cond-mat.stat-mech - 统计数学

    cs.AI - 人工智能 cs.AR - 硬件体系结构 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math-ph - 数学物理 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 nlin.AO - 适应和自组织系统 physics.ao-ph - 大气和海洋物理 physics.comp-ph - 计算物理学 physics.soc-ph - 物理学与社会 q-fin.ST - 统计金融学 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cond-mat.stat-mech]Entropy production and thermodynamics of information under protocol constraints
    • [cs.AI]Applications of Artificial Intelligence in Live Action Role-Playing Games (LARP)
    • [cs.AR]Evaluation of hybrid run-time power models for the ARM big.LITTLE architecture
    • [cs.CL]A Baseline Analysis for Podcast Abstractive Summarization
    • [cs.CL]Abstractive Summarization of Spoken and Written Instructions with BERT
    • [cs.CL]Comparative Computational Analysis of Global Structure in Canonical, Non-Canonical and Non-Literary Texts
    • [cs.CL]Conceptualized Representation Learning for Chinese Biomedical Text Mining
    • [cs.CL]Contextualized moral inference
    • [cs.CL]DUTH at SemEval-2020 Task 11: BERT with Entity Mapping for Propaganda Classification
    • [cs.CL]ETC-NLG: End-to-end Topic-Conditioned Natural Language Generation
    • [cs.CL]Is this sentence valid? An Arabic Dataset for Commonsense Validation
    • [cs.CL]JokeMeter at SemEval-2020 Task 7: Convolutional humor
    • [cs.CL]Learning from students’ perception on professors through opinion mining
    • [cs.CL]Query Understanding via Intent Description Generation
    • [cs.CL]Simple Unsupervised Similarity-Based Aspect Extraction
    • [cs.CL]TabSim: A Siamese Neural Network for Accurate Estimation of Table Similarity
    • [cs.CL]YNU-HPCC at SemEval-2020 Task 11: LSTM Network for Detection of Propaganda Techniques in News Articles
    • [cs.CR]Individual Privacy Accounting via a Renyi Filter
    • [cs.CR]Precision Health Data: Requirements, Challenges and Existing Techniques for Data Security and Privacy
    • [cs.CV]3rd Place Solution to “Google Landmark Retrieval 2020”
    • [cs.CV]A Critical Analysis of Patch Similarity Based Image Denoising Algorithms
    • [cs.CV]Active Class Incremental Learning for Imbalanced Datasets
    • [cs.CV]Adaptive Context-Aware Multi-Modal Network for Depth Completion
    • [cs.CV]AgingMapGAN (AMGAN): High-Resolution Controllable Face Aging with Spatially-Aware Conditional GANs
    • [cs.CV]Bias-Awareness for Zero-Shot Learning the Seen and Unseen
    • [cs.CV]Boundary Uncertainty in a Single-Stage Temporal Action Localization Network
    • [cs.CV]CDeC-Net: Composite Deformable Cascade Network for Table Detection in Document Images
    • [cs.CV]Cascade Convolutional Neural Network for Image Super-Resolution
    • [cs.CV]Confidence-aware Adversarial Learning for Self-supervised Semantic Matching
    • [cs.CV]Data Science for Motion and Time Analysis with Modern Motion Sensor Data
    • [cs.CV]Deep Active Learning in Remote Sensing for data efficient Change Detection
    • [cs.CV]Discriminability Distillation in Group Representation Learning
    • [cs.CV]FastSal: a Computationally Efficient Network for Visual Saliency Prediction
    • [cs.CV]GRAB: A Dataset of Whole-Body Human Grasping of Objects
    • [cs.CV]Graphical Object Detection in Document Images
    • [cs.CV]Image Colorization: A Survey and Dataset
    • [cs.CV]Improving Deep Stereo Network Generalization with Geometric Priors
    • [cs.CV]In-Home Daily-Life Captioning Using Radio Signals
    • [cs.CV]Interactive Annotation of 3D Object Geometry using 2D Scribbles
    • [cs.CV]LULC Segmentation of RGB Satellite Image Using FCN-8
    • [cs.CV]Label Decoupling Framework for Salient Object Detection
    • [cs.CV]Learning to Learn in a Semi-Supervised Fashion
    • [cs.CV]Mask-guided sample selection for Semi-Supervised Instance Segmentation
    • [cs.CV]Masked Face Recognition for Secure Authentication
    • [cs.CV]MonStereo: When Monocular and Stereo Meet at the Tail of 3D Human Localization
    • [cs.CV]On estimating gaze by self-attention augmented convolutions
    • [cs.CV]Probabilistic Deep Learning for Instance Segmentation
    • [cs.CV]Protect, Show, Attend and Tell: Image Captioning Model with Ownership Protection
    • [cs.CV]Spatiotemporal Action Recognition in Restaurant Videos
    • [cs.CV]Think about boundary: Fusing multi-level boundary information for landmark heatmap regression
    • [cs.CV]Towards End-to-end Car License Plate Location and Recognition in Unconstrained Scenarios
    • [cs.CV]Two-Stream Networks for Lane-Change Prediction of Surrounding Vehicles
    • [cs.CV]Using the discrete radon transformation for grayscale image moments
    • [cs.CY]An Economic Perspective on Predictive Maintenance of Filtration Units
    • [cs.CY]Historical Context and Key Features of Digital Money Tokens
    • [cs.CY]Machine Reasoning to Assess Pandemics Risks: Case of USS Theodore Roosevelt
    • [cs.CY]On Course, But Not There Yet: Enterprise Architecture Conformance and Benefits in Systems Development
    • [cs.DB]Table2Charts: Learning Shared Representations for Recommending Charts on Multi-dimensional Data
    • [cs.DC]Exosphere — Bringing The Cloud Closer
    • [cs.HC]Adapting Security Warnings to Counter Misinformation
    • [cs.IR]A Federated Multi-View Deep Learning Framework for Privacy-Preserving Recommendations
    • [cs.IR]Continual Domain Adaptation for Machine Reading Comprehension
    • [cs.IT]Cell-Free Massive MIMO with Channel Aging and Pilot Contamination
    • [cs.IT]Constructive Spherical Codes by Hopf Foliations
    • [cs.IT]Convergence of Federated Learning over a Noisy Downlink
    • [cs.IT]Dual-Polarized FDD Massive MIMO: A Comprehensive Framework
    • [cs.IT]Physical Layer Security in Cooperative NOMA Hybrid VLC/RF Systems
    • [cs.IT]Transmitting Extra Bits by Rotating Signal Constellations
    • [cs.IT]Uplink-Downlink Duality Between Multiple-Access and Broadcast Channels with Compressing Relays
    • [cs.LG]An empirical investigation of different classifiers, encoding and ensemble schemes for next event prediction using business process event logs
    • [cs.LG]Auxiliary-task Based Deep Reinforcement Learning for Participant Selection Problem in Mobile Crowdsourcing
    • [cs.LG]Balanced Activation for Long-tailed Visual Recognition
    • [cs.LG]Channel-Directed Gradients for Optimization of Convolutional Neural Networks
    • [cs.LG]CnGAN: Generative Adversarial Networks for Cross-network user preference generation for non-overlapped users
    • [cs.LG]Collaborative Filtering under Model Uncertainty
    • [cs.LG]Counterfactual Explanations for Machine Learning on Multivariate Time Series Data
    • [cs.LG]Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning
    • [cs.LG]Dynamic Dispatching for Large-Scale Heterogeneous Fleet via Multi-agent Deep Reinforcement Learning
    • [cs.LG]Ensuring Monotonic Policy Improvement in Entropy-regularized Value-based Reinforcement Learning
    • [cs.LG]Evaluating Nonlinear Decision Trees for Binary Classification Tasks with Other Existing Methods
    • [cs.LG]Exploring the use of Time-Dependent Cross-Network Information for Personalized Recommendations
    • [cs.LG]FedMVT: Semi-supervised Vertical Federated Learning with MultiView Training
    • [cs.LG]GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework
    • [cs.LG]Improving Fair Predictions Using Variational Inference In Causal Models
    • [cs.LG]LSTM Networks for Online Cross-Network Recommendations
    • [cs.LG]LowFER: Low-rank Bilinear Pooling for Link Prediction
    • [cs.LG]Many-to-one Recurrent Neural Network for Session-based Recommendation
    • [cs.LG]Multiple Classification with Split Learning
    • [cs.LG]Multiple-Source Adaptation with Domain Classifiers
    • [cs.LG]PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization
    • [cs.LG]Residual Network Based Direct Synthesis of EM Structures: A Study on One-to-One Transformers
    • [cs.LG]Sensitive Information Detection: Recursive Neural Networks for Encoding Context
    • [cs.LG]Smart Weather Forecasting Using Machine Learning:A Case Study in Tennessee
    • [cs.LG]Stochastic Markov Gradient Descent and Training Low-Bit Neural Networks
    • [cs.LG]The Advantage of Conditional Meta-Learning for Biased Regularization and Fine-Tuning
    • [cs.LG]The Fairness-Accuracy Pareto Front
    • [cs.LG]Theory of Deep Q-Learning: A Dynamical Systems Perspective
    • [cs.LG]Two Sides of the Same Coin: White-box and Black-box Attacks for Transfer Learning
    • [cs.LG]Unsupervised Multi-Modal Representation Learning for Affective Computing with Multi-Corpus Wearable Data
    • [cs.LG]Variable selection for Gaussian process regression through a sparse projection
    • [cs.LG]t-Soft Update of Target Network for Deep Reinforcement Learning
    • [cs.NE]A Survey on Evolutionary Neural Architecture Search
    • [cs.NE]Adding Filters to Improve Reservoir Computer Performance
    • [cs.NI]The Lockdown Effect: Implications of the COVID-19 Pandemic on Internet Traffic
    • [cs.RO]A Robotic Line Scan System with Adaptive ROI for Inspection of Defects over Convex Free-form Specular Surfaces
    • [cs.RO]Angular Momentum about the Contact Point for Control of Bipedal Locomotion: Validation in a LIP-based Controller
    • [cs.RO]Evaluating the Effect of Crutch-using on Trunk Muscle Loads
    • [cs.RO]Feature Guided Search for Creative Problem Solving Through Tool Construction
    • [cs.RO]Learning Obstacle Representations for Neural Motion Planning
    • [cs.RO]OpenBot: Turning Smartphones into Robots
    • [cs.RO]Tool Macgyvering: A Novel Framework for Combining Tool Substitution and Construction
    • [cs.RO]Visualization of Intended Assistance for Acceptance of Shared Control
    • [cs.SD]Medley2K: A Dataset of Medley Transitions
    • [cs.SE]A Review of Serverless Use Cases and their Characteristics
    • [cs.SE]A Tale of Two Cities: Software Developers Working from Home During the COVID-19 Pandemic
    • [cs.SE]Patching as Translation: the Data and the Metaphor
    • [cs.SE]Towards Guidelines for Assessing Qualities of Machine Learning Systems
    • [cs.SI]Complicating the Social Networks for Better Storytelling: An Empirical Study of Chinese Historical Text and Novel
    • [cs.SI]Degree difference: A simple measure to characterize structural heterogeneity in complex networks
    • [cs.SI]Multi-team Formation using Community Based Approach in Real-World Networks
    • [cs.SI]Predicting Shifting Individuals Using Text Mining and Graph Machine Learning on Twitter
    • [econ.EM]Powerful Inference
    • [eess.AS]Few Shot Text-Independent speaker verification using 3D-CNN
    • [eess.AS]ICE-Talk: an Interface for a Controllable Expressive Talking Machine
    • [eess.AS]Improving Tail Performance of a Deliberation E2E ASR Model Using a Large Text Corpus
    • [eess.IV]Efficient Blind-Spot Neural Network Architecture for Image Denoising
    • [eess.IV]Measure Anatomical Thickness from Cardiac MRI with Deep Neural Networks
    • [eess.SP]Continuous Authentication of Wearable Device Users from Heart Rate, Gait, and Breathing Data
    • [eess.SP]Federated Learning for Channel Estimation in Conventional and IRS-Assisted Massive MIMO
    • [eess.SY]Loop-shaping for reset control systems — A higher-order sinusoidal-input describing functions approach
    • [math-ph]Quantum statistical learning via Quantum Wasserstein natural gradient
    • [math.OC]Online Convex Optimization Perspective for Learning from Dynamically Revealed Preferences
    • [math.OC]Optimization with learning-informed differential equation constraints and its applications
    • [math.OC]Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization
    • [math.OC]Unconstrained optimisation on Riemannian manifolds
    • [math.PR]Markov Chain Convergence Rates from Coupling Constructions
    • [math.ST]A Kernel Two-Sample Test for Functional Data
    • [math.ST]Minimax estimation of norms of a probability density: I. Lower bounds
    • [math.ST]Minimax estimation of norms of a probability density: II. Rate-optimal estimation procedures
    • [nlin.AO]Noise-induced degeneration in online learning
    • [physics.ao-ph]Machine learning for weather and climate are worlds apart
    • [physics.comp-ph]Solving Inverse Stochastic Problems from Discrete Particle Observations Using the Fokker-Planck Equation and Physics-informed Neural Networks
    • [physics.soc-ph]High-resolution human mobility data reveal race and wealth disparities in disaster evacuation patterns
    • [physics.soc-ph]Modeling and Analysis of Excess Commuting with Trip Chains
    • [physics.soc-ph]Uncovering Hidden Dependency in Weighted Networks via Information Entropy
    • [q-fin.ST]Quantifying the impact of Covid-19 on stock market: An analysis from multi-source information
    • [quant-ph]RLD Fisher Information Bound for Multiparameter Estimation of Quantum Channels
    • [stat.AP]Geometric and statistical techniques for projective mapping of chocolate chip cookies with a large number of consumers
    • [stat.AP]How Ominous is the Future Global Warming Premonition?
    • [stat.AP]Importance subsampling for power system planning under multi-year demand and weather uncertainty
    • [stat.AP]Power laws in the Roman Empire: a survival analysis
    • [stat.AP]Torus Probabilistic Principal Component Analysis
    • [stat.CO]Prediction of Hilbertian autoregressive processes : a Recurrent Neural Network approach
    • [stat.ME]A Cramér-von Mises test of uniformity on the hypersphere
    • [stat.ME]Are You All Normal? It Depends!
    • [stat.ME]Efficient Detection Of Infected Individuals using Two Stage Testing
    • [stat.ME]High-frequency Estimation of the Lévy-driven Graph Ornstein-Uhlenbeck process
    • [stat.ME]Maximum likelihood estimation of parameters of spherical particle size distributions from profile size measurements and its application for small samples
    • [stat.ME]Path Dependent Structural Equation Models
    • [stat.ME]Policy Implications of Statistical Estimates: A General Bayesian Decision-Theoretic Model for Binary Outcomes
    • [stat.ME]Regularization Methods Based on the $L_q$-Likelihood for Linear Models with Heavy-Tailed Errors
    • [stat.ME]Statistically Significant Pattern Mining with Ordinal Utility
    • [stat.ME]Unbiased estimator for the variance of the leave-one-out cross-validation estimator for a Bayesian normal model with fixed variance
    • [stat.ML]Block-wise Minimization-Majorization algorithm for Huber’s criterion: sparse learning and applications
    • [stat.ML]Looking deeper into LIME
    • [stat.ML]New Directions in Distributed Deep Learning: Bringing the Network at Forefront of IoT Design
    • [stat.ML]Using Deep Networks for Scientific Discovery in Physiological Signals

    ·····································

    • [cond-mat.stat-mech]Entropy production and thermodynamics of information under protocol constraints
    Artemy Kolchinsky, David H. Wolpert
    http://arxiv.org/abs/2008.10764v1

    • [cs.AI]Applications of Artificial Intelligence in Live Action Role-Playing Games (LARP)
    Christoph Salge, Emily Short, Mike Preuss, Spyridion Samothrakis, Pieter Spronck
    http://arxiv.org/abs/2008.11003v1

    • [cs.AR]Evaluation of hybrid run-time power models for the ARM big.LITTLE architecture
    Kris Nikov, Jose L. Nunez-Yanez, Matthew Horsnell
    http://arxiv.org/abs/2008.10604v1

    • [cs.CL]A Baseline Analysis for Podcast Abstractive Summarization
    Chujie Zheng, Harry Jiannan Wang, Kunpeng Zhang, Ling Fan
    http://arxiv.org/abs/2008.10648v1

    • [cs.CL]Abstractive Summarization of Spoken and Written Instructions with BERT
    Alexandra Savelieva, Bryan Au-Yeung, Vasanth Ramani
    http://arxiv.org/abs/2008.09676v2

    • [cs.CL]Comparative Computational Analysis of Global Structure in Canonical, Non-Canonical and Non-Literary Texts
    Mahdi Mohseni, Volker Gast, Christoph Redies
    http://arxiv.org/abs/2008.10906v1

    • [cs.CL]Conceptualized Representation Learning for Chinese Biomedical Text Mining
    Ningyu Zhang, Qianghuai Jia, Kangping Yin, Liang Dong, Feng Gao, Nengwei Hua
    http://arxiv.org/abs/2008.10813v1

    • [cs.CL]Contextualized moral inference
    Jing Yi Xie, Graeme Hirst, Yang Xu
    http://arxiv.org/abs/2008.10762v1

    • [cs.CL]DUTH at SemEval-2020 Task 11: BERT with Entity Mapping for Propaganda Classification
    Anastasios Bairaktaris, Symeon Symeonidis, Avi Arampatzis
    http://arxiv.org/abs/2008.09894v2

    • [cs.CL]ETC-NLG: End-to-end Topic-Conditioned Natural Language Generation
    Ginevra Carbone, Gabriele Sarti
    http://arxiv.org/abs/2008.10875v1

    • [cs.CL]Is this sentence valid? An Arabic Dataset for Commonsense Validation
    Saja Tawalbeh, Mohammad AL-Smadi
    http://arxiv.org/abs/2008.10873v1

    • [cs.CL]JokeMeter at SemEval-2020 Task 7: Convolutional humor
    Martin Docekal, Martin Fajcik, Josef Jon, Pavel Smrz
    http://arxiv.org/abs/2008.11053v1

    • [cs.CL]Learning from students’ perception on professors through opinion mining
    Vladimir Vargas-Calderón, Juan S. Flórez, Leonel F. Ardila, Nicolas Parra-A., Jorge E. Camargo, Nelson Vargas
    http://arxiv.org/abs/2008.11183v1

    • [cs.CL]Query Understanding via Intent Description Generation
    Ruqing Zhang, Jiafeng Guo, Yixing Fan, Yanyan Lan, Xueqi Cheng
    http://arxiv.org/abs/2008.10889v1

    • [cs.CL]Simple Unsupervised Similarity-Based Aspect Extraction
    Danny Suarez Vargas, Lucas R. C. Pessutto, Viviane Pereira Moreira
    http://arxiv.org/abs/2008.10820v1

    • [cs.CL]TabSim: A Siamese Neural Network for Accurate Estimation of Table Similarity
    Maryam Habibi, Johannes Starlinger, Ulf Leser
    http://arxiv.org/abs/2008.10856v1

    • [cs.CL]YNU-HPCC at SemEval-2020 Task 11: LSTM Network for Detection of Propaganda Techniques in News Articles
    Jiaxu Dao, Jin Wang, Xuejie Zhang
    http://arxiv.org/abs/2008.10166v2

    • [cs.CR]Individual Privacy Accounting via a Renyi Filter
    Vitaly Feldman, Tijana Zrnic
    http://arxiv.org/abs/2008.11193v1

    • [cs.CR]Precision Health Data: Requirements, Challenges and Existing Techniques for Data Security and Privacy
    Chandra Thapa, Seyit Camtepe
    http://arxiv.org/abs/2008.10733v1

    • [cs.CV]3rd Place Solution to “Google Landmark Retrieval 2020”
    Ke Mei, Lei li, Jinchang Xu, Yanhua Cheng, Yugeng Lin
    http://arxiv.org/abs/2008.10480v2

    • [cs.CV]A Critical Analysis of Patch Similarity Based Image Denoising Algorithms
    Varuna De Silva
    http://arxiv.org/abs/2008.10824v1

    • [cs.CV]Active Class Incremental Learning for Imbalanced Datasets
    Eden Belouadah, Adrian Popescu, Umang Aggarwal, Léo Saci
    http://arxiv.org/abs/2008.10968v1

    • [cs.CV]Adaptive Context-Aware Multi-Modal Network for Depth Completion
    Shanshan Zhao, Mingming Gong, Huan Fu, Dacheng Tao
    http://arxiv.org/abs/2008.10833v1

    • [cs.CV]AgingMapGAN (AMGAN): High-Resolution Controllable Face Aging with Spatially-Aware Conditional GANs
    Julien Despois, Frederic Flament, Matthieu Perrot
    http://arxiv.org/abs/2008.10960v1

    • [cs.CV]Bias-Awareness for Zero-Shot Learning the Seen and Unseen
    William Thong, Cees G. M. Snoek
    http://arxiv.org/abs/2008.11185v1

    • [cs.CV]Boundary Uncertainty in a Single-Stage Temporal Action Localization Network
    Ting-Ting Xie, Christos Tzelepis, Ioannis Patras
    http://arxiv.org/abs/2008.11170v1

    • [cs.CV]CDeC-Net: Composite Deformable Cascade Network for Table Detection in Document Images
    Madhav Agarwal, Ajoy Mondal, C. V. Jawahar
    http://arxiv.org/abs/2008.10831v1

    • [cs.CV]Cascade Convolutional Neural Network for Image Super-Resolution
    Jianwei Zhang, zhenxing Wang, yuhui Zheng, Guoqing Zhang
    http://arxiv.org/abs/2008.10329v2

    • [cs.CV]Confidence-aware Adversarial Learning for Self-supervised Semantic Matching
    Shuaiyi Huang, Qiuyue Wang, Xuming He
    http://arxiv.org/abs/2008.10902v1

    • [cs.CV]Data Science for Motion and Time Analysis with Modern Motion Sensor Data
    Chiwoo Park, Sang Do Noh, Anuj Srivastava
    http://arxiv.org/abs/2008.10786v1

    • [cs.CV]Deep Active Learning in Remote Sensing for data efficient Change Detection
    Vít Růžička, Stefano D’Aronco, Jan Dirk Wegner, Konrad Schindler
    http://arxiv.org/abs/2008.11201v1

    • [cs.CV]Discriminability Distillation in Group Representation Learning
    Manyuan Zhang, Guanglu Song, Hang Zhou, Yu Liu
    http://arxiv.org/abs/2008.10850v1

    • [cs.CV]FastSal: a Computationally Efficient Network for Visual Saliency Prediction
    Feiyan Hu, Kevin McGuinness
    http://arxiv.org/abs/2008.11151v1

    • [cs.CV]GRAB: A Dataset of Whole-Body Human Grasping of Objects
    Omid Taheri, Nima Ghorbani, Michael J. Black, Dimitrios Tzionas
    http://arxiv.org/abs/2008.11200v1

    • [cs.CV]Graphical Object Detection in Document Images
    Ranajit Saha, Ajoy Mondal, C. V. Jawahar
    http://arxiv.org/abs/2008.10843v1

    • [cs.CV]Image Colorization: A Survey and Dataset
    Saeed Anwar, Muhammad Tahir, Chongyi Li, Ajmal Mian, Fahad Shahbaz Khan, Abdul Wahab Muzaffar
    http://arxiv.org/abs/2008.10774v1

    • [cs.CV]Improving Deep Stereo Network Generalization with Geometric Priors
    Jialiang Wang, Varun Jampani, Deqing Sun, Charles Loop, Stan Birchfield, Jan Kautz
    http://arxiv.org/abs/2008.11098v1

    • [cs.CV]In-Home Daily-Life Captioning Using Radio Signals
    Lijie Fan, Tianhong Li, Yuan Yuan, Dina Katabi
    http://arxiv.org/abs/2008.10966v1

    • [cs.CV]Interactive Annotation of 3D Object Geometry using 2D Scribbles
    Tianchang Shen, Jun Gao, Amlan Kar, Sanja Fidler
    http://arxiv.org/abs/2008.10719v1

    • [cs.CV]LULC Segmentation of RGB Satellite Image Using FCN-8
    Abu Bakar Siddik Nayem, Anis Sarker, Ovi Paul, Amin Ali, Md. Ashraful Amin, AKM Mahbubur Rahman
    http://arxiv.org/abs/2008.10736v1

    • [cs.CV]Label Decoupling Framework for Salient Object Detection
    Jun Wei, Shuhui Wang, Zhe Wu, Chi Su, Qingming Huang, Qi Tian
    http://arxiv.org/abs/2008.11048v1

    • [cs.CV]Learning to Learn in a Semi-Supervised Fashion
    Yun-Chun Chen, Chao-Te Chou, Yu-Chiang Frank Wang
    http://arxiv.org/abs/2008.11203v1

    • [cs.CV]Mask-guided sample selection for Semi-Supervised Instance Segmentation
    Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto
    http://arxiv.org/abs/2008.11073v1

    • [cs.CV]Masked Face Recognition for Secure Authentication
    Aqeel Anwar, Arijit Raychowdhury
    http://arxiv.org/abs/2008.11104v1

    • [cs.CV]MonStereo: When Monocular and Stereo Meet at the Tail of 3D Human Localization
    Lorenzo Bertoni, Sven Kreiss, Taylor Mordan, Alexandre Alahi
    http://arxiv.org/abs/2008.10913v1

    • [cs.CV]On estimating gaze by self-attention augmented convolutions
    Gabriel Lefundes, Luciano Oliveira
    http://arxiv.org/abs/2008.11055v1

    • [cs.CV]Probabilistic Deep Learning for Instance Segmentation
    Josef Lorenz Rumberger, Lisa Mais, Dagmar Kainmueller
    http://arxiv.org/abs/2008.10678v1

    • [cs.CV]Protect, Show, Attend and Tell: Image Captioning Model with Ownership Protection
    Jian Han Lim, Chee Seng Chan, Kam Woh Ng, Lixin Fan, Qiang Yang
    http://arxiv.org/abs/2008.11009v1

    • [cs.CV]Spatiotemporal Action Recognition in Restaurant Videos
    Akshat Gupta, Milan Desai, Wusheng Liang, Magesh Kannan
    http://arxiv.org/abs/2008.11149v1

    • [cs.CV]Think about boundary: Fusing multi-level boundary information for landmark heatmap regression
    Jinheng Xie, Jun Wan, Linlin Shen, Zhihui Lai
    http://arxiv.org/abs/2008.10924v1

    • [cs.CV]Towards End-to-end Car License Plate Location and Recognition in Unconstrained Scenarios
    Shuxin Qin, Sijiang Liu
    http://arxiv.org/abs/2008.10916v1

    • [cs.CV]Two-Stream Networks for Lane-Change Prediction of Surrounding Vehicles
    David Fernández-Llorca, Mahdi Biparva, Rubén Izquierdo-Gonzalo, John K. Tsotsos
    http://arxiv.org/abs/2008.10869v1

    • [cs.CV]Using the discrete radon transformation for grayscale image moments
    William Diggin, Michael Diggin
    http://arxiv.org/abs/2008.11083v1

    • [cs.CY]An Economic Perspective on Predictive Maintenance of Filtration Units
    Denis Tan Jing Yu, Adrian Law Wing-Keung
    http://arxiv.org/abs/2008.11070v1

    • [cs.CY]Historical Context and Key Features of Digital Money Tokens
    Shreepad Shukla
    http://arxiv.org/abs/2008.11084v1

    • [cs.CY]Machine Reasoning to Assess Pandemics Risks: Case of USS Theodore Roosevelt
    Kenneth Lai, Svetlana N. Yanushkevich
    http://arxiv.org/abs/2008.11040v1

    • [cs.CY]On Course, But Not There Yet: Enterprise Architecture Conformance and Benefits in Systems Development
    Ralph Foorthuis, Marlies van Steenbergen, Nino Mushkudiani, Wiel Bruls, Sjaak Brinkkemper, Rik Bos
    http://arxiv.org/abs/2008.11026v1

    • [cs.DB]Table2Charts: Learning Shared Representations for Recommending Charts on Multi-dimensional Data
    Mengyu Zhou, Qingtao Li, Yuejiang Li, Shi Han, Dongmei Zhang
    http://arxiv.org/abs/2008.11015v1

    • [cs.DC]Exosphere — Bringing The Cloud Closer
    Julian L. Pistorius, Chris Martin, Sanjana Sudarshan
    http://arxiv.org/abs/2008.10640v1

    • [cs.HC]Adapting Security Warnings to Counter Misinformation
    Ben Kaiser, Jerry Wei, Elena Lucherini, Kevin Lee, J. Nathan Matias, Jonathan Mayer
    http://arxiv.org/abs/2008.10772v1

    • [cs.IR]A Federated Multi-View Deep Learning Framework for Privacy-Preserving Recommendations
    Mingkai Huang, Hao Li, Bing Bai, Chang Wang, Kun Bai, Fei Wang
    http://arxiv.org/abs/2008.10808v1

    • [cs.IR]Continual Domain Adaptation for Machine Reading Comprehension
    Lixin Su, Jiafeng Guo, Ruqing Zhang, Yixing Fan, Yanyan Lan, Xueqi Cheng
    http://arxiv.org/abs/2008.10874v1

    • [cs.IT]Cell-Free Massive MIMO with Channel Aging and Pilot Contamination
    Jiakang Zheng, Jiayi Zhang, Emil Björnson, Bo Ai
    http://arxiv.org/abs/2008.10827v1

    • [cs.IT]Constructive Spherical Codes by Hopf Foliations
    Henrique K. Miyamoto, Sueli I. R. Costa, Henrique N. Sá Earp
    http://arxiv.org/abs/2008.10728v1

    • [cs.IT]Convergence of Federated Learning over a Noisy Downlink
    Mohammad Mohammadi Amiri, Deniz Gunduz, Sanjeev R. Kulkarni, H. Vincent Poor
    http://arxiv.org/abs/2008.11141v1

    • [cs.IT]Dual-Polarized FDD Massive MIMO: A Comprehensive Framework
    Mahdi Barzegar Khalilsarai, Tianyu Yang, Saeid Haghighatshoar, Xinping Yi, Giuseppe Caire
    http://arxiv.org/abs/2008.11182v1

    • [cs.IT]Physical Layer Security in Cooperative NOMA Hybrid VLC/RF Systems
    Mohanad Obeed, Anas Chaaban, Anas M. Salhab, Salam A. Zummo, Mohamed-Slim Alouini
    http://arxiv.org/abs/2008.10839v1

    • [cs.IT]Transmitting Extra Bits by Rotating Signal Constellations
    Jiachen Sun, Hao Liu, Xiao Ma
    http://arxiv.org/abs/2008.10818v1

    • [cs.IT]Uplink-Downlink Duality Between Multiple-Access and Broadcast Channels with Compressing Relays
    Liang Liu, Ya-Feng Liu, Pratik Patil, Wei Yu
    http://arxiv.org/abs/2008.10901v1

    • [cs.LG]An empirical investigation of different classifiers, encoding and ensemble schemes for next event prediction using business process event logs
    Bayu Adhi Tama, Marco Comuzzi, Jonghyeon Ko
    http://arxiv.org/abs/2008.10748v1

    • [cs.LG]Auxiliary-task Based Deep Reinforcement Learning for Participant Selection Problem in Mobile Crowdsourcing
    Wei Shen, Xiaonan He, Chuheng Zhang, Qiang Ni, Wanchu Dou, Yan Wang
    http://arxiv.org/abs/2008.11087v1

    • [cs.LG]Balanced Activation for Long-tailed Visual Recognition
    Jiawei Ren, Cunjun Yu, Zhongang Cai, Haiyu Zhao
    http://arxiv.org/abs/2008.11037v1

    • [cs.LG]Channel-Directed Gradients for Optimization of Convolutional Neural Networks
    Dong Lao, Peihao Zhu, Peter Wonka, Ganesh Sundaramoorthi
    http://arxiv.org/abs/2008.10766v1

    • [cs.LG]CnGAN: Generative Adversarial Networks for Cross-network user preference generation for non-overlapped users
    Dilruk Perera, Roger Zimmermann
    http://arxiv.org/abs/2008.10845v1

    • [cs.LG]Collaborative Filtering under Model Uncertainty
    Robin M. Schmidt, Moritz Hahn
    http://arxiv.org/abs/2008.10117v2

    • [cs.LG]Counterfactual Explanations for Machine Learning on Multivariate Time Series Data
    Emre Ates, Burak Aksar, Vitus J. Leung, Ayse K. Coskun
    http://arxiv.org/abs/2008.10781v1

    • [cs.LG]Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning
    Steven L. Brunton, J. Nathan Kutz, Krithika Manohar, Aleksandr Y. Aravkin, Kristi Morgansen, Jennifer Klemisch, Nicholas Goebel, James Buttrick, Jeffrey Poskin, Agnes Blom-Schieber, Thomas Hogan, Darren McDonald
    http://arxiv.org/abs/2008.10740v1

    • [cs.LG]Dynamic Dispatching for Large-Scale Heterogeneous Fleet via Multi-agent Deep Reinforcement Learning
    Chi Zhang, Philip Odonkor, Shuai Zheng, Hamed Khorasgani, Susumu Serita, Chetan Gupta
    http://arxiv.org/abs/2008.10713v1

    • [cs.LG]Ensuring Monotonic Policy Improvement in Entropy-regularized Value-based Reinforcement Learning
    Lingwei Zhu, Takamitsu Matsubara
    http://arxiv.org/abs/2008.10806v1

    • [cs.LG]Evaluating Nonlinear Decision Trees for Binary Classification Tasks with Other Existing Methods
    Yashesh Dhebar, Sparsh Gupta, Kalyanmoy Deb
    http://arxiv.org/abs/2008.10753v1

    • [cs.LG]Exploring the use of Time-Dependent Cross-Network Information for Personalized Recommendations
    Dilruk Perera, Roger Zimmermann
    http://arxiv.org/abs/2008.10866v1

    • [cs.LG]FedMVT: Semi-supervised Vertical Federated Learning with MultiView Training
    Yan Kang, Yang Liu, Tianjian Chen
    http://arxiv.org/abs/2008.10838v1

    • [cs.LG]GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework
    Haotao Wang, Shupeng Gui, Haichuan Yang, Ji Liu, Zhangyang Wang
    http://arxiv.org/abs/2008.11062v1

    • [cs.LG]Improving Fair Predictions Using Variational Inference In Causal Models
    Rik Helwegen, Christos Louizos, Patrick Forré
    http://arxiv.org/abs/2008.10880v1

    • [cs.LG]LSTM Networks for Online Cross-Network Recommendations
    Dilruk Perera, Roger Zimmermann
    http://arxiv.org/abs/2008.10849v1

    • [cs.LG]LowFER: Low-rank Bilinear Pooling for Link Prediction
    Saadullah Amin, Stalin Varanasi, Katherine Ann Dunfield, Günter Neumann
    http://arxiv.org/abs/2008.10858v1

    • [cs.LG]Many-to-one Recurrent Neural Network for Session-based Recommendation
    Amine Dadoun, Raphael Troncy
    http://arxiv.org/abs/2008.11136v1

    • [cs.LG]Multiple Classification with Split Learning
    Jongwon Kim, Sungho Shin, Yeonguk Yu, Junseok Lee, Kyoobin Lee
    http://arxiv.org/abs/2008.09874v2

    • [cs.LG]Multiple-Source Adaptation with Domain Classifiers
    Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh, Ningshan Zhang
    http://arxiv.org/abs/2008.11036v1

    • [cs.LG]PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization
    Zhize Li, Hongyan Bao, Xiangliang Zhang, Peter Richtárik
    http://arxiv.org/abs/2008.10898v1

    • [cs.LG]Residual Network Based Direct Synthesis of EM Structures: A Study on One-to-One Transformers
    David Munzer, Siawpeng Er, Minshuo Chen, Yan Li, Naga S. Mannem, Tuo Zhao, Hua Wang
    http://arxiv.org/abs/2008.10755v1

    • [cs.LG]Sensitive Information Detection: Recursive Neural Networks for Encoding Context
    Jan Neerbek
    http://arxiv.org/abs/2008.10863v1

    • [cs.LG]Smart Weather Forecasting Using Machine Learning:A Case Study in Tennessee
    A H M Jakaria, Md Mosharaf Hossain, Mohammad Ashiqur Rahman
    http://arxiv.org/abs/2008.10789v1

    • [cs.LG]Stochastic Markov Gradient Descent and Training Low-Bit Neural Networks
    Jonathan Ashbrock, Alexander M. Powell
    http://arxiv.org/abs/2008.11117v1

    • [cs.LG]The Advantage of Conditional Meta-Learning for Biased Regularization and Fine-Tuning
    Giulia Denevi, Massimiliano Pontil, Carlo Ciliberto
    http://arxiv.org/abs/2008.10857v1

    • [cs.LG]The Fairness-Accuracy Pareto Front
    Susan Wei, Marc Niethammer
    http://arxiv.org/abs/2008.10797v1

    • [cs.LG]Theory of Deep Q-Learning: A Dynamical Systems Perspective
    Arunselvan Ramaswamy
    http://arxiv.org/abs/2008.10870v1

    • [cs.LG]Two Sides of the Same Coin: White-box and Black-box Attacks for Transfer Learning
    Yinghua Zhang, Yangqiu Song, Jian Liang, Kun Bai, Qiang Yang
    http://arxiv.org/abs/2008.11089v1

    • [cs.LG]Unsupervised Multi-Modal Representation Learning for Affective Computing with Multi-Corpus Wearable Data
    Kyle Ross, Paul Hungler, Ali Etemad
    http://arxiv.org/abs/2008.10726v1

    • [cs.LG]Variable selection for Gaussian process regression through a sparse projection
    Chiwoo Park, David J. Borth, Nicholas S. Wilson, Chad N. Hunter
    http://arxiv.org/abs/2008.10769v1

    • [cs.LG]t-Soft Update of Target Network for Deep Reinforcement Learning
    Taisuke Kobayashi, Wendyam Eric Lionel Ilboudo
    http://arxiv.org/abs/2008.10861v1

    • [cs.NE]A Survey on Evolutionary Neural Architecture Search
    Yuqiao Liu, Yanan Sun, Bing Xue, Mengjie Zhang, Gary Yen
    http://arxiv.org/abs/2008.10937v1

    • [cs.NE]Adding Filters to Improve Reservoir Computer Performance
    Thomas L. Carroll
    http://arxiv.org/abs/2008.10633v1

    • [cs.NI]The Lockdown Effect: Implications of the COVID-19 Pandemic on Internet Traffic
    Anja Feldmann, Oliver Gasser, Franziska Lichtblau, Enric Pujol, Ingmar Poese, Christoph Dietzel, Daniel Wagner, Matthias Wichtlhuber, Juan Tapidor, Narseo Vallina-Rodriguez, Oliver Hohlfeld, Georgios Smaragdakis
    http://arxiv.org/abs/2008.10959v1

    • [cs.RO]A Robotic Line Scan System with Adaptive ROI for Inspection of Defects over Convex Free-form Specular Surfaces
    Shengzeng Huo, David Navarro-Alarcon, David Chik
    http://arxiv.org/abs/2008.10816v1

    • [cs.RO]Angular Momentum about the Contact Point for Control of Bipedal Locomotion: Validation in a LIP-based Controller
    Yukai Gong, Jessy Grizzle
    http://arxiv.org/abs/2008.10763v1

    • [cs.RO]Evaluating the Effect of Crutch-using on Trunk Muscle Loads
    Jing Chang, Wenrui Wang, Damien Chablat, Fouad Bennis
    http://arxiv.org/abs/2008.10882v1

    • [cs.RO]Feature Guided Search for Creative Problem Solving Through Tool Construction
    Lakshmi Nair, Sonia Chernova
    http://arxiv.org/abs/2008.10685v1

    • [cs.RO]Learning Obstacle Representations for Neural Motion Planning
    Robin Strudel, Ricardo Garcia, Justin Carpentier, Jean-Paul Laumond, Ivan Laptev, Cordelia Schmid
    http://arxiv.org/abs/2008.11174v1

    • [cs.RO]OpenBot: Turning Smartphones into Robots
    Matthias Müller, Vladlen Koltun
    http://arxiv.org/abs/2008.10631v1

    • [cs.RO]Tool Macgyvering: A Novel Framework for Combining Tool Substitution and Construction
    Lakshmi Nair, Nithin Shrivatsav, Sonia Chernova
    http://arxiv.org/abs/2008.10638v1

    • [cs.RO]Visualization of Intended Assistance for Acceptance of Shared Control
    Connor Brooks, Daniel Szafir
    http://arxiv.org/abs/2008.10759v1

    • [cs.SD]Medley2K: A Dataset of Medley Transitions
    Lukas Faber, Sandro Luck, Damian Pascual, Andreas Roth, Gino Brunner, Roger Wattenhofer
    http://arxiv.org/abs/2008.11159v1

    • [cs.SE]A Review of Serverless Use Cases and their Characteristics
    Simon Eismann, Joel Scheuner, Erwin van Eyk, Maximilian Schwinger, Johannes Grohmann, Nikolas Herbst, Cristina L. Abad, Alexandru Iosup
    http://arxiv.org/abs/2008.11110v1

    • [cs.SE]A Tale of Two Cities: Software Developers Working from Home During the COVID-19 Pandemic
    Denae Ford, Margaret-Anne Storey, Thomas Zimmermann, Christian Bird, Sonia Jaffe, Chandra Maddila, Jenna L. Butler, Brian Houck, Nachiappan Nagappan
    http://arxiv.org/abs/2008.11147v1

    • [cs.SE]Patching as Translation: the Data and the Metaphor
    Yangruibo Ding, Baishakhi Ray, Premkumar Devanbu, Vincent J. Hellendoorn
    http://arxiv.org/abs/2008.10707v1

    • [cs.SE]Towards Guidelines for Assessing Qualities of Machine Learning Systems
    Julien Siebert, Lisa Joeckel, Jens Heidrich, Koji Nakamichi, Kyoko Ohashi, Isao Namba, Rieko Yamamoto, Mikio Aoyama
    http://arxiv.org/abs/2008.11007v1

    • [cs.SI]Complicating the Social Networks for Better Storytelling: An Empirical Study of Chinese Historical Text and Novel
    Chenhan Zhang
    http://arxiv.org/abs/2008.10835v1

    • [cs.SI]Degree difference: A simple measure to characterize structural heterogeneity in complex networks
    Amirhossein Farzam, Areejit Samal, Jürgen Jost
    http://arxiv.org/abs/2008.10751v1

    • [cs.SI]Multi-team Formation using Community Based Approach in Real-World Networks
    Ramesh Bobby Addanki, Durga Bhavani S
    http://arxiv.org/abs/2008.11191v1

    • [cs.SI]Predicting Shifting Individuals Using Text Mining and Graph Machine Learning on Twitter
    Federico Albanese, Leandro Lombardi, Esteban Feuerstein, Pablo Balenzuela
    http://arxiv.org/abs/2008.10749v1

    • [econ.EM]Powerful Inference
    Xiaohong Chen, Sokbae Lee, Myung Hwan Seo
    http://arxiv.org/abs/2008.11140v1

    • [eess.AS]Few Shot Text-Independent speaker verification using 3D-CNN
    Prateek Mishra
    http://arxiv.org/abs/2008.11088v1

    • [eess.AS]ICE-Talk: an Interface for a Controllable Expressive Talking Machine
    Noé Tits, Kevin El Haddad, Thierry Dutoit
    http://arxiv.org/abs/2008.11045v1

    • [eess.AS]Improving Tail Performance of a Deliberation E2E ASR Model Using a Large Text Corpus
    Cal Peyser, Sepand Mavandadi, Tara N. Sainath, James Apfel, Ruoming Pang, Shankar Kumar
    http://arxiv.org/abs/2008.10491v2

    • [eess.IV]Efficient Blind-Spot Neural Network Architecture for Image Denoising
    David Honzátko, Siavash A. Bigdeli, Engin Türetken, L. Andrea Dunbar
    http://arxiv.org/abs/2008.11010v1

    • [eess.IV]Measure Anatomical Thickness from Cardiac MRI with Deep Neural Networks
    Qiaoying Huang, Eric Z. Chen, Hanchao Yu, Yimo Guo, Terrence Chen, Dimitris Metaxas, Shanhui Sun
    http://arxiv.org/abs/2008.11109v1

    • [eess.SP]Continuous Authentication of Wearable Device Users from Heart Rate, Gait, and Breathing Data
    William Cheung, Sudip Vhaduri
    http://arxiv.org/abs/2008.10779v1

    • [eess.SP]Federated Learning for Channel Estimation in Conventional and IRS-Assisted Massive MIMO
    Ahmet M. Elbir, Sinem Coleri
    http://arxiv.org/abs/2008.10846v1

    • [eess.SY]Loop-shaping for reset control systems — A higher-order sinusoidal-input describing functions approach
    Niranjan Saikumar, Kars Heinen, S. Hassan HosseinNia
    http://arxiv.org/abs/2008.10908v1

    • [math-ph]Quantum statistical learning via Quantum Wasserstein natural gradient
    Simon Becker, Wuchen Li
    http://arxiv.org/abs/2008.11135v1

    • [math.OC]Online Convex Optimization Perspective for Learning from Dynamically Revealed Preferences
    Violet Xinying Chen, Fatma Kılınç-Karzan
    http://arxiv.org/abs/2008.10460v2

    • [math.OC]Optimization with learning-informed differential equation constraints and its applications
    Guozhi Dong, Michael Hintermueller, Kostas Papafitsoros
    http://arxiv.org/abs/2008.10893v1

    • [math.OC]Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization
    Tianyi Chen, Yuejiao Sun, Wotao Yin
    http://arxiv.org/abs/2008.10847v1

    • [math.OC]Unconstrained optimisation on Riemannian manifolds
    Tuyen Trung Truong
    http://arxiv.org/abs/2008.11091v1

    • [math.PR]Markov Chain Convergence Rates from Coupling Constructions
    Yu Hang Jiang, Tong Liu, Zhiya Lou, Jeffrey S. Rosenthal, Shanshan Shangguan, Fei Wang, Zixuan Wu
    http://arxiv.org/abs/2008.10675v1

    • [math.ST]A Kernel Two-Sample Test for Functional Data
    George Wynne, Andrew B. Duncan
    http://arxiv.org/abs/2008.11095v1

    • [math.ST]Minimax estimation of norms of a probability density: I. Lower bounds
    Alexander Goldenshluger, Oleg Lepski
    http://arxiv.org/abs/2008.10979v1

    • [math.ST]Minimax estimation of norms of a probability density: II. Rate-optimal estimation procedures
    Alexander Goldenshluger, Oleg Lepski
    http://arxiv.org/abs/2008.10987v1

    • [nlin.AO]Noise-induced degeneration in online learning
    Yuzuru Sato, Daiji Tsutsui, Akio Fujiwara
    http://arxiv.org/abs/2008.10498v1

    • [physics.ao-ph]Machine learning for weather and climate are worlds apart
    Duncan Watson-Parris
    http://arxiv.org/abs/2008.10679v1

    • [physics.comp-ph]Solving Inverse Stochastic Problems from Discrete Particle Observations Using the Fokker-Planck Equation and Physics-informed Neural Networks
    Xiaoli Chen, Liu Yang, Jinqiao Duan, George Em Karniadakis
    http://arxiv.org/abs/2008.10653v1

    • [physics.soc-ph]High-resolution human mobility data reveal race and wealth disparities in disaster evacuation patterns
    Hengfang Deng, Daniel P. Aldrich, Michael M. Danziger, Jianxi Gao, Nolan E. Phillips, Sean P. Cornelius, Qi Ryan Wang
    http://arxiv.org/abs/2008.11169v1

    • [physics.soc-ph]Modeling and Analysis of Excess Commuting with Trip Chains
    Yujie Hu, Xiaopeng Li
    http://arxiv.org/abs/2008.11082v1

    • [physics.soc-ph]Uncovering Hidden Dependency in Weighted Networks via Information Entropy
    Mi Jin Lee, Eun Lee, Byunghwee Lee, Hawoong Jeong, Deok-Sun Lee, Sang Hoon Lee
    http://arxiv.org/abs/2008.11047v1

    • [q-fin.ST]Quantifying the impact of Covid-19 on stock market: An analysis from multi-source information
    Asim Kumer Dey, Toufiqul Haq, Kumer Das, Yulia R. Gel
    http://arxiv.org/abs/2008.10885v1

    • [quant-ph]RLD Fisher Information Bound for Multiparameter Estimation of Quantum Channels
    Vishal Katariya, Mark M. Wilde
    http://arxiv.org/abs/2008.11178v1

    • [stat.AP]Geometric and statistical techniques for projective mapping of chocolate chip cookies with a large number of consumers
    David Orden, Encarnación Fernández-Fernández, Marino Tejedor-Romero, Alejandra Martínez-Moraian
    http://arxiv.org/abs/2008.10431v2

    • [stat.AP]How Ominous is the Future Global Warming Premonition?
    Debashis Chatterjee, Sourabh Bhattacharya
    http://arxiv.org/abs/2008.11175v1

    • [stat.AP]Importance subsampling for power system planning under multi-year demand and weather uncertainty
    Adriaan P Hilbers, David J Brayshaw, Axel Gandy
    http://arxiv.org/abs/2008.10300v2

    • [stat.AP]Power laws in the Roman Empire: a survival analysis
    Pedro L. Ramos, Luciano da F. Costa, Francisco Louzada, Francisco A. Rodrigues
    http://arxiv.org/abs/2008.10344v1

    • [stat.AP]Torus Probabilistic Principal Component Analysis
    Anahita Nodehi, Mousa Golalizadeh, Mehdi Maadooliat, Claudio Agostinelli
    http://arxiv.org/abs/2008.10725v1

    • [stat.CO]Prediction of Hilbertian autoregressive processes : a Recurrent Neural Network approach
    Cl’{e]ment Carré, André Mas
    http://arxiv.org/abs/2008.11155v1

    • [stat.ME]A Cramér-von Mises test of uniformity on the hypersphere
    Eduardo García-Portugués, Paula Navarro-Esteban, Juan A. Cuesta-Albertos
    http://arxiv.org/abs/2008.10767v1

    • [stat.ME]Are You All Normal? It Depends!
    Wanfang Chen, Marc G. Genton
    http://arxiv.org/abs/2008.10957v1

    • [stat.ME]Efficient Detection Of Infected Individuals using Two Stage Testing
    Arjun Kodialam
    http://arxiv.org/abs/2008.10741v1

    • [stat.ME]High-frequency Estimation of the Lévy-driven Graph Ornstein-Uhlenbeck process
    Valentin Courgeau, Almut E. D. Veraart
    http://arxiv.org/abs/2008.10930v1

    • [stat.ME]Maximum likelihood estimation of parameters of spherical particle size distributions from profile size measurements and its application for small samples
    Ekaterina Poliakova
    http://arxiv.org/abs/2008.09091v2

    • [stat.ME]Path Dependent Structural Equation Models
    Ranjani Srinivasan, Jaron Lee, Narges Ahmidi, Ilya Shpitser
    http://arxiv.org/abs/2008.10706v1

    • [stat.ME]Policy Implications of Statistical Estimates: A General Bayesian Decision-Theoretic Model for Binary Outcomes
    Akisato Suzuki
    http://arxiv.org/abs/2008.10903v1

    • [stat.ME]Regularization Methods Based on the $L_q$-Likelihood for Linear Models with Heavy-Tailed Errors
    Yoshihiro Hirose
    http://arxiv.org/abs/2008.10876v1

    • [stat.ME]Statistically Significant Pattern Mining with Ordinal Utility
    Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma
    http://arxiv.org/abs/2008.10747v1

    • [stat.ME]Unbiased estimator for the variance of the leave-one-out cross-validation estimator for a Bayesian normal model with fixed variance
    Tuomas Sivula, Måns Magnusson, Aki Vehtari
    http://arxiv.org/abs/2008.10859v1

    • [stat.ML]Block-wise Minimization-Majorization algorithm for Huber’s criterion: sparse learning and applications
    Esa Ollila, Ammar Mian
    http://arxiv.org/abs/2008.10982v1

    • [stat.ML]Looking deeper into LIME
    Damien Garreau, Ulrike von Luxburg
    http://arxiv.org/abs/2008.11092v1

    • [stat.ML]New Directions in Distributed Deep Learning: Bringing the Network at Forefront of IoT Design
    Kartikeya Bhardwaj, Wei Chen, Radu Marculescu
    http://arxiv.org/abs/2008.10805v1

    • [stat.ML]Using Deep Networks for Scientific Discovery in Physiological Signals
    Tom Beer, Bar Eini-Porat, Sebastian Goodfellow, Danny Eytan, Uri Shalit
    http://arxiv.org/abs/2008.10936v1