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