cs.AI - 人工智能
cs.CL - 计算与语言 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DL - 数字图书馆 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.MM - 多媒体 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 math.LO - 逻辑演算 math.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 physics.ao-ph - 大气和海洋物理 physics.med-ph - 医学物理学 physics.soc-ph - 物理学与社会 q-bio.QM - 定量方法 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习 • [cs.AI]Adapting a Kidney Exchange Algorithm to Align with Human Values • [cs.AI]Combining Experts’ Causal Judgments • [cs.AI]Combining the Causal Judgments of Experts with Possibly Different Focus Areas • [cs.AI]Creative Artificial Intelligence — Algorithms vs. humans in an incentivized writing competition • [cs.AI]Learning and Reasoning for Robot Dialog and Navigation Tasks • [cs.AI]Monte Carlo Inverse Folding • [cs.AI]Tackling the DMN Challenges with cDMN: a Tight Integration of DMN and constraint reasoning • [cs.AI]The Second Type of Uncertainty in Monte Carlo Tree Search • [cs.CL]A Large-Scale Multi-Document Summarization Dataset from the Wikipedia Current Events Portal • [cs.CL]Applying the Transformer to Character-level Transduction • [cs.CL]BERTweet: A pre-trained language model for English Tweets • [cs.CL]BlaBla: Linguistic Feature Extraction for Clinical Analysis in Multiple Languages • [cs.CL]Enhancing Word Embeddings with Knowledge Extracted from Lexical Resources • [cs.CL]Examining the State-of-the-Art in News Timeline Summarization • [cs.CL]GM-CTSC at SemEval-2020 Task 1: Gaussian Mixtures Cross Temporal Similarity Clustering • [cs.CL]Leveraging Graph to Improve Abstractive Multi-Document Summarization • [cs.CL]Positive emotions help rank negative reviews in e-commerce • [cs.CL]Sentence level estimation of psycholinguistic norms using joint multidimensional annotations • [cs.CV]Active Speakers in Context • [cs.CV]Automated Copper Alloy Grain Size Evaluation Using a Deep-learning CNN • [cs.CV]Classification of Industrial Control Systems screenshots using Transfer Learning • [cs.CV]Classifying Suspicious Content in Tor Darknet • [cs.CV]Compute-Bound and Low-Bandwidth Distributed 3D Graph-SLAM • [cs.CV]Contextual Residual Aggregation for Ultra High-Resolution Image Inpainting • [cs.CV]Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review • [cs.CV]Deep learning with 4D spatio-temporal data representations for OCT-based force estimation • [cs.CV]Discriminative Dictionary Design for Action Classification in Still Images and Videos • [cs.CV]Dynamic Refinement Network for Oriented and Densely Packed Object Detection • [cs.CV]InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs • [cs.CV]Intra- and Inter-Action Understanding via Temporal Action Parsing • [cs.CV]Label Efficient Visual Abstractions for Autonomous Driving • [cs.CV]Localizing Firearm Carriers by Identifying Human-Object Pairs • [cs.CV]Map Generation from Large Scale Incomplete and Inaccurate Data Labels • [cs.CV]On Evaluating Weakly Supervised Action Segmentation Methods • [cs.CV]Perceptual Hashing applied to Tor domains recognition • [cs.CV]Portrait Shadow Manipulation • [cs.CV]Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection • [cs.CV]Reducing Overlearning through Disentangled Representations by Suppressing Unknown Tasks • [cs.CV]Relevant Region Prediction for Crowd Counting • [cs.CV]Representation Learning with Fine-grained Patterns • [cs.CV]Rethinking Performance Estimation in Neural Architecture Search • [cs.CV]What makes for good views for contrastive learning • [cs.CY]Do we need a Contact Tracing App? • [cs.CY]PeopleTraffic: a common framework for harmonizing privacy and epidemic risks • [cs.DB]Unlocking New York City Crime Insights using Relational Database Embeddings • [cs.DC]BeepTrace: Blockchain-enabled Privacy-preserving Contact Tracing for COVID-19 Pandemic and Beyond • [cs.DC]Efficient Process-to-Node Mapping Algorithms for Stencil Computations • [cs.DC]Rational Consensus • [cs.DL]What country, university or research institute, performed the best on COVID-19? Bibliometric analysis of scientific literature • [cs.HC]Benchmarking of a software stack for autonomous racing against a professional human race driver • [cs.IR]Context-Aware Learning to Rank with Self-Attention • [cs.IR]FashionBERT: Text and Image Matching with Adaptive Loss for Cross-modal Retrieval • [cs.IR]GLEAKE: Global and Local Embedding Automatic Keyphrase Extraction • [cs.IR]M2GRL: A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender Systems • [cs.IR]Neural Collaborative Filtering vs. Matrix Factorization Revisited • [cs.IT]Cell-Free Massive MIMO with Underlaid D2D Communications and Low Resolution ADCs • [cs.IT]Data-Importance Aware Radio Resource Allocation: Wireless Communication Helps Machine Learning • [cs.IT]Fast Decoding of Codes in the Rank, Subspace, and Sum-Rank Metric • [cs.IT]Predictor Antenna Systems: Exploiting Channel State Information for Vehicle Communications • [cs.IT]Safeguarding MIMO Communications with Reconfigurable Metasurfaces and Artificial Noise • [cs.IT]Unveiling the Importance of SIC in NOMA Systems: Part I — State of the Art and Recent Findings • [cs.IT]Unveiling the Importance of SIC in NOMA Systems: Part II: New Results and Future Directions • [cs.IT]User Activity Detection and Channel Estimation for Grant-Free Random Access in LEO Satellite-Enabled Internet-of-Things • [cs.LG]$p$-Norm Flow Diffusion for Local Graph Clustering • [cs.LG]A Novel Meta Learning Framework for Feature Selection using Data Synthesis and Fuzzy Similarity • [cs.LG]A reinforcement learning based decision support system in textile manufacturing process • [cs.LG]Accounting for Input Noise in Gaussian Process Parameter Retrieval • [cs.LG]An Incremental Clustering Method for Anomaly Detection in Flight Data • [cs.LG]An LSTM approach to Predict Migration based on Google Trends • [cs.LG]Anomaly Detection in Video Games • [cs.LG]Batch Decorrelation for Active Metric Learning • [cs.LG]Best Arm Identification in Spectral Bandits • [cs.LG]BiQGEMM: Matrix Multiplication with Lookup Table For Binary-Coding-based Quantized DNNs • [cs.LG]DisCoveR: Accurate & Efficient Discovery of Declarative Process Models • [cs.LG]Early Classification of Time Series. Cost-based Optimization Criterion and Algorithms • [cs.LG]Experience Augmentation: Boosting and Accelerating Off-Policy Multi-Agent Reinforcement Learning • [cs.LG]Fair Outlier Detection • [cs.LG]Feature Purification: How Adversarial Training Performs Robust Deep Learning • [cs.LG]Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise • [cs.LG]Graph Structure Learning for Robust Graph Neural Networks • [cs.LG]Hidden Markov Models and their Application for Predicting Failure Events • [cs.LG]Learning Representations using Spectral-Biased Random Walks on Graphs • [cs.LG]Mirror Descent Policy Optimization • [cs.LG]Multitask Learning with Single Gradient Step Update for Task Balancing • [cs.LG]Network On Network for Tabular Data Classification in Real-world Applications • [cs.LG]Neural Ordinary Differential Equation based Recurrent Neural Network Model • [cs.LG]Reinforcement Learning for Variable Selection in a Branch and Bound Algorithm • [cs.LG]Risk of Training Diagnostic Algorithms on Data with Demographic Bias • [cs.LG]Self-Updating Models with Error Remediation • [cs.LG]The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models • [cs.LG]The Effects of Randomness on the Stability of Node Embeddings • [cs.LG]Uncertainty Quantification Using Neural Networks for Molecular Property Prediction • [cs.LG]Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere • [cs.LG]Understanding Negative Sampling in Graph Representation Learning • [cs.MM]A Modified Fourier-Mellin Approach for Source Device Identification on Stabilized Videos • [cs.MM]Webpage Segmentation for Extracting Images and Their Surrounding Contextual Information • [cs.RO]Collision-free Trajectory Planning for Autonomous Surface Vehicle • [cs.RO]Development of a Shape-memorable Adaptive Pin Array Fixture • [cs.RO]Differential Mapping Spiking Neural Network for Sensor-Based Robot Control • [cs.RO]Learning natural locomotion behaviors for humanoid robots using human knowledge • [cs.RO]Model Predictive Instantaneous Safety Metric for Evaluation of Automated Driving Systems • [cs.SE]Behavioral Software Engineering: Methodological Introduction to Psychometrics • [cs.SE]Representation of Developer Expertise in Open Source Software • [cs.SI]A Clarified Typology of Core-Periphery Structure in Networks • [cs.SI]A Computational Analysis of Polarization on Indian and Pakistani Social Media • [cs.SI]Characterizing networks of propaganda on Twitter: a case study • [cs.SI]Embeddings-Based Clustering for Target Specific Stances: The Case of a Polarized Turkey • [cs.SI]Every Colour You Are: Stance Prediction and Turnaround in Controversial Issues • [cs.SI]GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Detection • [cs.SI]Heterogeneous Susceptibilities in Social Influence Models • [cs.SI]Images and Misinformation in Political Groups: Evidence from WhatsApp in India • [cs.SI]Motif Discovery Algorithms in Static and Temporal Networks: A Survey • [cs.SI]The Many Faces of Balance: Multilevel Structural Evaluation of Signed Directed Social Networks • [cs.SI]Towards Characterizing the COVID-19 Awareness on Twitter • [cs.SI]Weibo-COV: A Large-Scale COVID-19 Social Media Dataset from Webio • [econ.EM]Treatment recommendation with distributional targets • [eess.AS]A Comparison of Label-Synchronous and Frame-Synchronous End-to-End Models for Speech Recognition • [eess.AS]A Further Study of Unsupervised Pre-training for Transformer Based Speech Recognition • [eess.AS]Early Stage LM Integration Using Local and Global Log-Linear Combination • [eess.AS]End-to-End Speaker Diarization for an Unknown Number of Speakers with Encoder-Decoder Based Attractors • [eess.AS]Exploring Transformers for Large-Scale Speech Recognition • [eess.AS]Investigation of Large-Margin Softmax in Neural Language Modeling • [eess.AS]PyChain: A Fully Parallelized PyTorch Implementation of LF-MMI for End-to-End ASR • [eess.AS]Relative Positional Encoding for Speech Recognition and Direct Translation • [eess.IV]A Statistical Model for Imaging Systems • [eess.IV]Adapting JPEG XS gains and priorities to tasks and contents • [eess.IV]An Innovative Approach to Determine Rebar Depth and Size by Comparing GPR Data with a Theoretical Database • [eess.IV]Attention-based network for low-light image enhancement • [eess.IV]AutoML Segmentation for 3D Medical Image Data: Contribution to the MSD Challenge 2018 • [eess.IV]Data Consistent CT Reconstruction from Insufficient Data with Learned Prior Images • [eess.IV]Iterative Network for Image Super-Resolution • [eess.IV]Local semi-supervised approach to brain tissue classification in child brain MRI • [eess.IV]Lung Segmentation from Chest X-rays using Variational Data Imputation • [eess.SP]Federated Deep Learning Framework For Hybrid Beamforming in mm-Wave Massive MIMO • [math.LO]On embedding Lambek calculus into commutative categorial grammars • [math.NA]Inverse problems with second-order Total Generalized Variation constraints • [math.NA]The Random Feature Model for Input-Output Maps between Banach Spaces • [math.OC]Lasso formulation of the shortest path problem • [math.ST]Exponential ergodicity of mirror-Langevin diffusions • [math.ST]Functional delta residuals and applications to functional effect sizes • [math.ST]Inference on the Change Point in High Dimensional Dynamic Graphical Models • [math.ST]Model Repair: Robust Recovery of Over-Parameterized Statistical Models • [math.ST]Revisiting Concentration of Missing Mass • [math.ST]Smooth Distribution Function Estimation for Lifetime Distributions using Szasz-Mirakyan Operators • [physics.ao-ph]Estimating volcanic ash emissions using retrieved satellite ash columns and inverse ash transport modelling • [physics.med-ph]Self-supervised Dynamic CT Perfusion Image Denoising with Deep Neural Networks • [physics.soc-ph]Empowering Urban Governance through Urban Science: Multi-scale Dynamics of Urban Systems Worldwide • [physics.soc-ph]Phase transitions and social distancing control measures for SARS-CoV-2 on small world networks • [physics.soc-ph]Spatial Heterogeneity Can Lead to Substantial Local Variations in COVID-19 Timing and Severity • [q-bio.QM]Interactive exploration of population scale pharmacoepidemiology datasets • [stat.AP]A Critical Assessment of Some Recent Work on COVID-19 • [stat.AP]A Route to School Informational Intervention for Air Pollution Exposure Reduction • [stat.AP]Additive stacking for disaggregate electricity demand forecasting • [stat.AP]Balancing spatial and non-spatial variation in varying coefficient modeling: a remedy for spurious correlation • [stat.AP]Uncertainty representation for early phase clinical test evaluations: a case study • [stat.ME]A Toolbox for the Radial and Angular Marginalization of Bivariate Normal Distributions • [stat.ME]Dyadic Reciprocity as a Function of Covariates • [stat.ME]Dynamic mixtures of finite mixtures and telescoping sampling • [stat.ME]Matching methods for obtaining survival functions to estimate the effect of a time-dependent treatment • [stat.ME]On a family of discrete log-symmetric distributions • [stat.ME]On the use of cross-validation for the calibration of the tuning parameter in the adaptive lasso • [stat.ME]Simultaneous Confidence Tubes for Comparison of Several Multivariate Linear Regression Models • [stat.ME]Tables of Quantiles of the Distribution of the Empirical Chiral Index in the Case of the Uniform Law and in the Case of the Normal Law • [stat.ME]The Impact of Unmeasured Within- and Between-Cluster Confounding on the Bias of Effect Estimators from Fixed Effect, Mixed effect and Instrumental Variable Models • [stat.ME]The hidden waves in the ECG uncovered: A multicomponent model for the Cardiac Rhythm • [stat.ML]Informative Path Planning for Anomaly Detection in Environment Exploration and Monitoring • [stat.ML]Learning Undirected Graphs in Financial Markets • [stat.ML]Nonparametric Score Estimators • [stat.ML]ReLU Code Space: A Basis for Rating Network Quality Besides Accuracy • [stat.ML]Riemannian geometry for Compound Gaussian distributions: application to recursive change detection • [stat.ML]Tessellated Wasserstein Auto-Encoders • [stat.ML]The Inverse G-Wishart Distribution and Variational Message Passing ····································· • [cs.AI]Adapting a Kidney Exchange Algorithm to Align with Human Values Rachel Freedman, Jana Schaich Borg, Walter Sinnott-Armstrong, John P. Dickerson, Vincent Conitzer http://arxiv.org/abs/2005.09755v1 • [cs.AI]Combining Experts’ Causal Judgments Dalal Alrajeh, Hana Chockler, Joseph Y. Halpern http://arxiv.org/abs/2005.10180v1 • [cs.AI]Combining the Causal Judgments of Experts with Possibly Different Focus Areas Meir Friedenberg, Joseph Y. Halpern http://arxiv.org/abs/2005.10131v1 • [cs.AI]Creative Artificial Intelligence — Algorithms vs. humans in an incentivized writing competition Nils Köbis, Luca Mossink http://arxiv.org/abs/2005.09980v1 • [cs.AI]Learning and Reasoning for Robot Dialog and Navigation Tasks Keting Lu, Shiqi Zhang, Peter Stone, Xiaoping Chen http://arxiv.org/abs/2005.09833v1 • [cs.AI]Monte Carlo Inverse Folding Tristan Cazenave, Thomas Fournier http://arxiv.org/abs/2005.09961v1 • [cs.AI]Tackling the DMN Challenges with cDMN: a Tight Integration of DMN and constraint reasoning Bram Aerts, Simon Vandevelde, Joost Vennekens http://arxiv.org/abs/2005.09998v1 • [cs.AI]The Second Type of Uncertainty in Monte Carlo Tree Search Thomas M Moerland, Joost Broekens, Aske Plaat, Catholijn M Jonker http://arxiv.org/abs/2005.09645v1 • [cs.CL]A Large-Scale Multi-Document Summarization Dataset from the Wikipedia Current Events Portal Demian Gholipour Ghalandari, Chris Hokamp, Nghia The Pham, John Glover, Georgiana Ifrim http://arxiv.org/abs/2005.10070v1 • [cs.CL]Applying the Transformer to Character-level Transduction Shijie Wu, Ryan Cotterell, Mans Hulden http://arxiv.org/abs/2005.10213v1 • [cs.CL]BERTweet: A pre-trained language model for English Tweets Dat Quoc Nguyen, Thanh Vu, Anh Tuan Nguyen http://arxiv.org/abs/2005.10200v1 • [cs.CL]BlaBla: Linguistic Feature Extraction for Clinical Analysis in Multiple Languages Abhishek Shivkumar, Jack Weston, Raphael Lenain, Emil Fristed http://arxiv.org/abs/2005.10219v1 • [cs.CL]Enhancing Word Embeddings with Knowledge Extracted from Lexical Resources Magdalena Biesialska, Bardia Rafieian, Marta R. Costa-jussà http://arxiv.org/abs/2005.10048v1 • [cs.CL]Examining the State-of-the-Art in News Timeline Summarization Demian Gholipour Ghalandari, Georgiana Ifrim http://arxiv.org/abs/2005.10107v1 • [cs.CL]GM-CTSC at SemEval-2020 Task 1: Gaussian Mixtures Cross Temporal Similarity Clustering Pierluigi Cassotti, Annalina Caputo, Marco Polignano, Pierpaolo Basile http://arxiv.org/abs/2005.09946v1 • [cs.CL]Leveraging Graph to Improve Abstractive Multi-Document Summarization Wei Li, Xinyan Xiao, Jiachen Liu, Hua Wu, Haifeng Wang, Junping Du http://arxiv.org/abs/2005.10043v1 • [cs.CL]Positive emotions help rank negative reviews in e-commerce Di Weng, Jichang Zhao http://arxiv.org/abs/2005.09837v1 • [cs.CL]Sentence level estimation of psycholinguistic norms using joint multidimensional annotations Anil Ramakrishna, Shrikanth Narayanan http://arxiv.org/abs/2005.10232v1 • [cs.CV]Active Speakers in Context Juan Leon Alcazar, Fabian Caba Heilbron, Long Mai, Federico Perazzi, Joon-Young Lee, Pablo Arbelaez, Bernard Ghanem http://arxiv.org/abs/2005.09812v1 • [cs.CV]Automated Copper Alloy Grain Size Evaluation Using a Deep-learning CNN George S. Baggs, Paul Guerrier, Andrew Loeb, Jason C. Jones http://arxiv.org/abs/2005.09634v1 • [cs.CV]Classification of Industrial Control Systems screenshots using Transfer Learning Pablo Blanco Medina, Eduardo Fidalgo Fernandez, Enrique Alegre, Francisco Jáñez Martino, Roberto A. Vasco-Carofilis, Víctor Fidalgo Villar http://arxiv.org/abs/2005.10098v1 • [cs.CV]Classifying Suspicious Content in Tor Darknet Eduardo Fidalgo Fernandez, Roberto Andrés Vasco Carofilis, Francisco Jáñez Martino, Pablo Blanco Medina http://arxiv.org/abs/2005.10086v1 • [cs.CV]Compute-Bound and Low-Bandwidth Distributed 3D Graph-SLAM Jincheng Zhang, Andrew R. Willis, Jamie Godwin http://arxiv.org/abs/2005.10222v1 • [cs.CV]Contextual Residual Aggregation for Ultra High-Resolution Image Inpainting Zili Yi, Qiang Tang, Shekoofeh Azizi, Daesik Jang, Zhan Xu http://arxiv.org/abs/2005.09704v1 • [cs.CV]Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review Ying Li, Lingfei Ma, Zilong Zhong, Fei Liu, Dongpu Cao, Jonathan Li, Michael A. Chapman http://arxiv.org/abs/2005.09830v1 • [cs.CV]Deep learning with 4D spatio-temporal data representations for OCT-based force estimation Nils Gessert, Marcel Bengs, Matthias Schlüter, Alexander Schlaefer http://arxiv.org/abs/2005.10033v1 • [cs.CV]Discriminative Dictionary Design for Action Classification in Still Images and Videos Abhinaba Roy, Biplab Banerjee http://arxiv.org/abs/2005.10149v1 • [cs.CV]Dynamic Refinement Network for Oriented and Densely Packed Object Detection Xingjia Pan, Yuqiang Ren, Kekai Sheng, Weiming Dong, Haolei Yuan, Xiaowei Guo, Chongyang Ma, Changsheng Xu http://arxiv.org/abs/2005.09973v1 • [cs.CV]InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs Yujun Shen, Ceyuan Yang, Xiaoou Tang, Bolei Zhou http://arxiv.org/abs/2005.09635v1 • [cs.CV]Intra- and Inter-Action Understanding via Temporal Action Parsing Dian Shao, Yue Zhao, Bo Dai, Dahua Lin http://arxiv.org/abs/2005.10229v1 • [cs.CV]Label Efficient Visual Abstractions for Autonomous Driving Aseem Behl, Kashyap Chitta, Aditya Prakash, Eshed Ohn-Bar, Andreas Geiger http://arxiv.org/abs/2005.10091v1 • [cs.CV]Localizing Firearm Carriers by Identifying Human-Object Pairs Abdul Basit, Muhammad Akhtar Munir, Mohsen Ali, Arif Mahmood http://arxiv.org/abs/2005.09329v2 • [cs.CV]Map Generation from Large Scale Incomplete and Inaccurate Data Labels Rui Zhang, Conrad Albrecht, Wei Zhang, Xiaodong Cui, Ulrich Finkler, David Kung, Siyuan Lu http://arxiv.org/abs/2005.10053v1 • [cs.CV]On Evaluating Weakly Supervised Action Segmentation Methods Yaser Souri, Alexander Richard, Luca Minciullo, Juergen Gall http://arxiv.org/abs/2005.09743v1 • [cs.CV]Perceptual Hashing applied to Tor domains recognition Rubel Biswas, Roberto A. Vasco-Carofilis, Eduardo Fidalgo Fernandez, Francisco Jáñez Martino, Pablo Blanco Medina http://arxiv.org/abs/2005.10090v1 • [cs.CV]Portrait Shadow Manipulation Xuaner Cecilia Zhang, Jonathan T. Barron, Yun-Ta Tsai, Rohit Pandey, Xiuming Zhang, Ren Ng, David E. Jacobs http://arxiv.org/abs/2005.08925v2 • [cs.CV]Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection Alex Bewley, Pei Sun, Thomas Mensink, Dragomir Anguelov, Cristian Sminchisescu http://arxiv.org/abs/2005.09927v1 • [cs.CV]Reducing Overlearning through Disentangled Representations by Suppressing Unknown Tasks Naveen Panwar, Tarun Tater, Anush Sankaran, Senthil Mani http://arxiv.org/abs/2005.10220v1 • [cs.CV]Relevant Region Prediction for Crowd Counting Xinya Chen, Yanrui Bin, Changxin Gao, Nong Sang, Hao Tang http://arxiv.org/abs/2005.09816v1 • [cs.CV]Representation Learning with Fine-grained Patterns Yuanhong Xu, Qi Qian, Hao Li, Rong Jin, Juhua Hu http://arxiv.org/abs/2005.09681v1 • [cs.CV]Rethinking Performance Estimation in Neural Architecture Search Xiawu Zheng, Rongrong Ji, Qiang Wang, Qixiang Ye, Zhenguo Li, Yonghong Tian, Qi Tian http://arxiv.org/abs/2005.09917v1 • [cs.CV]What makes for good views for contrastive learning Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola http://arxiv.org/abs/2005.10243v1 • [cs.CY]Do we need a Contact Tracing App? Leonardo Maccari, Valeria Cagno http://arxiv.org/abs/2005.10187v1 • [cs.CY]PeopleTraffic: a common framework for harmonizing privacy and epidemic risks Ruggero Caravita http://arxiv.org/abs/2005.10061v1 • [cs.DB]Unlocking New York City Crime Insights using Relational Database Embeddings Apoorva Nitsure, Rajesh Bordawekar, Jose Neves http://arxiv.org/abs/2005.09617v2 • [cs.DC]BeepTrace: Blockchain-enabled Privacy-preserving Contact Tracing for COVID-19 Pandemic and Beyond Hao Xu, Lei Zhang, Oluwakayode Onireti, Yang Fang, William Bill Buchanan, Muhammad Ali Imran http://arxiv.org/abs/2005.10103v1 • [cs.DC]Efficient Process-to-Node Mapping Algorithms for Stencil Computations Sascha Hunold, Konrad von Kirchbach, Markus Lehr, Christian Schulz, Jesper Larsson Träff http://arxiv.org/abs/2005.09521v2 • [cs.DC]Rational Consensus Joseph Y. Halpern, Xavier Vilaca http://arxiv.org/abs/2005.10141v1 • [cs.DL]What country, university or research institute, performed the best on COVID-19? Bibliometric analysis of scientific literature Petar Radanliev, David De Roure, Rob Walton, Max Van Kleek, Omar Santos, Rafael Mantilla Montalvo, La Treall Maddox http://arxiv.org/abs/2005.10082v1 • [cs.HC]Benchmarking of a software stack for autonomous racing against a professional human race driver Leonhard Hermansdorfer, Johannes Betz, Markus Lienkamp http://arxiv.org/abs/2005.10044v1 • [cs.IR]Context-Aware Learning to Rank with Self-Attention Przemysław Pobrotyn, Tomasz Bartczak, Mikołaj Synowiec, Radosław Białobrzeski, Jarosław Bojar http://arxiv.org/abs/2005.10084v1 • [cs.IR]FashionBERT: Text and Image Matching with Adaptive Loss for Cross-modal Retrieval Dehong Gao, Linbo Jin, Ben Chen, Minghui Qiu, Yi Wei, Yi Hu, Hao Wang http://arxiv.org/abs/2005.09801v1 • [cs.IR]GLEAKE: Global and Local Embedding Automatic Keyphrase Extraction Javad Rafiei Asl, Juan M. Banda http://arxiv.org/abs/2005.09740v1 • [cs.IR]M2GRL: A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender Systems Menghan Wang, Yujie Lin, Guli Lin, Keping Yang, Xiao-ming Wu http://arxiv.org/abs/2005.10110v1 • [cs.IR]Neural Collaborative Filtering vs. Matrix Factorization Revisited Steffen Rendle, Walid Krichene, Li Zhang, John Anderson http://arxiv.org/abs/2005.09683v1 • [cs.IT]Cell-Free Massive MIMO with Underlaid D2D Communications and Low Resolution ADCs Hamed Masoumi, Mohammad Javad Emadi, Stefano Buzzi http://arxiv.org/abs/2005.10068v1 • [cs.IT]Data-Importance Aware Radio Resource Allocation: Wireless Communication Helps Machine Learning Yuan Liu, Zhi Zeng, Weijun Tang, Fangjiong Chen http://arxiv.org/abs/2005.09868v1 • [cs.IT]Fast Decoding of Codes in the Rank, Subspace, and Sum-Rank Metric Hannes Bartz, Thomas Jerkovits, Sven Puchinger, Johan Rosenkilde http://arxiv.org/abs/2005.09916v1 • [cs.IT]Predictor Antenna Systems: Exploiting Channel State Information for Vehicle Communications Hao Guo http://arxiv.org/abs/2005.09758v1 • [cs.IT]Safeguarding MIMO Communications with Reconfigurable Metasurfaces and Artificial Noise George C. Alexandropoulos, Konstantinos Katsanos, Miaowen Wen, Daniel B. da Costa http://arxiv.org/abs/2005.10062v1 • [cs.IT]Unveiling the Importance of SIC in NOMA Systems: Part I — State of the Art and Recent Findings Z. Ding, R. Schober, H. V. Poor http://arxiv.org/abs/2005.10215v1 • [cs.IT]Unveiling the Importance of SIC in NOMA Systems: Part II: New Results and Future Directions Z. Ding, R. Schober, H. V. Poor http://arxiv.org/abs/2005.10217v1 • [cs.IT]User Activity Detection and Channel Estimation for Grant-Free Random Access in LEO Satellite-Enabled Internet-of-Things Zhaoji Zhang, Ying Li, Chongwen Huang, Qinghua Guo, Lei Liu, Chau Yuen, Yong Liang Guan http://arxiv.org/abs/2005.09826v1 • [cs.LG]$p$-Norm Flow Diffusion for Local Graph Clustering Shenghao Yang, Di Wang, Kimon Fountoulakis http://arxiv.org/abs/2005.09810v1 • [cs.LG]A Novel Meta Learning Framework for Feature Selection using Data Synthesis and Fuzzy Similarity Zixiao Shen, Xin Chen, Jonathan M. Garibaldi http://arxiv.org/abs/2005.09856v1 • [cs.LG]A reinforcement learning based decision support system in textile manufacturing process Zhenglei He, Kim Phuc Tran, Sébastien Thomassey, Xianyi Zeng, Changhai Yi http://arxiv.org/abs/2005.09867v1 • [cs.LG]Accounting for Input Noise in Gaussian Process Parameter Retrieval J. Emmanuel Johnson, Valero Laparra, Gustau Camps-Valls http://arxiv.org/abs/2005.09907v1 • [cs.LG]An Incremental Clustering Method for Anomaly Detection in Flight Data Weizun Zhao, Lishuai Li, Sameer Alam, Yanjun Wang http://arxiv.org/abs/2005.09874v1 • [cs.LG]An LSTM approach to Predict Migration based on Google Trends Nicolas Golenvaux, Pablo Gonzalez Alvarez, Harold Silvère Kiossou, Pierre Schaus http://arxiv.org/abs/2005.09902v1 • [cs.LG]Anomaly Detection in Video Games Benedict Wilkins, Chris Watkins, Kostas Stathis http://arxiv.org/abs/2005.10211v1 • [cs.LG]Batch Decorrelation for Active Metric Learning Priyadarshini K, Ritesh Goru, Siddhartha Chaudhuri, Subhasis Chaudhuri http://arxiv.org/abs/2005.10008v1 • [cs.LG]Best Arm Identification in Spectral Bandits Tomáš Kocák, Aurélien Garivier http://arxiv.org/abs/2005.09841v1 • [cs.LG]BiQGEMM: Matrix Multiplication with Lookup Table For Binary-Coding-based Quantized DNNs Yongkweon Jeon, Baeseong Park, Se Jung Kwon, Byeongwook Kim, Jeongin Yun, Dongsoo Lee http://arxiv.org/abs/2005.09904v1 • [cs.LG]DisCoveR: Accurate & Efficient Discovery of Declarative Process Models Christoffer Olling Back, Tijs Slaats, Thomas Troels Hildebrandt, Morten Marquard http://arxiv.org/abs/2005.10085v1 • [cs.LG]Early Classification of Time Series. Cost-based Optimization Criterion and Algorithms Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Asma Dachraoui http://arxiv.org/abs/2005.09945v1 • [cs.LG]Experience Augmentation: Boosting and Accelerating Off-Policy Multi-Agent Reinforcement Learning Zhenhui Ye, Yining Chen, Guanghua Song, Bowei Yang, Shen Fan http://arxiv.org/abs/2005.09453v2 • [cs.LG]Fair Outlier Detection Deepak P, Savitha Sam Abraham http://arxiv.org/abs/2005.09900v1 • [cs.LG]Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu, Yuanzhi Li http://arxiv.org/abs/2005.10190v1 • [cs.LG]Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise Yue Wang, Shaofeng Zou http://arxiv.org/abs/2005.10175v1 • [cs.LG]Graph Structure Learning for Robust Graph Neural Networks Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang http://arxiv.org/abs/2005.10203v1 • [cs.LG]Hidden Markov Models and their Application for Predicting Failure Events Paul Hofmann, Zaid Tashman http://arxiv.org/abs/2005.09971v1 • [cs.LG]Learning Representations using Spectral-Biased Random Walks on Graphs Charu Sharma, Jatin Chauhan, Manohar Kaul http://arxiv.org/abs/2005.09752v1 • [cs.LG]Mirror Descent Policy Optimization Manan Tomar, Lior Shani, Yonathan Efroni, Mohammad Ghavamzadeh http://arxiv.org/abs/2005.09814v1 • [cs.LG]Multitask Learning with Single Gradient Step Update for Task Balancing Sungjae Lee, Youngdoo Son http://arxiv.org/abs/2005.09910v1 • [cs.LG]Network On Network for Tabular Data Classification in Real-world Applications Yuanfei Luo, Hao Zhou, Weiwei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang http://arxiv.org/abs/2005.10114v1 • [cs.LG]Neural Ordinary Differential Equation based Recurrent Neural Network Model Mansura Habiba, Barak A. Pearlmutter http://arxiv.org/abs/2005.09807v1 • [cs.LG]Reinforcement Learning for Variable Selection in a Branch and Bound Algorithm Marc Etheve, Zacharie Alès, Côme Bissuel, Olivier Juan, Safia Kedad-Sidhoum http://arxiv.org/abs/2005.10026v1 • [cs.LG]Risk of Training Diagnostic Algorithms on Data with Demographic Bias Samaneh Abbasi-Sureshjani, Ralf Raumanns, Britt E. J. Michels, Gerard Schouten, Veronika Cheplygina http://arxiv.org/abs/2005.10050v1 • [cs.LG]Self-Updating Models with Error Remediation Justin E. Doak, Michael R. Smith, Joey B. Ingram http://arxiv.org/abs/2005.09787v1 • [cs.LG]The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models Stephan Rabanser, Tim Januschowski, Valentin Flunkert, David Salinas, Jan Gasthaus http://arxiv.org/abs/2005.10111v1 • [cs.LG]The Effects of Randomness on the Stability of Node Embeddings Tobias Schumacher, Hinrikus Wolf, Martin Ritzert, Florian Lemmerich, Jan Bachmann, Florian Frantzen, Max Klabunde, Martin Grohe, Markus Strohmaier http://arxiv.org/abs/2005.10039v1 • [cs.LG]Uncertainty Quantification Using Neural Networks for Molecular Property Prediction Lior Hirschfeld, Kyle Swanson, Kevin Yang, Regina Barzilay, Connor W. Coley http://arxiv.org/abs/2005.10036v1 • [cs.LG]Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere Tongzhou Wang, Phillip Isola http://arxiv.org/abs/2005.10242v1 • [cs.LG]Understanding Negative Sampling in Graph Representation Learning Zhen Yang, Ming Ding, Chang Zhou, Hongxia Yang, Jingren Zhou, Jie Tang http://arxiv.org/abs/2005.09863v1 • [cs.MM]A Modified Fourier-Mellin Approach for Source Device Identification on Stabilized Videos Sara Mandelli, Fabrizio Argenti, Paolo Bestagini, Massimo Iuliani, Alessandro Piva, Stefano Tubaro http://arxiv.org/abs/2005.09984v1 • [cs.MM]Webpage Segmentation for Extracting Images and Their Surrounding Contextual Information F. Fauzi, H. J. Long, M. Belkhatir http://arxiv.org/abs/2005.09639v1 • [cs.RO]Collision-free Trajectory Planning for Autonomous Surface Vehicle Licheng Wen, Jiaqing Yan, Xuemeng Yang, Yong Liu, Yong Gu http://arxiv.org/abs/2005.09857v1 • [cs.RO]Development of a Shape-memorable Adaptive Pin Array Fixture Peihao Shi, Zhengtao Hu, Kazuyuki Nagata, Weiwei Wan, Yukiyasu Domae, Kensuke Harada http://arxiv.org/abs/2005.09968v1 • [cs.RO]Differential Mapping Spiking Neural Network for Sensor-Based Robot Control Omar Zahra, Silvia Tolu, David Navarro-Alarcon http://arxiv.org/abs/2005.10017v1 • [cs.RO]Learning natural locomotion behaviors for humanoid robots using human knowledge Chuanyu Yang, Kai Yuan, Shuai Heng, Taku Komura, Zhibin Li http://arxiv.org/abs/2005.10195v1 • [cs.RO]Model Predictive Instantaneous Safety Metric for Evaluation of Automated Driving Systems Bowen Weng, Sughosh J. Rao, Eeshan Deosthale, Scott Schnelle, Frank Barickman http://arxiv.org/abs/2005.09999v1 • [cs.SE]Behavioral Software Engineering: Methodological Introduction to Psychometrics Daniel Graziotin, Per Lenberg, Robert Feldt, Stefan Wagner http://arxiv.org/abs/2005.09959v1 • [cs.SE]Representation of Developer Expertise in Open Source Software Tapajit Dey, Andrey Karnauch, Audris Mockus http://arxiv.org/abs/2005.10176v1 • [cs.SI]A Clarified Typology of Core-Periphery Structure in Networks Ryan J. Gallagher, Jean-Gabriel Young, Brooke Foucault Welles http://arxiv.org/abs/2005.10191v1 • [cs.SI]A Computational Analysis of Polarization on Indian and Pakistani Social Media Aman Tyagi, Anjalie Field, Priyank Lathwal, Yulia Tsvetkov, Kathleen M. Carley http://arxiv.org/abs/2005.09803v1 • [cs.SI]Characterizing networks of propaganda on Twitter: a case study Stefano Guarino, Noemi Trino, Alessandro Celestini, Alessandro Chessa, Gianni Riotta http://arxiv.org/abs/2005.10004v1 • [cs.SI]Embeddings-Based Clustering for Target Specific Stances: The Case of a Polarized Turkey Ammar Rashed, Mucahid Kutlu, Kareem Darwish, Tamer Elsayed, Cansın Bayrak http://arxiv.org/abs/2005.09649v1 • [cs.SI]Every Colour You Are: Stance Prediction and Turnaround in Controversial Issues Eduardo Graells-Garrido, Ricardo Baeza-Yates, Mounia Lalmas http://arxiv.org/abs/2005.10019v1 • [cs.SI]GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Detection Shijie Zhang, Hongzhi Yin, Tong Chen, Quoc Viet Nguyen Hung, Zi Huang, Lizhen Cui http://arxiv.org/abs/2005.10150v1 • [cs.SI]Heterogeneous Susceptibilities in Social Influence Models Daniel K. Sewell http://arxiv.org/abs/2005.09996v1 • [cs.SI]Images and Misinformation in Political Groups: Evidence from WhatsApp in India Kiran Garimella, Dean Eckles http://arxiv.org/abs/2005.09784v1 • [cs.SI]Motif Discovery Algorithms in Static and Temporal Networks: A Survey Ali Jazayeri, Christopher C. Yang http://arxiv.org/abs/2005.09721v1 • [cs.SI]The Many Faces of Balance: Multilevel Structural Evaluation of Signed Directed Social Networks Samin Aref, Ly Dinh, Rezvaneh Rezapour, Jana Diesner http://arxiv.org/abs/2005.09925v1 • [cs.SI]Towards Characterizing the COVID-19 Awareness on Twitter Muhammad Saad, Muhammad Hassan, Fareed Zaffar http://arxiv.org/abs/2005.08379v2 • [cs.SI]Weibo-COV: A Large-Scale COVID-19 Social Media Dataset from Webio Yong Hu, Heyan Huang, Anfan Chen, Xian-Ling Mao http://arxiv.org/abs/2005.09174v2 • [econ.EM]Treatment recommendation with distributional targets Anders Bredahl Kock, David Preinerstorfer, Bezirgen Veliyev http://arxiv.org/abs/2005.09717v1 • [eess.AS]A Comparison of Label-Synchronous and Frame-Synchronous End-to-End Models for Speech Recognition Linhao Dong, Cheng Yi, Jianzong Wang, Shiyu Zhou, Shuang Xu, Xueli Jia, Bo Xu http://arxiv.org/abs/2005.10113v1 • [eess.AS]A Further Study of Unsupervised Pre-training for Transformer Based Speech Recognition Dongwei Jiang, Wubo Li, Ruixiong Zhang, Miao Cao, Ne Luo, Yang Han, Wei Zou, Xiangang Li http://arxiv.org/abs/2005.09862v1 • [eess.AS]Early Stage LM Integration Using Local and Global Log-Linear Combination Wilfried Michel, Ralf Schlüter, Hermann Ney http://arxiv.org/abs/2005.10049v1 • [eess.AS]End-to-End Speaker Diarization for an Unknown Number of Speakers with Encoder-Decoder Based Attractors Shota Horiguchi, Yusuke Fujita, Shinji Watanabe, Yawen Xue, Kenji Nagamatsu http://arxiv.org/abs/2005.09921v1 • [eess.AS]Exploring Transformers for Large-Scale Speech Recognition Liang Lu, Changliang Liu, Jinyu Li, Yifan Gong http://arxiv.org/abs/2005.09684v1 • [eess.AS]Investigation of Large-Margin Softmax in Neural Language Modeling Jingjing Huo, Yingbo Gao, Weiyue Wang, Ralf Schlüter, Hermann Ney http://arxiv.org/abs/2005.10089v1 • [eess.AS]PyChain: A Fully Parallelized PyTorch Implementation of LF-MMI for End-to-End ASR Yiwen Shao, Yiming Wang, Daniel Povey, Sanjeev Khudanpur http://arxiv.org/abs/2005.09824v1 • [eess.AS]Relative Positional Encoding for Speech Recognition and Direct Translation Ngoc-Quan Pham, Thanh-Le Ha, Tuan-Nam Nguyen, Thai-Son Nguyen, Elizabeth Salesky, Sebastian Stueker, Jan Niehues, Alexander Waibel http://arxiv.org/abs/2005.09940v1 • [eess.IV]A Statistical Model for Imaging Systems Jianfeng Zhou http://arxiv.org/abs/2005.09644v1 • [eess.IV]Adapting JPEG XS gains and priorities to tasks and contents Benoit Brummer, Christophe De Vleeschouwer http://arxiv.org/abs/2005.08768v2 • [eess.IV]An Innovative Approach to Determine Rebar Depth and Size by Comparing GPR Data with a Theoretical Database Zhongming Xiang, Ge Ou, Abbas Rashidi http://arxiv.org/abs/2005.09643v1 • [eess.IV]Attention-based network for low-light image enhancement Cheng Zhang, Qingsen Yan, Yu zhu, Jinqiu Sun, Yanning Zhang http://arxiv.org/abs/2005.09829v1 • [eess.IV]AutoML Segmentation for 3D Medical Image Data: Contribution to the MSD Challenge 2018 Oliver Rippel, Leon Weninger, Dorit Merhof http://arxiv.org/abs/2005.09978v1 • [eess.IV]Data Consistent CT Reconstruction from Insufficient Data with Learned Prior Images Yixing Huang, Alexander Preuhs, Michael Manhart, Guenter Lauritsch, Andreas Maier http://arxiv.org/abs/2005.10034v1 • [eess.IV]Iterative Network for Image Super-Resolution Yuqing Liu, Shiqi Wang, Jian Zhang, Shanshe Wang, Siwei Ma, Wen Gao http://arxiv.org/abs/2005.09964v1 • [eess.IV]Local semi-supervised approach to brain tissue classification in child brain MRI Nataliya Portman, Paule-J Toussaint, Alan C. Evans http://arxiv.org/abs/2005.09871v1 • [eess.IV]Lung Segmentation from Chest X-rays using Variational Data Imputation Raghavendra Selvan, Erik B. Dam, Sofus Rischel, Kaining Sheng, Mads Nielsen, Akshay Pai http://arxiv.org/abs/2005.10052v1 • [eess.SP]Federated Deep Learning Framework For Hybrid Beamforming in mm-Wave Massive MIMO Ahmet M. Elbir, Sinem Coleri http://arxiv.org/abs/2005.09969v1 • [math.LO]On embedding Lambek calculus into commutative categorial grammars Sergey Slavnov http://arxiv.org/abs/2005.10058v1 • [math.NA]Inverse problems with second-order Total Generalized Variation constraints Kristian Bredies, Tuomo Valkonen http://arxiv.org/abs/2005.09725v1 • [math.NA]The Random Feature Model for Input-Output Maps between Banach Spaces Nicholas H. Nelsen, Andrew M. Stuart http://arxiv.org/abs/2005.10224v1 • [math.OC]Lasso formulation of the shortest path problem Anqi Dong, Amirhossein Taghvaei, Tryphon T. Georgiou http://arxiv.org/abs/2005.09152v1 • [math.ST]Exponential ergodicity of mirror-Langevin diffusions Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet, Austin Stromme http://arxiv.org/abs/2005.09669v1 • [math.ST]Functional delta residuals and applications to functional effect sizes Fabian J. E. Telschow, Samuel Davenport, Armin Schwartzman http://arxiv.org/abs/2005.10041v1 • [math.ST]Inference on the Change Point in High Dimensional Dynamic Graphical Models Abhishek Kaul, Hongjin Zhang, Konstantinos Tsampourakis http://arxiv.org/abs/2005.09711v1 • [math.ST]Model Repair: Robust Recovery of Over-Parameterized Statistical Models Chao Gao, John Lafferty http://arxiv.org/abs/2005.09912v1 • [math.ST]Revisiting Concentration of Missing Mass Maciej Skorski http://arxiv.org/abs/2005.10018v1 • [math.ST]Smooth Distribution Function Estimation for Lifetime Distributions using Szasz-Mirakyan Operators Ariane Hanebeck, Bernhard Klar http://arxiv.org/abs/2005.09994v1 • [physics.ao-ph]Estimating volcanic ash emissions using retrieved satellite ash columns and inverse ash transport modelling André R. Brodtkorb, Anna Benedictow, Heiko Klein, Arve Kylling, Agnes Nyiri, Alvaro Valdebenito, Espen Sollum http://arxiv.org/abs/2005.09942v1 • [physics.med-ph]Self-supervised Dynamic CT Perfusion Image Denoising with Deep Neural Networks Dufan Wu, Hui Ren, Quanzheng Li http://arxiv.org/abs/2005.09766v1 • [physics.soc-ph]Empowering Urban Governance through Urban Science: Multi-scale Dynamics of Urban Systems Worldwide Juste Raimbault, Eric Denis, Denise Pumain http://arxiv.org/abs/2005.10007v1 • [physics.soc-ph]Phase transitions and social distancing control measures for SARS-CoV-2 on small world networks Benjamin Braun, Başak Taraktaş, Brian Beckage, Jane Molofsky http://arxiv.org/abs/2005.09751v1 • [physics.soc-ph]Spatial Heterogeneity Can Lead to Substantial Local Variations in COVID-19 Timing and Severity Loring J. Thomas, Peng Huang, Fan Yin, Xiaoshuang Iris Luo, Zack W. Almquist, John R. Hipp, Carter T. Butts http://arxiv.org/abs/2005.09850v1 • [q-bio.QM]Interactive exploration of population scale pharmacoepidemiology datasets Tengel Ekrem Skar, Einar Holsbø, Kristian Svendsen, Lars Ailo Bongo http://arxiv.org/abs/2005.09890v1 • [stat.AP]A Critical Assessment of Some Recent Work on COVID-19 Jörg Stoye http://arxiv.org/abs/2005.10237v1 • [stat.AP]A Route to School Informational Intervention for Air Pollution Exposure Reduction Shiraz Ahmed, Muhammad Adnan, Davy Janssens, Geert Wets http://arxiv.org/abs/2005.09955v1 • [stat.AP]Additive stacking for disaggregate electricity demand forecasting Christian Capezza, Biagio Palumbo, Yannig Goude, Simon N. Wood, Matteo Fasiolo http://arxiv.org/abs/2005.10092v1 • [stat.AP]Balancing spatial and non-spatial variation in varying coefficient modeling: a remedy for spurious correlation Daisuke Murakami, Daniel A. Griffith http://arxiv.org/abs/2005.09981v1 • [stat.AP]Uncertainty representation for early phase clinical test evaluations: a case study Sara Graziadio, Kevin J. Wilson http://arxiv.org/abs/2005.10011v1 • [stat.ME]A Toolbox for the Radial and Angular Marginalization of Bivariate Normal Distributions Emily A. Cooper, Hany Farid http://arxiv.org/abs/2005.09696v1 • [stat.ME]Dyadic Reciprocity as a Function of Covariates Jeremy Koster http://arxiv.org/abs/2005.09827v1 • [stat.ME]Dynamic mixtures of finite mixtures and telescoping sampling Sylvia Frühwirth-Schnatter, Gertraud Malsiner-Walli, Bettina Grün http://arxiv.org/abs/2005.09918v1 • [stat.ME]Matching methods for obtaining survival functions to estimate the effect of a time-dependent treatment Yun Li, Douglas E. Schaubel, Kevin He http://arxiv.org/abs/2005.09738v1 • [stat.ME]On a family of discrete log-symmetric distributions Helton Saulo, Roberto Vila, Leonardo Paiva, Narayanaswamy Balakrishnan http://arxiv.org/abs/2005.09744v1 • [stat.ME]On the use of cross-validation for the calibration of the tuning parameter in the adaptive lasso Ballout Nadim, Etievant Lola, Viallon Vivian http://arxiv.org/abs/2005.10119v1 • [stat.ME]Simultaneous Confidence Tubes for Comparison of Several Multivariate Linear Regression Models Jianan Peng, Wei Liu, Frank Bretz, Anthony Hayter http://arxiv.org/abs/2005.10059v1 • [stat.ME]Tables of Quantiles of the Distribution of the Empirical Chiral Index in the Case of the Uniform Law and in the Case of the Normal Law Michel Petitjean http://arxiv.org/abs/2005.09960v1 • [stat.ME]The Impact of Unmeasured Within- and Between-Cluster Confounding on the Bias of Effect Estimators from Fixed Effect, Mixed effect and Instrumental Variable Models Yun Li, Yoonseok Lee, Friedrich K Port, Bruce M Robinson http://arxiv.org/abs/2005.09780v1 • [stat.ME]The hidden waves in the ECG uncovered: A multicomponent model for the Cardiac Rhythm Cristina Rueda, Yolanda Larriba, Adrián Lamela http://arxiv.org/abs/2005.10173v1 • [stat.ML]Informative Path Planning for Anomaly Detection in Environment Exploration and Monitoring Antoine Blanchard, Themistoklis Sapsis http://arxiv.org/abs/2005.10040v1 • [stat.ML]Learning Undirected Graphs in Financial Markets José Vinícius de Miranda Cardoso, Daniel P. Palomar http://arxiv.org/abs/2005.09958v1 • [stat.ML]Nonparametric Score Estimators Yuhao Zhou, Jiaxin Shi, Jun Zhu http://arxiv.org/abs/2005.10099v1 • [stat.ML]ReLU Code Space: A Basis for Rating Network Quality Besides Accuracy Natalia Shepeleva, Werner Zellinger, Michal Lewandowski, Bernhard Moser http://arxiv.org/abs/2005.09903v1 • [stat.ML]Riemannian geometry for Compound Gaussian distributions: application to recursive change detection Florent Bouchard, Ammar Mian, Jialun Zhou, Salem Said, Guillaume Ginolhac, Yannick Berthoumieu http://arxiv.org/abs/2005.10087v1 • [stat.ML]Tessellated Wasserstein Auto-Encoders Kuo Gai, Shihua Zhang http://arxiv.org/abs/2005.09923v1 • [stat.ML]The Inverse G-Wishart Distribution and Variational Message Passing L. Maestrini, M. P. Wand http://arxiv.org/abs/2005.09876v1
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