeling with Uncertain Diagnostic Records
    • [stat.AP]Using multiple data streams to estimate and forecast SARS-CoV-2 transmission dynamics, with application to the virus spread in Orange County, California
    • [stat.ME]Anomaly Detection in Stationary Settings: A Permutation-Based Higher Criticism Approach
    • [stat.ME]Bootstrap p-values reduce type 1 error of the robust rank-order test of difference in medians
    • [stat.ME]Empirical Bayes methods for monitoring health care quality
    • [stat.ME]Fairness in Risk Assessment Instruments: Post-Processing to Achieve Counterfactual Equalized Odds
    • [stat.ME]Penalized Maximum Likelihood Estimator for Mixture of von Mises-Fisher Distributions
    • [stat.ME]Simulating Name-like Vectors for Testing Large-scale Entity Resolution
    • [stat.ML]Binary Classification as a Phase Separation Process
    • [stat.ML]Communication-efficient distributed eigenspace estimation
    • [stat.ML]Estimation of Structural Causal Model via Sparsely Mixing Independent Component Analysis
    • [stat.ML]Gradient-based Competitive Learning: Theory
    • [stat.ML]Multilinear Common Component Analysis via Kronecker Product Representation
    • [stat.ML]Non-exponentially weighted aggregation: regret bounds for unbounded loss functions
    • [stat.ML]Screening Rules and its Complexity for Active Set Identification
    • [stat.ML]Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces
    • [stat.ML]Unfolding by Folding: a resampling approach to the problem of matrix inversion without actually inverting any matrix

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    • [astro-ph.IM]Active deep learning method for the discovery of objects of interest in large spectroscopic surveys
    Petr Škoda, Ondřej Podsztavek, Pavel Tvrdík
    http://arxiv.org/abs/2009.03219v1

    • [cs.AI]A General Framework for Fairness in Multistakeholder Recommendations
    Harshal A. Chaudhari, Sangdi Lin, Ondrej Linda
    http://arxiv.org/abs/2009.02423v1

    • [cs.AI]Active Learning of Causal Structures with Deep Reinforcement Learning
    Amir Amirinezhad, Saber Salehkaleybar, Matin Hashemi
    http://arxiv.org/abs/2009.03009v1

    • [cs.AI]Blockchain-based Federated Learning for Failure Detection in Industrial IoT
    Weishan Zhang, Qinghua Lu, Qiuyu Yu, Zhaotong Li, Yue Liu, Sin Kit Lo, Shiping Chen, Xiwei Xu, Liming Zhu
    http://arxiv.org/abs/2009.02643v1

    • [cs.AI]Collaborative Management of Benchmark Instances and their Attributes
    Markus Iser, Luca Springer, Carsten Sinz
    http://arxiv.org/abs/2009.02995v1

    • [cs.AI]Driving Tasks Transfer in Deep Reinforcement Learning for Decision-making of Autonomous Vehicles
    Teng Liu, Xingyu Mu, Bing Huang, Yi Xie, Dongpu Cao
    http://arxiv.org/abs/2009.03268v1

    • [cs.AI]Online Disease Self-diagnosis with Inductive Heterogeneous Graph Convolutional Networks
    Zifeng Wang, Rui Wen, Xi Chen, Shilei Cao, Shao-Lun Huang, Buyue Qian, Yefeng Zheng
    http://arxiv.org/abs/2009.02625v1

    • [cs.AI]Predicting Requests in Large-Scale Online P2P Ridesharing
    Filippo Bistaffa, Juan A. Rodríguez-Aguilar, Jesús Cerquides
    http://arxiv.org/abs/2009.02997v1

    • [cs.AI]sunny-as2: Enhancing SUNNY for Algorithm Selection
    Tong Liu, Roberto Amadini, Jacopo Mauro, Maurizio Gabbrielli
    http://arxiv.org/abs/2009.03107v1

    • [cs.CL]Accenture at CheckThat! 2020: If you say so: Post-hoc fact-checking of claims using transformer-based models
    Evan Williams, Paul Rodrigues, Valerie Novak
    http://arxiv.org/abs/2009.02431v1

    • [cs.CL]Automatic Dialect Adaptation in Finnish and its Effect on Perceived Creativity
    Mika Hämäläinen, Niko Partanen, Khalid Alnajjar, Jack Rueter, Thierry Poibeau
    http://arxiv.org/abs/2009.02685v1

    • [cs.CL]BANANA at WNUT-2020 Task 2: Identifying COVID-19 Information on Twitter by Combining Deep Learning and Transfer Learning Models
    Tin Van Huynh, Luan Thanh Nguyen, Son T. Luu
    http://arxiv.org/abs/2009.02671v1

    • [cs.CL]Bio-inspired Structure Identification in Language Embeddings
    Hongwei, Zhou, Oskar Elek, Pranav Anand, Angus G. Forbes
    http://arxiv.org/abs/2009.02459v1

    • [cs.CL]COVCOR20 at WNUT-2020 Task 2: An Attempt to Combine Deep Learning and Expert rules
    Ali Hürriyetoğlu, Ali Safaya, Nelleke Oostdijk, Osman Mutlu, Erdem Yörük
    http://arxiv.org/abs/2009.03191v1

    • [cs.CL]Duluth at SemEval-2020 Task 7: Using Surprise as a Key to Unlock Humorous Headlines
    Shuning Jin, Yue Yin, XianE Tang, Ted Pedersen
    http://arxiv.org/abs/2009.02795v1

    • [cs.CL]E-BERT: A Phrase and Product Knowledge Enhanced Language Model for E-commerce
    Denghui Zhang, Zixuan Yuan, Yanchi Liu, Fuzhen Zhuang, Hui Xiong
    http://arxiv.org/abs/2009.02835v1

    • [cs.CL]MIDAS at SemEval-2020 Task 10: Emphasis Selection using Label Distribution Learning and Contextual Embeddings
    Sarthak Anand, Pradyumna Gupta, Hemant Yadav, Debanjan Mahata, Rakesh Gosangi, Haimin Zhang, Rajiv Ratn Shah
    http://arxiv.org/abs/2009.02619v1

    • [cs.CL]Once Upon A Time In Visualization: Understanding the Use of Textual Narratives for Causality
    Arjun Choudhry, Mandar Sharma, Pramod Chundury, Thomas Kapler, Derek W. S. Gray, Naren Ramakrishnan, Niklas Elmqvist
    http://arxiv.org/abs/2009.02649v1

    • [cs.CL]QiaoNing at SemEval-2020 Task 4: Commonsense Validation and Explanation system based on ensemble of language model
    Pai Liu
    http://arxiv.org/abs/2009.02645v1

    • [cs.CL]Recent Trends in the Use of Deep Learning Models for Grammar Error Handling
    Mina Naghshnejad, Tarun Joshi, Vijayan N. Nair
    http://arxiv.org/abs/2009.02358v1

    • [cs.CL]Robust Spoken Language Understanding with RL-based Value Error Recovery
    Chen Liu, Su Zhu, Lu Chen, Kai Yu
    http://arxiv.org/abs/2009.03095v1

    • [cs.CL]Romanian Diacritics Restoration Using Recurrent Neural Networks
    Stefan Ruseti, Teodor-Mihai Cotet, Mihai Dascalu
    http://arxiv.org/abs/2009.02743v1

    • [cs.CL]SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles
    G. Da San Martino, A. Barrón-Cedeño, H. Wachsmuth, R. Petrov, P. Nakov
    http://arxiv.org/abs/2009.02696v1

    • [cs.CL]Team Alex at CLEF CheckThat! 2020: Identifying Check-Worthy Tweets With Transformer Models
    Alex Nikolov, Giovanni Da San Martino, Ivan Koychev, Preslav Nakov
    http://arxiv.org/abs/2009.02931v1

    • [cs.CL]TorchKGE: Knowledge Graph Embedding in Python and PyTorch
    Armand Boschin
    http://arxiv.org/abs/2009.02963v1

    • [cs.CL]TransModality: An End2End Fusion Method with Transformer for Multimodal Sentiment Analysis
    Zilong Wang, Zhaohong Wan, Xiaojun Wan
    http://arxiv.org/abs/2009.02902v1

    • [cs.CL]UIT-HSE at WNUT-2020 Task 2: Exploiting CT-BERT for Identifying COVID-19 Information on the Twitter Social Network
    Khiem Vinh Tran, Hao Phu Phan, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen
    http://arxiv.org/abs/2009.02935v1

    • [cs.CL]UPB at SemEval-2020 Task 8: Joint Textual and Visual Modeling in a Multi-Task Learning Architecture for Memotion Analysis
    George-Alexandru Vlad, George-Eduard Zaharia, Dumitru-Clementin Cercel, Costin-Gabriel Chiru, Stefan Trausan-Matu
    http://arxiv.org/abs/2009.02779v1

    • [cs.CL]UPB at SemEval-2020 Task 9: Identifying Sentiment in Code-Mixed Social Media Texts using Transformers and Multi-Task Learning
    George-Eduard Zaharia, George-Alexandru Vlad, Dumitru-Clementin Cercel, Traian Rebedea, Costin-Gabriel Chiru
    http://arxiv.org/abs/2009.02780v1

    • [cs.CL]Uncovering the Corona Virus Map Using Deep Entities and Relationship Models
    Kuldeep Singh, Puneet Singla, Ketan Sarode, Anurag Chandrakar, Chetan Nichkawde
    http://arxiv.org/abs/2009.03068v1

    • [cs.CL]Why Not Simply Translate? A First Swedish Evaluation Benchmark for Semantic Similarity
    Tim Isbister, Magnus Sahlgren
    http://arxiv.org/abs/2009.03116v1

    • [cs.CR]Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data Hiding
    Sahar Abdelnabi, Mario Fritz
    http://arxiv.org/abs/2009.03015v1

    • [cs.CR]Attribute-Based Access Control for Smart Cities: A Smart Contract-Driven Framework
    Yuanyu Zhang, Mirei Yutaka, Masahiro Sasabe, Shoji Kasahara
    http://arxiv.org/abs/2009.02933v1

    • [cs.CV]3D Room Layout Estimation Beyond the Manhattan World Assumption
    Dongho Choi
    http://arxiv.org/abs/2009.02857v1

    • [cs.CV]A Deep Learning Approach to Tongue Detection for Pediatric Population
    Javad Rahimipour Anaraki, Silvia Orlandi, Tom Chau
    http://arxiv.org/abs/2009.02397v1

    • [cs.CV]A Genetic Feature Selection Based Two-stream Neural Network for Anger Veracity Recognition
    Chaoxing Huang, Xuanying Zhu, Tom Gedeon
    http://arxiv.org/abs/2009.02650v1

    • [cs.CV]A Light-Weight Object Detection Framework with FPA Module for Optical Remote Sensing Imagery
    Xi Gu, Lingbin Kong, Zhicheng Wang, Jie Li, Zhaohui Yu, Gang Wei
    http://arxiv.org/abs/2009.03063v1

    • [cs.CV]A Review on Near Duplicate Detection of Images using Computer Vision Techniques
    K. K. Thyagharajan, G. Kalaiarasi
    http://arxiv.org/abs/2009.03224v1

    • [cs.CV]A novel action recognition system for smart monitoring of elderly people using Action Pattern Image and Series CNN with transfer learning
    L. Aneesh Euprazia, K. K. Thyagharajan
    http://arxiv.org/abs/2009.03285v1

    • [cs.CV]ACDC: Weight Sharing in Atom-Coefficient Decomposed Convolution
    Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu
    http://arxiv.org/abs/2009.02386v1

    • [cs.CV]An Efficient Technique for Image Captioning using Deep Neural Network
    Borneel Bikash Phukan, Amiya Ranjan Panda
    http://arxiv.org/abs/2009.02565v1

    • [cs.CV]Approaches, Challenges, and Applications for Deep Visual Odometry: Toward to Complicated and Emerging Areas
    Ke Wang, Sai Ma, Junlan Chen, Fan Ren
    http://arxiv.org/abs/2009.02672v1

    • [cs.CV]Are Deep Neural Architectures Losing Information? Invertibility Is Indispensable
    Yang Liu, Zhenyue Qin, Saeed Anwar, Sabrina Caldwell, Tom Gedeon
    http://arxiv.org/abs/2009.03173v1

    • [cs.CV]Benchmarking off-the-shelf statistical shape modeling tools in clinical applications
    Anupama Goparaju, Alexandre Bone, Nan Hu, Heath B. Henninger, Andrew E. Anderson, Stanley Durrleman, Matthijs Jacxsens, Alan Morris, Ibolya Csecs, Nassir Marrouche, Shireen Y. Elhabian
    http://arxiv.org/abs/2009.02878v1

    • [cs.CV]Channel-wise Alignment for Adaptive Object Detection
    Hang Yang, Shan Jiang, Xinge Zhu, Mingyang Huang, Zhiqiang Shen, Chunxiao Liu, Jianping Shi
    http://arxiv.org/abs/2009.02862v1

    • [cs.CV]Class Interference Regularization
    Bharti Munjal, Sikandar Amin, Fabio Galasso
    http://arxiv.org/abs/2009.02396v1

    • [cs.CV]DV-ConvNet: Fully Convolutional Deep Learning on Point Clouds with Dynamic Voxelization and 3D Group Convolution
    Zhaoyu Su, Pin Siang Tan, Junkang Chow, Jimmy Wu, Yehur Cheong, Yu-Hsing Wang
    http://arxiv.org/abs/2009.02918v1

    • [cs.CV]DeePSD: Automatic Deep Skinning And Pose Space Deformation For 3D Garment Animation
    Hugo Bertiche, Meysam Madadi, Sergio Escalera
    http://arxiv.org/abs/2009.02715v1

    • [cs.CV]Deep Longitudinal Modeling of Infant Cortical Surfaces
    Peirong Liu, Zhengwang Wu, Gang Li, Pew-Thian Yap, Dinggang Shen
    http://arxiv.org/abs/2009.02797v1

    • [cs.CV]Deep Sparse Light Field Refocusing
    Shachar Ben Dayan, David Mendlovic, Raja Giryes
    http://arxiv.org/abs/2009.02582v1

    • [cs.CV]Deepfake detection: humans vs. machines
    Pavel Korshunov, Sébastien Marcel
    http://arxiv.org/abs/2009.03155v1

    • [cs.CV]Don’t miss the Mismatch: Investigating the Objective Function Mismatch for Unsupervised Representation Learning
    Bonifaz Stuhr, Jürgen Brauer
    http://arxiv.org/abs/2009.02383v1

    • [cs.CV]Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks
    Wei-An Lin, Chun Pong Lau, Alexander Levine, Rama Chellappa, Soheil Feizi
    http://arxiv.org/abs/2009.02470v1

    • [cs.CV]Efficient Pedestrian Detection in Top-View Fisheye Images Using Compositions of Perspective View Patches
    Sheng-Ho Chiang, Tsaipei Wang
    http://arxiv.org/abs/2009.02711v1

    • [cs.CV]End-to-End Deep Learning Model for Cardiac Cycle Synchronization from Multi-View Angiographic Sequences
    Raphaël Royer-Rivard, Fantin Girard, Nagib Dahdah, Farida Cheriet
    http://arxiv.org/abs/2009.02345v1

    • [cs.CV]Explanation of Unintended Radiated Emission Classification via LIME
    Tom Grimes, Eric Church, William Pitts, Lynn Wood
    http://arxiv.org/abs/2009.02418v1

    • [cs.CV]Frontier Detection and Reachability Analysis for Efficient 2D Graph-SLAM Based Active Exploration
    Zezhou Sun, Banghe Wu, Cheng-Zhong Xu, Sanjay E. Sarma, Jian Yang, Hui Kong
    http://arxiv.org/abs/2009.02869v1

    • [cs.CV]GazeMAE: General Representations of Eye Movements using a Micro-Macro Autoencoder
    Louise Gillian C. Bautista, Prospero C. Naval, Jr
    http://arxiv.org/abs/2009.02437v1

    • [cs.CV]Generalization on the Enhancement of Layerwise Relevance Interpretability of Deep Neural Network
    Erico Tjoa, Guan Cuntai
    http://arxiv.org/abs/2009.02516v1

    • [cs.CV]Improved Modeling of 3D Shapes with Multi-view Depth Maps
    Kamal Gupta, Susmija Jabbireddy, Ketul Shah, Abhinav Shrivastava, Matthias Zwicker
    http://arxiv.org/abs/2009.03298v1

    • [cs.CV]Improving colonoscopy lesion classification using semi-supervised deep learning
    Mayank Golhar, Taylor L. Bobrow, MirMilad Pourmousavi Khoshknab, Simran Jit, Saowanee Ngamruengphong, Nicholas J. Durr
    http://arxiv.org/abs/2009.03162v1

    • [cs.CV]Integrating Egocentric Localization for More Realistic Point-Goal Navigation Agents
    Samyak Datta, Oleksandr Maksymets, Judy Hoffman, Stefan Lee, Dhruv Batra, Devi Parikh
    http://arxiv.org/abs/2009.03231v1

    • [cs.CV]Interpretable Deep Multimodal Image Super-Resolution
    Iman Marivani, Evaggelia Tsiligianni, Bruno Cornelis, Nikos Deligiannis
    http://arxiv.org/abs/2009.03118v1

    • [cs.CV]Learning from Multiple Datasets with Heterogeneous and Partial Labels for Universal Lesion Detection in CT
    Ke Yan, Jinzheng Cai, Youjing Zheng, Adam P. Harrison, Dakai Jin, You-Bao Tang, Yu-Xing Tang, Lingyun Huang, Jing Xiao, Le Lu
    http://arxiv.org/abs/2009.02577v1

    • [cs.CV]Light Field View Synthesis via Aperture Flow and Propagation Confidence Map
    Nan Meng, Kai Li, Jianzhuang Liu, Edmund Y. Lam
    http://arxiv.org/abs/2009.02978v1

    • [cs.CV]MFL_COVID19: Quantifying Country-based Factors affecting Case Fatality Rate in Early Phase of COVID-19 Epidemic via Regularised Multi-task Feature Learning
    Po Yang, Jun Qi, Xulong Wang, Yun Yang
    http://arxiv.org/abs/2009.02827v1

    • [cs.CV]Multimodal Memorability: Modeling Effects of Semantics and Decay on Video Memorability
    Anelise Newman, Camilo Fosco, Vincent Casser, Allen Lee, Barry McNamara, Aude Oliva
    http://arxiv.org/abs/2009.02568v1

    • [cs.CV]Player Identification in Hockey Broadcast Videos
    Alvin Chan, Martin D. Levine, Mehrsan Javan
    http://arxiv.org/abs/2009.02429v1

    • [cs.CV]Progressive Bilateral-Context Driven Model for Post-Processing Person Re-Identification
    Min Cao, Chen Chen, Hao Dou, Xiyuan Hu, Silong Peng, Arjan Kuijper
    http://arxiv.org/abs/2009.03098v1

    • [cs.CV]Quantifying Explainability of Saliency Methods in Deep Neural Networks
    Erico Tjoa, Cuntai Guan
    http://arxiv.org/abs/2009.02899v1

    • [cs.CV]Real-Time Segmentation of Non-Rigid Surgical Tools based on Deep Learning and Tracking
    Luis C. García-Peraza-Herrera, Wenqi Li, Caspar Gruijthuijsen, Alain Devreker, George Attilakos, Jan Deprest, Emmanuel Vander Poorten, Danail Stoyanov, Tom Vercauteren, Sébastien Ourselin
    http://arxiv.org/abs/2009.03016v1

    • [cs.CV]Reverse-engineering Bar Charts Using Neural Networks
    Fangfang Zhou, Yong Zhao, Wenjiang Chen, Yijing Tan, Yaqi Xu, Yi Chen, Chao Liu, Ying Zhao
    http://arxiv.org/abs/2009.02491v1

    • [cs.CV]Stem-leaf segmentation and phenotypic trait extraction of maize shoots from three-dimensional point cloud
    Chao Zhu, Teng Miao, Tongyu Xu, Tao Yang, Na Li
    http://arxiv.org/abs/2009.03108v1

    • [cs.CV]Stochastic-YOLO: Efficient Probabilistic Object Detection under Dataset Shifts
    Tiago Azevedo, René de Jong, Partha Maji
    http://arxiv.org/abs/2009.02967v1

    • [cs.CV]TRANSPR: Transparency Ray-Accumulating Neural 3D Scene Point Renderer
    Maria Kolos, Artem Sevastopolsky, Victor Lempitsky
    http://arxiv.org/abs/2009.02819v1

    • [cs.CV]Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges
    Qingyong Hu, Bo Yang, Sheikh Khalid, Wen Xiao, Niki Trigoni, Andrew Markham
    http://arxiv.org/abs/2009.03137v1

    • [cs.CV]Uncertainty Inspired RGB-D Saliency Detection
    Jing Zhang, Deng-Ping Fan, Yuchao Dai, Saeed Anwar, Fatemeh Saleh, Sadegh Aliakbarian, Nick Barnes
    http://arxiv.org/abs/2009.03075v1

    • [cs.CV]Unsupervised Wasserstein Distance Guided Domain Adaptation for 3D Multi-Domain Liver Segmentation
    Chenyu You, Junlin Yang, Julius Chapiro, James S. Duncan
    http://arxiv.org/abs/2009.02831v1

    • [cs.CV]User-Guided Domain Adaptation for Rapid Annotation from User Interactions: A Study on Pathological Liver Segmentation
    Ashwin Raju, Zhanghexuan Ji, Chi Tung Cheng, Jinzheng Cai, Junzhou Huang, Jing Xiao, Le Lu, ChienHung Liao, Adam P. Harrison
    http://arxiv.org/abs/2009.02455v1

    • [cs.CV]User-assisted Video Reflection Removal
    Amgad Ahmed, Suhong Kim, Mohamed Elgharib, Mohamed Hefeeda
    http://arxiv.org/abs/2009.03281v1

    • [cs.CV]Video Moment Retrieval via Natural Language Queries
    Xinli Yu, Mohsen Malmir, Cynthia He, Yue Liu, Rex Wu
    http://arxiv.org/abs/2009.02406v1

    • [cs.CV]Visual Object Tracking by Segmentation with Graph Convolutional Network
    Bo Jianga, Panpan Zhang, Lili Huang
    http://arxiv.org/abs/2009.02523v1

    • [cs.CV]Visual Sentiment Analysis from Disaster Images in Social Media
    Syed Zohaib Hassan, Kashif Ahmad, Steven Hicks, Paal Halvorsen, Ala Al-Fuqaha, Nicola Conci, Michael Riegler
    http://arxiv.org/abs/2009.03051v1

    • [cs.CY]Critical Business Decision Making for Technology Startups — A PerceptIn Case Study
    Shaoshan Liu
    http://arxiv.org/abs/2009.03011v1

    • [cs.CY]Detecting Informal Organization Through Data Mining Techniques
    Maryam Abdirad, Jamal Shahrabi
    http://arxiv.org/abs/2009.02895v1

    • [cs.CY]Hawkes-modeled telecommunication patterns reveal relationship dynamics and personality traits
    Mateusz Nurek, Radosław Michalski, Marian-Andrei Rizoiu
    http://arxiv.org/abs/2009.02032v2

    • [cs.CY]IVACS: Intelligent Voice Assistant for Coronavirus Disease (COVID-19) Self-Assessment
    Parashar Dhakal, Praveen Damacharla, Ahmad Y. Javaid, Hari K. Vege, Vijay K. Devabhaktuni
    http://arxiv.org/abs/2009.02673v1

    • [cs.CY]Improving Maritime Traffic Emission Estimations on Missing Data with CRBMs
    Alberto Gutierrez-Torre, Josep Ll. Berral, David Buchaca, Marc Guevara, Albert Soret, David Carrera
    http://arxiv.org/abs/2009.03001v1

    • [cs.CY]Intelligent Luminaire based Real-time Indoor Positioning for Assisted Living
    Iuliana Marin, Maria Iuliana Bocicor, Arthur-Jozsef Molnar
    http://arxiv.org/abs/2009.02483v1

    • [cs.CY]Measuring Massive Multitask Language Understanding
    Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, Jacob Steinhardt
    http://arxiv.org/abs/2009.03300v1

    • [cs.CY]Motivated Reasoning and Blame: Responses to Performance Framing and Outgroup Triggers during COVID-19
    Gregory A. Porumbescu, Donald Moynihan, Jason Anastasopoulos, Asmus Leth Olsen
    http://arxiv.org/abs/2009.03037v1

    • [cs.CY]Report on the 2019 Workshop on Smart Farming and Data Analytics (SFDAI)
    Liadh Kelly, Simone van der Burg, Aine Regan, Peter Mooney
    http://arxiv.org/abs/2009.03088v1

    • [cs.CY]Respect for Human Autonomy in Recommender Systems
    Lav R. Varshney
    http://arxiv.org/abs/2009.02603v1

    • [cs.CY]SilkViser:A Visual Explorer of Blockchain-based Cryptocurrency Transaction Data
    Zengsheng Zhong, Shuirun Wei, Yeting Xu, Ying Zhao, Fangfang Zhou, Feng Luo, Ronghua Shi
    http://arxiv.org/abs/2009.02651v1

    • [cs.CY]Technological Platform for the Prevention and Management of Healthcare Associated Infections and Outbreaks
    Maria Iuliana Bocicor, Maria Dascălu, Agnieszka Gaczowska, Sorin Hostiuc, Alin Moldoveanu, Antonio Molina, Arthur-Jozsef Molnar, Ionuţ Negoi, Vlad Racoviţă
    http://arxiv.org/abs/2009.02502v1

    • [cs.CY]Text Mining over Curriculum Vitae of Peruvian Professionals using Official Scientific Site DINA
    Josimar Edinson Chire Saire, Honorio Apaza Alanoca
    http://arxiv.org/abs/2009.03087v1

    • [cs.CY]Towards an Interoperable Data Protocol Aimed at Linking the Fashion Industry with AI Companies
    Mohammed Al-Rawi, Joeran Beel
    http://arxiv.org/abs/2009.03005v1

    • [cs.DC]“Reduction of Monetary Cost in Cloud Storage System by Using Extended Strict Timed Causal Consistency”
    Hesam Nejati Sharif Aldin, Mostafa Razavi Ghods, Hossein Deldari
    http://arxiv.org/abs/2009.02355v1

    • [cs.DC]An SMDP-Based Approach to Thermal-Aware Task Scheduling in NoC-based MPSoC platforms
    Farnaz Niknia, Kiamehr Rezaee, Vesal Hakami
    http://arxiv.org/abs/2009.02813v1

    • [cs.DC]Asynchronous Runtime with Distributed Manager for Task-based Programming Models
    Jaume Bosch, Carlos Álvarez, Daniel Jiménez-González, Xavier Martorell, Eduard Ayguadé
    http://arxiv.org/abs/2009.03066v1

    • [cs.DC]Design and Evaluation of a Simple Data Interface for Efficient Data Transfer Across Diverse Storage
    Zhengchun Liu, Rajkumar Kettimuthu, Joaquin Chung, Rachana Ananthakrishnan, Michael Link, Ian Foster
    http://arxiv.org/abs/2009.03190v1

    • [cs.DC]Hierarchical Roofline Analysis: How to Collect Data using Performance Tools on Intel CPUs and NVIDIA GPUs
    Charlene Yang
    http://arxiv.org/abs/2009.02449v1

    • [cs.DC]Infrastructure de Services Cloud FaaS sur noeuds IoT
    David Fernández Blanco, Frédéric Le Mouël
    http://arxiv.org/abs/2009.02511v1

    • [cs.DC]Running Neural Networks on the NIC
    Giuseppe Siracusano, Salvator Galea, Davide Sanvito, Mohammad Malekzadeh, Hamed Haddadi, Gianni Antichi, Roberto Bifulco
    http://arxiv.org/abs/2009.02353v1

    • [cs.DS]Multi-Way Number Partitioning: an Information-Theoretic View
    Niloufar Ahmadypour, Amin Gohari
    http://arxiv.org/abs/2009.02710v1

    • [cs.GR]Interactive Visualization of Terascale Data in the Browser: Fact or Fiction?
    Will Usher, Valerio Pascucci
    http://arxiv.org/abs/2009.03254v1

    • [cs.GT]PAC Reinforcement Learning Algorithm for General-Sum Markov Games
    Ashkan Zehfroosh, Herbert G. Tanner
    http://arxiv.org/abs/2009.02605v1

    • [cs.HC]Visually Analyzing Contextualized Embeddings
    Matthew Berger
    http://arxiv.org/abs/2009.02554v1

    • [cs.IR]“And the Winner Is…”: Dynamic Lotteries for Multi-group Fairness-Aware Recommendation
    Nasim Sonboli, Robin Burke, Nicholas Mattei, Farzad Eskandanian, Tian Gao
    http://arxiv.org/abs/2009.02590v1

    • [cs.IR]An Improved Algorithm for Fast K-Word Proximity Search Based on Multi-Component Key Indexes
    Alexander B. Veretennikov
    http://arxiv.org/abs/2009.02684v1

    • [cs.IR]CAVA: A Visual Analytics System for Exploratory Columnar Data Augmentation Using Knowledge Graphs
    Dylan Cashman, Shenyu Xu, Subhajit Das, Florian Heimerl, Cong Liu, Shah Rukh Humayoun, Michael Gleicher, Alex Endert, Remco Chang
    http://arxiv.org/abs/2009.02865v1

    • [cs.IR]Contextual Personalized Re-Ranking of Music Recommendations through Audio Features
    Boning Gong, Mesut Kaya, Nava Tintarev
    http://arxiv.org/abs/2009.02782v1

    • [cs.IR]Detecting User Community in Sparse Domain via Cross-Graph Pairwise Learning
    Zheng Gao, Hongsong Li, Zhuoren Jiang, Xiaozhong Liu
    http://arxiv.org/abs/2009.02637v1

    • [cs.IR]Efficient Personalized Community Detection via Genetic Evolution
    Zheng Gao, Chun Guo, Xiaozhong Liu
    http://arxiv.org/abs/2009.02657v1

    • [cs.IR]Personalized Review Ranking for Improving Shopper’s Decision Making: A Term Frequency based Approach
    Akhil Sai Peddireddy
    http://arxiv.org/abs/2009.03258v1

    • [cs.IR]Vapur: A Search Engine to Find Related Protein — Compound Pairs in COVID-19 Literature
    Abdullatif Köksal, Hilal Dönmez, Rıza Özçelik, Elif Ozkirimli, Arzucan Özgür
    http://arxiv.org/abs/2009.02526v1

    • [cs.IT]A Class of Optimal Structures for Node Computations in Message Passing Algorithms
    Xuan He, Kui Cai, Liang Zhou
    http://arxiv.org/abs/2009.02535v1

    • [cs.IT]Alternating Beamforming with Intelligent Reflecting Surface Element Allocation
    Hyesang Cho, Junil Choi
    http://arxiv.org/abs/2009.02875v1

    • [cs.IT]Analysis of Uplink IRS-Assisted NOMA under Nakagami-m Fading via Moments Matching
    Bashar Tahir, Stefan Schwarz, Markus Rupp
    http://arxiv.org/abs/2009.03133v1

    • [cs.IT]Centralized & Distributed Deep Reinforcement Learning Methods for Downlink Sum-Rate Optimization
    Ahmad Ali Khan, Raviraj Adve
    http://arxiv.org/abs/2009.03033v1

    • [cs.IT]Deep Ensemble of Weighted Viterbi Decoders for Tail-Biting Convolutional Codes
    Tomer Raviv, Asaf Schwartz, Yair Be’ery
    http://arxiv.org/abs/2009.02591v1

    • [cs.IT]End-to-End Mutual-Coupling-Aware Communication Model for Reconfigurable Intelligent Surfaces: An Electromagnetic-Compliant Approach Based on Mutual Impedances
    Gabriele Gradoni, Marco Di Renzo
    http://arxiv.org/abs/2009.02694v1

    • [cs.IT]Extended quasi-cyclic constructions of quantum codes and entanglement-assisted quantum codes
    Jingjie Lv, Ruihu Li, Yu Yao
    http://arxiv.org/abs/2009.02543v1

    • [cs.IT]Finite-Alphabet MMSE Equalization for All-Digital Massive MU-MIMO mmWave Communication
    Oscar Castañeda, Sven Jacobsson, Giuseppe Durisi, Tom Goldstein, Christoph Studer
    http://arxiv.org/abs/2009.02747v1

    • [cs.IT]Improved Error Performance in NOMA-based Diamond Relaying
    Ferdi Kara, Hakan Kaya
    http://arxiv.org/abs/2009.02682v1

    • [cs.IT]Multiple Private Key Generation for Continuous Memoryless Sources with A Helper
    Lin Zhou
    http://arxiv.org/abs/2009.02852v1

    • [cs.IT]New Upper Bounds in the Hypothesis Testing Problem with Information Constraints
    Marat V. Burnashev
    http://arxiv.org/abs/2009.03149v1

    • [cs.IT]Optimal Deterministic Group Testing Algorithms to Estimate the Number of Defectives
    Nader H. Bshouty, Catherine A. Haddad-Zaknoon
    http://arxiv.org/abs/2009.02520v1

    • [cs.IT]Optimal Scheduling Policy for Minimizing Age of Information with a Relay
    Jaeyoung Song, Deniz Gunduz, Wan Choi
    http://arxiv.org/abs/2009.02716v1

    • [cs.IT]Performance Analysis and User Association Optimization for Wireless Network Aided by Multiple Intelligent Reflecting Surfaces
    Weidong Mei, Rui Zhang
    http://arxiv.org/abs/2009.02551v1

    • [cs.IT]Reconfigurable Intelligent Surfaces for Localization: Position and Orientation Error Bounds
    Ahmed Elzanaty, Anna Guerra, Francesco Guidi, Mohamed-Slim Alouini
    http://arxiv.org/abs/2009.02818v1

    • [cs.IT]Soft-Output Finite Alphabet Equalization for mmWAVE Massive MIMO
    Oscar Castañeda, Sven Jacobsson, Giuseppe Durisi, Tom Goldstein, Christoph Studer
    http://arxiv.org/abs/2009.02990v1

    • [cs.IT]User Selection Approaches to Mitigate the Straggler Effect for Federated Learning on Cell-Free Massive MIMO Networks
    Tung T. Vu, Duy T. Ngo, Hien Quoc Ngo, Minh N. Dao, Nguyen H. Tran, Richard H. Middleton
    http://arxiv.org/abs/2009.02031v2

    • [cs.IT]Weighted Information Filtering, Smoothing, and Out-of-Sequence Measurement Processing
    Yaron Shulami, Daniel Sigalov
    http://arxiv.org/abs/2009.02659v1

    • [cs.LG]A Change-Detection Based Thompson Sampling Framework for Non-Stationary Bandits
    Gourab Ghatak
    http://arxiv.org/abs/2009.02791v1

    • [cs.LG]A Framework for Private Matrix Analysis
    Jalaj Upadhyay, Sarvagya Upadhyay
    http://arxiv.org/abs/2009.02668v1

    • [cs.LG]A Generative Adversarial Approach To ECG Synthesis And Denoising
    Karol Antczak
    http://arxiv.org/abs/2009.02700v1

    • [cs.LG]A Hybrid PAC Reinforcement Learning Algorithm
    Ashkan Zehfroosh, Herbert G. Tanner
    http://arxiv.org/abs/2009.02602v1

    • [cs.LG]A Neural Network Perturbation Theory Based on the Born Series
    Bastian Kaspschak, Ulf-G. Meißner
    http://arxiv.org/abs/2009.03192v1

    • [cs.LG]A Simple and General Graph Neural Network with Stochastic Message Passing
    Ziwei Zhang, Chenhao Niu, Peng Cui, Bo Zhang, Wei Cui, Wenwu Zhu
    http://arxiv.org/abs/2009.02562v1

    • [cs.LG]A perturbation based out-of-sample extension framework
    Roy Mitz, Yoel Shkolnisky
    http://arxiv.org/abs/2009.02955v1

    • [cs.LG]An Analysis of Alternating Direction Method of Multipliers for Feed-forward Neural Networks
    Seyedeh Niusha Alavi Foumani, Ce Guo, Wayne Luk
    http://arxiv.org/abs/2009.02825v1

    • [cs.LG]An FPGA Accelerated Method for Training Feed-forward Neural Networks Using Alternating Direction Method of Multipliers and LSMR
    Seyedeh Niusha Alavi Foumani, Ce Guo, Wayne Luk
    http://arxiv.org/abs/2009.02784v1

    • [cs.LG]Anomaly Detection With Partitioning Overfitting Autoencoder Ensembles
    Boris Lorbeer, Max Botler
    http://arxiv.org/abs/2009.02755v1

    • [cs.LG]Automatic detection of microsleep episodes with deep learning
    Alexander Malafeev, Anneke Hertig-Godeschalk, David R. Schreier, Jelena Skorucak, Johannes Mathis, Peter Achermann
    http://arxiv.org/abs/2009.03027v1

    • [cs.LG]Black Box to White Box: Discover Model Characteristics Based on Strategic Probing
    Josh Kalin, Matthew Ciolino, David Noever, Gerry Dozier
    http://arxiv.org/abs/2009.03136v1

    • [cs.LG]Bluff: Interactively Deciphering Adversarial Attacks on Deep Neural Networks
    Nilaksh Das, Haekyu Park, Zijie J. Wang, Fred Hohman, Robert Firstman, Emily Rogers, Duen Horng, Chau
    http://arxiv.org/abs/2009.02608v1

    • [cs.LG]Computational Models for Academic Performance Estimation
    Vipul Bansal, Himanshu Buckchash, Balasubramanian Raman
    http://arxiv.org/abs/2009.02661v1

    • [cs.LG]Crowding Prediction of In-Situ Metro Passengers Using Smart Card Data
    Xiancai Tian, Chen Zhang, Baihua Zheng
    http://arxiv.org/abs/2009.02880v1

    • [cs.LG]Detection Defense Against Adversarial Attacks with Saliency Map
    Dengpan Ye, Chuanxi Chen, Changrui Liu, Hao Wang, Shunzhi Jiang
    http://arxiv.org/abs/2009.02738v1

    • [cs.LG]Discovering Reliable Causal Rules
    Kailash Budhathoki, Mario Boley, Jilles Vreeken
    http://arxiv.org/abs/2009.02728v1

    • [cs.LG]Dynamically Computing Adversarial Perturbations for Recurrent Neural Networks
    Shankar A. Deka, Dušan M. Stipanović, Claire J. Tomlin
    http://arxiv.org/abs/2009.02874v1

    • [cs.LG]ECOC as a Method of Constructing Deep Convolutional Neural Network Ensembles
    Sara Atito Ali Ahmed, Cemre Zor, Berrin Yanikoglu, Muhammad Awais, Josef Kittler
    http://arxiv.org/abs/2009.02961v1

    • [cs.LG]Efficient Projection Algorithms onto the Weighted l1 Ball
    Guillaume Perez, Sebastian Ament, Carla Gomes, Michel Barlaud
    http://arxiv.org/abs/2009.02980v1

    • [cs.LG]FLFE: A Communication-Efficient and Privacy-Preserving Federated Feature Engineering Framework
    Pei Fang, Zhendong Cai, Hui Chen, QingJiang Shi
    http://arxiv.org/abs/2009.02557v1

    • [cs.LG]Fast and Secure Distributed Nonnegative Matrix Factorization
    Yuqiu Qian, Conghui Tan, Danhao Ding, Hui Li, Nikos Mamoulis
    http://arxiv.org/abs/2009.02845v1

    • [cs.LG]FlipOut: Uncovering Redundant Weights via Sign Flipping
    Andrei Apostol, Maarten Stol, Patrick Forré
    http://arxiv.org/abs/2009.02594v1

    • [cs.LG]GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training
    Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-yan Liu, Liwei Wang
    http://arxiv.org/abs/2009.03294v1

    • [cs.LG]HLSGD Hierarchical Local SGD With Stale Gradients Featuring
    Yuhao Zhou, Qing Ye, Hailun Zhang, Jiancheng Lv
    http://arxiv.org/abs/2009.02701v1

    • [cs.LG]Hybrid Differentially Private Federated Learning on Vertically Partitioned Data
    Chang Wang, Jian Liang, Mingkai Huang, Bing Bai, Kun Bai, Hao Li
    http://arxiv.org/abs/2009.02763v1

    • [cs.LG]Implicit Multidimensional Projection of Local Subspaces
    Rongzheng Bian, Yumeng Xue, Liang Zhou, Jian Zhang, Baoquan Chen, Daniel Weiskopf, Yunhai Wang
    http://arxiv.org/abs/2009.03259v1

    • [cs.LG]Information Theoretic Counterfactual Learning from Missing-Not-At-Random Feedback
    Zifeng Wang, Xi Chen, Rui Wen, Shao-Lun Huang, Ercan E. Kuruoglu, Yefeng Zheng
    http://arxiv.org/abs/2009.02623v1

    • [cs.LG]Information Theoretic Meta Learning with Gaussian Processes
    Michalis K. Titsias, Sotirios Nikoloutsopoulos, Alexandre Galashov
    http://arxiv.org/abs/2009.03228v1

    • [cs.LG]Iterative Correction of Sensor Degradation and a Bayesian Multi-Sensor Data Fusion Method
    Luka Kolar, Rok Šikonja, Lenart Treven
    http://arxiv.org/abs/2009.03091v1

    • [cs.LG]LFGCN: Levitating over Graphs with Levy Flights
    Yuzhou Chen, Yulia R. Gel, Konstantin Avrachenkov
    http://arxiv.org/abs/2009.02365v1

    • [cs.LG]Learning Inter- and Intra-manifolds for Matrix Factorization-based Multi-Aspect Data Clustering
    Khanh Luong, Richi Nayak
    http://arxiv.org/abs/2009.02859v1

    • [cs.LG]Learning Unbiased Representations via Rényi Minimization
    Vincent Grari, Oualid El Hajouji, Sylvain Lamprier, Marcin Detyniecki
    http://arxiv.org/abs/2009.03183v1

    • [cs.LG]Learning from Very Few Samples: A Survey
    Jiang Lu, Pinghua Gong, Jieping Ye, Changshui Zhang
    http://arxiv.org/abs/2009.02653v1

    • [cs.LG]Learning to Rank under Multinomial Logit Choice
    James A. Grant, David S. Leslie
    http://arxiv.org/abs/2009.03207v1

    • [cs.LG]Optimizing Mode Connectivity via Neuron Alignment
    N. Joseph Tatro, Pin-Yu Chen, Payel Das, Igor Melnyk, Prasanna Sattigeri, Rongjie Lai
    http://arxiv.org/abs/2009.02439v1

    • [cs.LG]Ordinal-Content VAE: Isolating Ordinal-Valued Content Factors in Deep Latent Variable Models
    Minyoung Kim, Vladimir Pavlovic
    http://arxiv.org/abs/2009.03034v1

    • [cs.LG]Particle Swarm Optimized Federated Learning For Industrial IoT and Smart City Services
    Basheer Qolomany, Kashif Ahmad, Ala Al-Fuqaha, Junaid Qadir
    http://arxiv.org/abs/2009.02560v1

    • [cs.LG]Profiling US Restaurants from Billions of Payment Card Transactions
    Himel Dev, Hossein Hamooni
    http://arxiv.org/abs/2009.02461v1

    • [cs.LG]PySAD: A Streaming Anomaly Detection Framework in Python
    Selim F. Yilmaz, Suleyman S. Kozat
    http://arxiv.org/abs/2009.02572v1

    • [cs.LG]Real-time and Large-scale Fleet Allocation of Autonomous Taxis: A Case Study in New York Manhattan Island
    Yue Yang, Wencang Bao, Mohsen Ramezani, Zhe Xu
    http://arxiv.org/abs/2009.02762v1

    • [cs.LG]Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices
    Luo Luo, Cheng Chen, Guangzeng Xie, Haishan Ye
    http://arxiv.org/abs/2009.02553v1

    • [cs.LG]S-SGD: Symmetrical Stochastic Gradient Descent with Weight Noise Injection for Reaching Flat Minima
    Wonyong Sung, Iksoo Choi, Jinhwan Park, Seokhyun Choi, Sungho Shin
    http://arxiv.org/abs/2009.02479v1

    • [cs.LG]Scaling up Differentially Private Deep Learning with Fast Per-Example Gradient Clipping
    Jaewoo Lee, Daniel Kifer
    http://arxiv.org/abs/2009.03106v1

    • [cs.LG]Sparse Network Inversion for Key Instance Detection in Multiple Instance Learning
    Beomjo Shin, Junsu Cho, Hwanjo Yu, Seungjin Choi
    http://arxiv.org/abs/2009.02909v1

    • [cs.LG]Stabilizing Invertible Neural Networks Using Mixture Models
    Paul Hagemann, Sebastian Neumayer
    http://arxiv.org/abs/2009.02994v1

    • [cs.LG]System Identification Through Lipschitz Regularized Deep Neural Networks
    Elisa Negrini, Giovanna Citti, Luca Capogna
    http://arxiv.org/abs/2009.03288v1

    • [cs.LG]Towards Probabilistic Tensor Canonical Polyadic Decomposition 2.0: Automatic Tensor Rank Learning Using Generalized Hyperbolic Prior
    Lei Cheng, Zhongtao Chen, Qingjiang Shi, Yik-Chung Wu, Sergios Theodoridis
    http://arxiv.org/abs/2009.02472v1

    • [cs.LG]Unifying Clustered and Non-stationary Bandits
    Chuanhao Li, Qingyun Wu, Hongning Wang
    http://arxiv.org/abs/2009.02463v1

    • [cs.LG]Using Machine Teaching to Investigate Human Assumptions when Teaching Reinforcement Learners
    Yun-Shiuan Chuang, Xuezhou Zhang, Yuzhe Ma, Mark K. Ho, Joseph L. Austerweil, Xiaojin Zhu
    http://arxiv.org/abs/2009.02476v1

    • [cs.LG]Why Spectral Normalization Stabilizes GANs: Analysis and Improvements
    Zinan Lin, Vyas Sekar, Giulia Fanti
    http://arxiv.org/abs/2009.02773v1

    • [cs.LO]Ambiguity Hierarchy of Regular Infinite Tree Languages
    Alexander Rabinovich, Doron Tiferet
    http://arxiv.org/abs/2009.02985v1

    • [cs.NI]Blockchain-based Privacy Preservation for 5G-enabled Drone Communications
    Yulei Wu, Hong-Ning Dai, Hao Wang, Kim-Kwang Raymond Choo
    http://arxiv.org/abs/2009.03164v1

    • [cs.NI]Examining Machine Learning for 5G and Beyond through an Adversarial Lens
    Muhammad Usama, Rupendra Nath Mitra, Inaam Ilahi, Junaid Qadir, Mahesh K. Marina
    http://arxiv.org/abs/2009.02473v1

    • [cs.NI]Summarization in Semantic Based Service Discovery in Dynamic IoT-Edge Networks
    Hessam Moeini, I-Ling Yen, Farokh Bastani
    http://arxiv.org/abs/2009.02858v1

    • [cs.NI]Unleashing In-network Computing on Scientific Workloads
    Daehyeok Kim, Ankush Jain, Zaoxing Liu, George Amvrosiadis, Damian Hazen, Bradley Settlemyer, Vyas Sekar
    http://arxiv.org/abs/2009.02457v1

    • [cs.RO]A Hierarchical Architecture for Human-Robot Cooperation Processes
    Kourosh Darvish, Enrico Simetti, Fulvio Mastrogiovanni, Giuseppe Casalino
    http://arxiv.org/abs/2009.02807v1

    • [cs.RO]A Robust Laser-Inertial Odometry and Mapping Method for Large-Scale Highway Environments
    Shibo Zhao, Zheng Fang, HaoLai Li, Sebastian Scherer
    http://arxiv.org/abs/2009.02622v1

    • [cs.RO]Animated Cassie: A Dynamic Relatable Robotic Character
    Zhongyu Li, Christine Cummings, Koushil Sreenath
    http://arxiv.org/abs/2009.02846v1

    • [cs.RO]BP-RRT: Barrier Pair Synthesis for Temporal Logic Motion Planning
    Binghan He, Jaemin Lee, Ufuk Topcu, Luis Sentis
    http://arxiv.org/abs/2009.02432v1

    • [cs.RO]Learning Topological Motion Primitives for Knot Planning
    Mengyuan Yan, Gen Li, Yilin Zhu, Jeannette Bohg
    http://arxiv.org/abs/2009.02615v1

    • [cs.RO]Receding Horizon Task and Motion Planning in Dynamic Environments
    Nicola Castaman, Enrico Pagello, Emanuele Menegatti, Alberto Pretto
    http://arxiv.org/abs/2009.03139v1

    • [cs.SE]Efficient Framework for Learning Code Representations through Semantic-Preserving Program Transformations
    Nghi D. Q. Bui
    http://arxiv.org/abs/2009.02731v1

    • [cs.SE]Improving Problem Identification via Automated Log Clustering using Dimensionality Reduction
    Carl Martin Rosenberg, Leon Moonen
    http://arxiv.org/abs/2009.03257v1

    • [cs.SE]The Integrity of Machine Learning Algorithms against Software Defect Prediction
    Param Khakhar and, Rahul Kumar Dubey, Senior Member IEEE
    http://arxiv.org/abs/2009.02571v1

    • [cs.SE]distr6: R6 Object-Oriented Probability Distributions Interface in R
    Raphael Sonabend, Franz Kiraly
    http://arxiv.org/abs/2009.02993v1

    • [cs.SI]Analysing Twitter Semantic Networks: the case of 2018 Italian Elections
    Tommaso Radicioni, Elena Pavan, Tiziano Squartini, Fabio Saracco
    http://arxiv.org/abs/2009.02960v1

    • [cs.SI]Friend Network as Gatekeeper: A Study of WeChat Users’ Consumption of Friend-Curated Contents
    Quan Li, Zhenhui Peng, Haipeng Zeng, Qiaoan Chen, Lingling Yi, Ziming Wu, Xiaojuan Ma, Tianjian Chen
    http://arxiv.org/abs/2009.02531v1

    • [cs.SI]HAP-SAP: Semantic Annotation in LBSNs using Latent Spatio-Temporal Hawkes Process
    Manisha Dubey, P. K. Srijith, Maunendra Sankar Desarkar
    http://arxiv.org/abs/2009.02548v1

    • [cs.SI]Preserving Minority Structures in Graph Sampling
    Ying Zhao, Haojin Jiang, Qi’an Chen, Yaqi Qin, Huixuan Xie, Yitao Wu Shixia Liu, Zhiguang Zhou, Jiazhi Xia, Fangfang Zhou
    http://arxiv.org/abs/2009.02498v1

    • [cs.SI]Utilizing Citation Network Structure to Predict Citation Counts: A Deep Learning Approach
    Qihang Zhao
    http://arxiv.org/abs/2009.02647v1

    • [econ.EM]Doubly Robust Semiparametric Difference-in-Differences Estimators with High-Dimensional Data
    Yang Ning, Sida Peng, Jing Tao
    http://arxiv.org/abs/2009.03151v1

    • [eess.AS]Any-to-Many Voice Conversion with Location-Relative Sequence-to-Sequence Modeling
    Songxiang Liu, Yuewen Cao, Disong Wang, Xixin Wu, Xunying Liu, Helen Meng
    http://arxiv.org/abs/2009.02725v1

    • [eess.AS]Cross-domain Adaptation with Discrepancy Minimization for Text-independent Forensic Speaker Verification
    Zhenyu Wang, Wei Xia, John H. L. Hansen
    http://arxiv.org/abs/2009.02444v1

    • [eess.AS]KoSpeech: Open-Source Toolkit for End-to-End Korean Speech Recognition
    Soohwan Kim, Seyoung Bae, Cheolhwang Won
    http://arxiv.org/abs/2009.03092v1

    • [eess.AS]Libri-Adapt: A New Speech Dataset for Unsupervised Domain Adaptation
    Akhil Mathur, Fahim Kawsar, Nadia Berthouze, Nicholas D. Lane
    http://arxiv.org/abs/2009.02814v1

    • [eess.IV]Brain Tumor Survival Prediction using Radiomics Features
    Sobia Yousaf, Syed Muhammad Anwar, Harish RaviPrakash, Ulas Bagci
    http://arxiv.org/abs/2009.02903v1

    • [eess.IV]Deep Learning for Automatic Spleen Length Measurement in Sickle Cell Disease Patients
    Zhen Yuan, Esther Puyol-Anton, Haran Jogeesvaran, Catriona Reid, Baba Inusa, Andrew P. King
    http://arxiv.org/abs/2009.02704v1

    • [eess.IV]Edge-variational Graph Convolutional Networks for Uncertainty-aware Disease Prediction
    Yongxiang Huang, Albert C. S. Chung
    http://arxiv.org/abs/2009.02759v1

    • [eess.IV]Max-Fusion U-Net for Multi-Modal Pathology Segmentation with Attention and Dynamic Resampling
    Haochuan Jiang, Chengjia Wang, Agisilaos Chartsias, Sotirios A. Tsaftaris
    http://arxiv.org/abs/2009.02569v1

    • [eess.IV]Perfusion Imaging: A Data Assimilation Approach
    Peirong Liu, Yueh Z. Lee, Stephen R. Aylward, Marc Niethammer
    http://arxiv.org/abs/2009.02796v1

    • [eess.IV]Semi-supervised Pathology Segmentation with Disentangled Representations
    Haochuan Jiang, Agisilaos Chartsias, Xinheng Zhang, Giorgos Papanastasiou, Scott Semple, Mark Dweck, David Semple, Rohan Dharmakumar, Sotirios A. Tsaftaris
    http://arxiv.org/abs/2009.02564v1

    • [eess.IV]The 2ST-UNet for Pneumothorax Segmentation in Chest X-Rays using ResNet34 as a Backbone for U-Net
    Ayat Abedalla, Malak Abdullah, Mahmoud Al-Ayyoub, Elhadj Benkhelifa
    http://arxiv.org/abs/2009.02805v1

    • [eess.IV]Towards learned optimal q-space sampling in diffusion MRI
    Tomer Weiss, Sanketh Vedula, Ortal Senouf, Oleg Michailovich, AlexBronstein
    http://arxiv.org/abs/2009.03008v1

    • [eess.SP]A Survey of Deep Learning Architectures for Intelligent Reflecting Surfaces
    Ahmet M. Elbir, Kumar Vijay Mishra
    http://arxiv.org/abs/2009.02540v1

    • [eess.SP]Adaptive and Fast Combined Waveform-Beamforming Design for mmWave Automotive Joint Communication-Radar
    Preeti Kumari, Nitin Jonathan Myers, Robert W. Heath Jr
    http://arxiv.org/abs/2009.02633v1

    • [eess.SP]Antenna Selection for Improving Energy Efficiency in XL-MIMO Systems
    José Carlos Marinello, Taufik Abrão, Abolfazl Amiri, Elisabeth de Carvalho, Petar Popovski
    http://arxiv.org/abs/2009.02542v1

    • [eess.SP]CSI-Based Multi-Antenna and Multi-Point Indoor Positioning Using Probability Fusion
    Emre Gönültaş, Eric Lei, Jack Langerman, Howard Huang, Christoph Studer
    http://arxiv.org/abs/2009.02798v1

    • [eess.SP]Data-Driven Transferred Energy Management Strategy for Hybrid Electric Vehicles via Deep Reinforcement Learning
    Jiangdong Liao, Teng Liu, Wenhao Tan, Shaobo Lu, Yalian Yang
    http://arxiv.org/abs/2009.03289v1

    • [eess.SP]Edge Learning with Unmanned Ground Vehicle: Joint Path, Energy and Sample Size Planning
    Dan Liu, Shuai Wang, Zhigang Wen, Lei Cheng, Miaowen Wen, Yik-Chung Wu
    http://arxiv.org/abs/2009.03140v1

    • [eess.SP]Simultaneous Energy Harvesting and Gait Recognition using Piezoelectric Energy Harvester
    Dong Ma, Guohao Lan, Weitao Xu, Mahbub Hassan, Wen Hu
    http://arxiv.org/abs/2009.02752v1

    • [eess.SY]Preserving Privacy of the Influence Structure in Friedkin-Johnsen Systems
    Jack Liell-Cock, Ian R. Manchester, Guodong Shi
    http://arxiv.org/abs/2009.02627v1

    • [hep-th]Machine Learning Calabi-Yau Four-folds
    Yang-Hui He, Andre Lukas
    http://arxiv.org/abs/2009.02544v1

    • [math.CO]Information Hiding Using Matroid Theory
    Ragnar Freij-Hollanti, Olga Kuznetsova
    http://arxiv.org/abs/2009.02991v1

    • [math.DS]OnsagerNet: Learning Stable and Interpretable Dynamics using a Generalized Onsager Principle
    Haijun Yu, Xinyuan Tian, Weinan E, Qianxiao Li
    http://arxiv.org/abs/2009.02327v1

    • [math.MG]Area-Invariant Pedal-Like Curves Derived from the Ellipse
    Dan Reznik, Ronaldo Garcia, Hellmuth Stachel
    http://arxiv.org/abs/2009.02581v1

    • [math.NA]Higher-order Quasi-Monte Carlo Training of Deep Neural Networks
    M. Longo, S. Mishra, T. K. Rusch, Ch. Schwab
    http://arxiv.org/abs/2009.02713v1

    • [math.NA]The Seven-League Scheme: Deep learning for large time step Monte Carlo simulations of stochastic differential equations
    Shuaiqiang Liu, Lech A. Grzelak, Cornelis W. Oosterlee
    http://arxiv.org/abs/2009.03202v1

    • [math.OC]Convergence Analysis of the Hessian Estimation Evolution Strategy
    Tobias Glasmachers, Oswin Krause
    http://arxiv.org/abs/2009.02732v1

    • [math.OC]Distributed Optimization, Averaging via ADMM, and Network Topology
    Guilherme França, José Bento
    http://arxiv.org/abs/2009.02604v1

    • [math.OC]Escaping Saddle Points in Ill-Conditioned Matrix Completion with a Scalable Second Order Method
    Christian Kümmerle, Claudio M. Verdun
    http://arxiv.org/abs/2009.02905v1

    • [math.OC]Nearly Bounded Regret of Re-solving Heuristics in Price-based Revenue Management
    Yining Wang
    http://arxiv.org/abs/2009.02861v1

    • [math.PR]An online learning approach to dynamic pricing and capacity sizing in service systems
    Xinyun Chen, Yunan Liu, Guiyu Hong
    http://arxiv.org/abs/2009.02911v1

    • [math.PR]Matched Queues with Matching Batch Pair (m, n)
    Heng-Li Liu, Quan-Lin Li, Chi Zhang
    http://arxiv.org/abs/2009.02742v1

    • [math.PR]New Upper Bounds for Trace Reconstruction
    Zachary Chase
    http://arxiv.org/abs/2009.03296v1

    • [math.PR]On estimation of quadratic variation for multivariate pure jump semimartingales
    Johannes Heiny, Mark Podolskij
    http://arxiv.org/abs/2009.02786v1

    • [math.PR]Positivity of Cumulative Sums for Multi-Index Function Components Explains the Lower Bound Formula in the Levin-Robbins-Leu Family of Sequential Subset Selection Procedures
    Bruce Levin, Cheng-Shiun Leu
    http://arxiv.org/abs/2009.02578v1

    • [math.ST]Admissible anytime-valid sequential inference must rely on nonnegative martingales
    Aaditya Ramdas, Johannes Ruf, Martin Larsson, Wouter Koolen
    http://arxiv.org/abs/2009.03167v1

    • [math.ST]False discovery rate control with e-values
    Ruodu Wang, Aaditya Ramdas
    http://arxiv.org/abs/2009.02824v1

    • [math.ST]Isotonic regression with unknown permutations: Statistics, computation, and adaptation
    Ashwin Pananjady, Richard J. Samworth
    http://arxiv.org/abs/2009.02609v1

    • [math.ST]Permutation Testing for Dependence in Time Series
    Joseph P. Romano, Marius A. Tirlea
    http://arxiv.org/abs/2009.03170v1

    • [physics.comp-ph]The role of feature space in atomistic learning
    Alexander Goscinski, Guillaume Fraux, Michele Ceriotti
    http://arxiv.org/abs/2009.02741v1

    • [physics.med-ph]Localization and classification of intracranialhemorrhages in CT data
    Jakub Nemcek, Roman Jakubicek, Jiri Chmelik
    http://arxiv.org/abs/2009.03046v1

    • [physics.plasm-ph]Deep Learning for the Analysis of Disruption Precursors based on Plasma Tomography
    Diogo R. Ferreira, Pedro J. Carvalho, Carlo Sozzi, Peter J. Lomas, JET Contributors
    http://arxiv.org/abs/2009.02708v1

    • [q-bio.NC]CalciumGAN: A Generative Adversarial Network Model for Synthesising Realistic Calcium Imaging Data of Neuronal Populations
    Bryan M. Li., Theoklitos Amvrosiadis, Nathalie Rochefort, Arno Onken
    http://arxiv.org/abs/2009.02707v1

    • [q-bio.NC]The Resolution Matrix for Visualizing Functional Network Connectivity
    Keith Dillon
    http://arxiv.org/abs/2009.03187v1

    • [q-bio.QM]Bayesian information-theoretic calibration of patient-specific radiotherapy sensitivity parameters for informing effective scanning protocols in cancer
    Heyrim Cho, Allison L. Lewis, Kathleen M. Storey
    http://arxiv.org/abs/2009.02620v1

    • [q-fin.ST]Capturing dynamics of post-earnings-announcement drift using genetic algorithm-optimised supervised learning
    Zhengxin Joseph Ye, Bjorn W. Schuller
    http://arxiv.org/abs/2009.03094v1

    • [stat.AP]An industry case of large-scale demand forecasting of hierarchical components
    Rodrigo Rivera-Castro, Ivan Nazarov, Yuke Xiang, Ivan Maksimov, Aleksandr Pletnev, Evgeny Burnaev
    http://arxiv.org/abs/2009.03262v1

    • [stat.AP]Bayesian shared-parameter models for analysing sardine fishing in the Mediterranean Sea
    Gabriel Calvo, Carmen Armero, Maria Grazia Pennino, Luigi Spezia
    http://arxiv.org/abs/2009.02992v1

    • [stat.AP]Evaluating the relative contribution of data sources in a Bayesian analysis with the application of estimating the size of hard to reach populations
    Jacob Parsons, Xiaoyue Niu, Le Bao
    http://arxiv.org/abs/2009.02372v1

    • [stat.AP]Identifying partners at sea on contrasting fisheries around the world
    Rocío Joo, Nicolas Bez, Marie-Pierre Etienne, Pablo Marin, Nicolas Goascoz, Jérôme Roux, Stéphanie Mahévas
    http://arxiv.org/abs/2009.02601v1

    • [stat.AP]Matching Bounds: How Choice of Matching AlgorithmImpacts Treatment Effects Estimates and What to Do about It
    Marco Morucci, Cynthia Rudin
    http://arxiv.org/abs/2009.02776v1

    • [stat.AP]Optimization of High-dimensional Simulation Models Using Synthetic Data
    Thomas Bartz-Beielstein, Eva Bartz, Frederik Rehbach, Olaf Mersmann
    http://arxiv.org/abs/2009.02781v1

    • [stat.AP]SARGDV: Efficient identification of groundwater-dependent vegetation using synthetic aperture radar
    Mason Terrett, Daniel Fryer, Tanya Doody, Hien Nguyen, Pascal Castellazzi
    http://arxiv.org/abs/2009.03129v1

    • [stat.AP]Structured Sparsity Modeling for Improved Multivariate Statistical Analysis based Fault Isolation
    Wei Chen, Jiusun Zeng, Xiaobin Xu, Shihua Luo
    http://arxiv.org/abs/2009.02528v1

    • [stat.AP]Suicide Risk Modeling with Uncertain Diagnostic Records
    Wenjie Wang, Chongliang Luo, Robert H. Aseltine, Fei Wang, Jun Yan, Kun Chen
    http://arxiv.org/abs/2009.02597v1

    • [stat.AP]Using multiple data streams to estimate and forecast SARS-CoV-2 transmission dynamics, with application to the virus spread in Orange County, California
    Jonathan Fintzi, Damon Bayer, Isaac Goldstein, Keith Lumbard, Emily Ricotta, Sarah Warner, Lindsay M. Busch, Jeffrey R. Strich, Daniel S. Chertow, Daniel M. Parker, Bernadette Boden-Albala, Alissa Dratch, Richard Chhuon, Nichole Quick, Matthew Zahn, Vladimir N. Minin
    http://arxiv.org/abs/2009.02654v1

    • [stat.ME]Anomaly Detection in Stationary Settings: A Permutation-Based Higher Criticism Approach
    Ivo V. Stoepker, Rui M. Castro, Ery Arias-Castro, Edwin van den Heuvel
    http://arxiv.org/abs/2009.03117v1

    • [stat.ME]Bootstrap p-values reduce type 1 error of the robust rank-order test of difference in medians
    Nirvik Sinha
    http://arxiv.org/abs/2009.02362v1

    • [stat.ME]Empirical Bayes methods for monitoring health care quality
    Hans C. van Houwelingen, Ronald Brand, Thomas A. Louis
    http://arxiv.org/abs/2009.03058v1

    • [stat.ME]Fairness in Risk Assessment Instruments: Post-Processing to Achieve Counterfactual Equalized Odds
    Alan Mishler, Edward H. Kennedy
    http://arxiv.org/abs/2009.02841v1

    • [stat.ME]Penalized Maximum Likelihood Estimator for Mixture of von Mises-Fisher Distributions
    Tin Lok James Ng
    http://arxiv.org/abs/2009.02921v1

    • [stat.ME]Simulating Name-like Vectors for Testing Large-scale Entity Resolution
    Samudra Herath, Matthew Roughan, Gary Glonek
    http://arxiv.org/abs/2009.03014v1

    • [stat.ML]Binary Classification as a Phase Separation Process
    Rafael Monteiro
    http://arxiv.org/abs/2009.02467v1

    • [stat.ML]Communication-efficient distributed eigenspace estimation
    Vasileios Charisopoulos, Austin R. Benson, Anil Damle
    http://arxiv.org/abs/2009.02436v1

    • [stat.ML]Estimation of Structural Causal Model via Sparsely Mixing Independent Component Analysis
    Kazuharu Harada, Hironori Fujisawa
    http://arxiv.org/abs/2009.03077v1

    • [stat.ML]Gradient-based Competitive Learning: Theory
    Giansalvo Cirrincione, Pietro Barbiero, Gabriele Ciravegna, Vincenzo Randazzo
    http://arxiv.org/abs/2009.02799v1

    • [stat.ML]Multilinear Common Component Analysis via Kronecker Product Representation
    Kohei Yoshikawa, Shuichi Kawano
    http://arxiv.org/abs/2009.02695v1

    • [stat.ML]Non-exponentially weighted aggregation: regret bounds for unbounded loss functions
    Pierre Alquier
    http://arxiv.org/abs/2009.03017v1

    • [stat.ML]Screening Rules and its Complexity for Active Set Identification
    Eugene Ndiaye, Olivier Fercoq, Joseph Salmon
    http://arxiv.org/abs/2009.02709v1

    • [stat.ML]Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces
    Hung Tran-The
    http://arxiv.org/abs/2009.02539v1

    • [stat.ML]Unfolding by Folding: a resampling approach to the problem of matrix inversion without actually inverting any matrix
    Pietro Vischia
    http://arxiv.org/abs/2009.02913v1