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
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• [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