cs.AI - 人工智能
cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DC - 分布式、并行与集群计算 cs.GT - 计算机科学与博弈论 cs.HC - 人机接口 cs.IT - 信息论 cs.LG - 自动学习 cs.MA - 多代理系统 cs.MM - 多媒体 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.PL - 编程语言 cs.RO - 机器人学 cs.SC - 符号计算 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 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.CO - 组合数学 math.NA - 数值分析 math.OC - 优化与控制 math.PR - 概率 nlin.AO - 适应和自组织系统 q-bio.NC - 神经元与认知 q-bio.PE - 人口与发展 q-bio.QM - 定量方法 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
• [cs.AI]Action Space Shaping in Deep Reinforcement Learning
• [cs.AI]An anytime tree search algorithm for the 2018 ROADEF/EURO challenge glass cutting problem
• [cs.AI]Benchmarking End-to-End Behavioural Cloning on Video Games
• [cs.AI]Bias in Machine Learning What is it Good (and Bad) for?
• [cs.AI]Improving Confidence in the Estimation of Values and Norms
• [cs.AI]Improving the Utility of Knowledge Graph Embeddings with Calibration
• [cs.AI]Information State Embedding in Partially Observable Cooperative Multi-Agent Reinforcement Learning
• [cs.AI]Mimicking Evolution with Reinforcement Learning
• [cs.AI]Personal Health Knowledge Graphs for Patients
• [cs.AI]Software Language Comprehension using a Program-Derived Semantic Graph
• [cs.CL]Causal Inference of Script Knowledge
• [cs.CL]Give your Text Representation Models some Love: the Case for Basque
• [cs.CL]How Furiously Can Colourless Green Ideas Sleep? Sentence Acceptability in Context
• [cs.CL]Igbo-English Machine Translation: An Evaluation Benchmark
• [cs.CL]Mapping Languages and Demographics with Georeferenced Corpora
• [cs.CL]Mapping Languages: The Corpus of Global Language Use
• [cs.CL]NUBES: A Corpus of Negation and Uncertainty in Spanish Clinical Texts
• [cs.CL]Revisiting the linearity in cross-lingual embedding mappings: from a perspective of word analogies
• [cs.CR]Topological Properties of Multi-Party Blockchain Transactions
• [cs.CV]Adversarial Learning for Personalized Tag Recommendation
• [cs.CV]Alleviating Semantic-level Shift: A Semi-supervised Domain Adaptation Method for Semantic Segmentation
• [cs.CV]An Attention-Based Deep Learning Model for Multiple Pedestrian Attributes Recognition
• [cs.CV]Articulation-aware Canonical Surface Mapping
• [cs.CV]BUDA: Boundless Unsupervised Domain Adaptation in Semantic Segmentation
• [cs.CV]Background Matting: The World is Your Green Screen
• [cs.CV]Bodies at Rest: 3D Human Pose and Shape Estimation from a Pressure Image using Synthetic Data
• [cs.CV]Boosting Deep Hyperspectral Image Classification with Spectral Unmixing
• [cs.CV]Consistent Multiple Sequence Decoding
• [cs.CV]Controllable Orthogonalization in Training DNNs
• [cs.CV]DOPS: Learning to Detect 3D Objects and Predict their 3D Shapes
• [cs.CV]DualConvMesh-Net: Joint Geodesic and Euclidean Convolutions on 3D Meshes
• [cs.CV]Effect of Annotation Errors on Drone Detection with YOLOv3
• [cs.CV]Face Quality Estimation and Its Correlation to Demographic and Non-Demographic Bias in Face Recognition
• [cs.CV]Generalized Zero-Shot Learning Via Over-Complete Distribution
• [cs.CV]Graph-based fusion for change detection in multi-spectral images
• [cs.CV]Improving 3D Object Detection through Progressive Population Based Augmentation
• [cs.CV]Learning Longterm Representations for Person Re-Identification Using Radio Signals
• [cs.CV]Learning Unsupervised Hierarchical Part Decomposition of 3D Objects from a Single RGB Image
• [cs.CV]Learning to See Through Obstructions
• [cs.CV]Learning to Segment the Tail
• [cs.CV]MCEN: Bridging Cross-Modal Gap between Cooking Recipes and Dish Images with Latent Variable Model
• [cs.CV]Map-Enhanced Ego-Lane Detection in the Missing Feature Scenarios
• [cs.CV]Memory-Efficient Incremental Learning Through Feature Adaptation
• [cs.CV]Model-based disentanglement of lens occlusions
• [cs.CV]Monocular Camera Localization in Prior LiDAR Maps with 2D-3D Line Correspondences
• [cs.CV]Objects of violence: synthetic data for practical ML in human rights investigations
• [cs.CV]Occlusion-Aware Depth Estimation with Adaptive Normal Constraints
• [cs.CV]PaStaNet: Toward Human Activity Knowledge Engine
• [cs.CV]Physically Realizable Adversarial Examples for LiDAR Object Detection
• [cs.CV]Pixel-BERT: Aligning Image Pixels with Text by Deep Multi-Modal Transformers
• [cs.CV]ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis
• [cs.CV]Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition
• [cs.CV]Robust Single Rotation Averaging
• [cs.CV]Robust Single-Image Super-Resolution via CNNs and TV-TV Minimization
• [cs.CV]SSHFD: Single Shot Human Fall Detection with Occluded Joints Resilience
• [cs.CV]Scene-Adaptive Video Frame Interpolation via Meta-Learning
• [cs.CV]Synchronizing Probability Measures on Rotations via Optimal Transport
• [cs.CV]Tracking Objects as Points
• [cs.CV]Tracking by Instance Detection: A Meta-Learning Approach
• [cs.CV]Unsupervised Real-world Image Super Resolution via Domain-distance Aware Training
• [cs.CY]A County-level Dataset for Informing the United States’ Response to COVID-19
• [cs.CY]Best Practices for Transparency in Machine Generated Personalization
• [cs.CY]Combating The Machine Ethics Crisis: An Educational Approach
• [cs.CY]Patterns of population displacement during mega-fires in California detected using Facebook Disaster Maps
• [cs.CY]Robots in the Danger Zone: Exploring Public Perception through Engagement
• [cs.CY]The Covid19Impact Survey: Assessing the Pulse of the COVID-19 Pandemic in Spain via 24 questions
• [cs.DC]A Blockchain-based Decentralized Federated Learning Framework with Committee Consensus
• [cs.DC]Building a Shared Resource HPC Center Across University Schools and Institutes: A Case Study
• [cs.DC]Scheduling Parallel-Task Jobs Subject to Packing and Placement Constraints
• [cs.GT]No-regret learning dynamics for extensive-form correlated and coarse correlated equilibria
• [cs.GT]Provable Sample Complexity Guarantees for Learning of Continuous-Action Graphical Games with Nonparametric Utilities
• [cs.HC]A Survey on Conversational Recommender Systems
• [cs.IT]An Upgrading Algorithm with Optimal Power Law
• [cs.IT]Analysis of Multi-Messages Retransmission Schemes
• [cs.IT]Fundamental Limits of Distributed Encoding
• [cs.IT]Gopala-Hemachandra codes revisited
• [cs.IT]Repetition-based NOMA Transmission and Its Outage Probability Analysis
• [cs.IT]Strong Converse for Testing Against Independence over a Noisy channel
• [cs.LG]Augmented Q Imitation Learning (AQIL)
• [cs.LG]Average Reward Adjusted Discounted Reinforcement Learning: Near-Blackwell-Optimal Policies for Real-World Applications
• [cs.LG]DeepSumm — Deep Code Summaries using Neural Transformer Architecture
• [cs.LG]Exploration of Reinforcement Learning for Event Camera using Car-like Robots
• [cs.LG]Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation
• [cs.LG]In Automation We Trust: Investigating the Role of Uncertainty in Active Learning Systems
• [cs.LG]Learning Representations For Images With Hierarchical Labels
• [cs.LG]Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T)
• [cs.LG]Learning to Ask Medical Questions using Reinforcement Learning
• [cs.LG]Learning to cooperate: Emergent communication in multi-agent navigation
• [cs.LG]Mirrorless Mirror Descent: A More Natural Discretization of Riemannian Gradient Flow
• [cs.LG]Object-Centric Image Generation with Factored Depths, Locations, and Appearances
• [cs.LG]Predicting Injectable Medication Adherence via a Smart Sharps Bin and Machine Learning
• [cs.LG]Predictive Bandits
• [cs.LG]Sequential Feature Classification in the Context of Redundancies
• [cs.LG]Sum-product networks: A survey
• [cs.LG]Surrogate-assisted performance tuning of knowledge discovery algorithms: application to clinical pathway evolutionary modeling
• [cs.LG]Understanding Global Feature Contributions Through Additive Importance Measures
• [cs.MA]Generate Country-Scale Networks of Interaction from Scattered Statistics
• [cs.MM]Multi-Modal Video Forensic Platform for Investigating Post-Terrorist Attack Scenarios
• [cs.NE]Device-aware inference operations in SONOS nonvolatile memory arrays
• [cs.NE]Projected Neural Network for a Class of Sparse Regression with Cardinality Penalty
• [cs.NI]IoT-Flock: An Open-source Framework for IoT Traffic Generation
• [cs.NI]Network Orchestration in Mobile Networks via a Synergy of Model-driven and AI-based Techniques
• [cs.PL]On the Principles of Differentiable Quantum Programming Languages
• [cs.PL]Proceedings of the 12th International Workshop on Programming Language Approaches to Concurrency- and Communication-cEntric Software
• [cs.RO]A Sensorized Multicurved Robot Finger with Data-driven Touch Sensing via Overlapping Light Signals
• [cs.RO]A reconfigurable robot workcell for quick set-up of assembly processes
• [cs.RO]CLASH WRIST — A hardware to increase the capability of CLASH fruit gripper to use environment constraints exploration
• [cs.RO]Constrained-Space Optimization and Reinforcement Learning for Complex Tasks
• [cs.RO]Enabling End-Users to Deploy Flexible Human-Robot Teams to Factories of the Future
• [cs.RO]Go Fetch: Mobile Manipulation in Unstructured Environments
• [cs.RO]Human-Guided Planner for Non-Prehensile Manipulation
• [cs.RO]Learned and Controlled Autonomous Robotic Exploration in an Extreme, Unknown Environment
• [cs.RO]Learning Agile Robotic Locomotion Skills by Imitating Animals
• [cs.RO]Multimodal Material Classification for Robots using Spectroscopy and High Resolution Texture Imaging
• [cs.SC]Explosive Proofs of Mathematical Truths
• [cs.SE]FaaSten Your Decisions: Classification Framework and Technology Review of Function-as-a-Service Platforms
• [cs.SI]#ArsonEmergency and Australia’s “Black Summer”: Polarisation and misinformation on social media
• [cs.SI]A k-hop Collaborate Game Model: Extended to Community Budgets and Adaptive Non-Submodularity
• [cs.SI]Analysing the Extent of Misinformation in Cancer Related Tweets
• [cs.SI]Modeling Dynamic Heterogeneous Network for Link Prediction using Hierarchical Attention with Temporal RNN
• [cs.SI]Spotting political social bots in Twitter: A use case of the 2019 Spanish general election
• [cs.SI]The Paradox of Information Access: On Modeling Social-Media-Induced Polarization
• [eess.AS]Improving auditory attention decoding performance of linear and non-linear methods using state-space model
• [eess.IV]End-To-End Convolutional Neural Network for 3D Reconstruction of Knee Bones From Bi-Planar X-Ray Images
• [eess.IV]Image Denoising Using Sparsifying Transform Learning and Weighted Singular Values Minimization
• [eess.IV]Introducing Anisotropic Minkowski Functionals for Local Structure Analysis and Prediction of Biomechanical Strength of Proximal Femur Specimens
• [eess.IV]Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipeline
• [eess.SP]Enhance the performance of navigation: A two-stage machine learning approach
• [eess.SY]Near Optimality and Tractability in Stochastic Nonlinear Control
• [eess.SY]Safe Feedback Motion Planning: A Contraction Theory and $\mathcal{L}_1$-Adaptive Control Based Approach
• [eess.SY]Safe Reinforcement Learning via Projection on a Safe Set: How to Achieve Optimality?
• [math.CO]Markov Chain-based Sampling for Exploring RNA Secondary Structure under the Nearest Neighbor Thermodynamic Model
• [math.CO]Power Hadamard matrices and Plotkin-optimal p-ary codes
• [math.NA]Bayesian ODE Solvers: The Maximum A Posteriori Estimate
• [math.OC]Fractional Deep Neural Network via Constrained Optimization
• [math.PR]Kernel autocovariance operators of stationary processes: Estimation and convergence
• [math.PR]Stopping explosion by penalising transmission to hubs in scale-free spatial random graphs
• [nlin.AO]Neuronal Sequence Models for Bayesian Online Inference
• [q-bio.NC]A macro agent and its actions
• [q-bio.PE]Coronavirus Covid-19 spreading in Italy: optimizing an epidemiological model with dynamic social distancing through Differential Evolution
• [q-bio.QM]DeepSIBA: Chemical Structure-based Inference of Biological Alterations
• [quant-ph]Single Quantum Deletion Error-Correcting Codes
• [stat.AP]Detecting Suspected Epidemic Cases Using Trajectory Big Data
• [stat.AP]Incorporating travel behavior regularity into passenger flow forecasting
• [stat.AP]Spatiotemporal analysis of urban heatwaves using Tukey g-and-h random field models
• [stat.CO]An approximate {KLD} based experimental design for models with intractable likelihoods
• [stat.CO]Distributed Bayesian clustering
• [stat.ME]A Monte Carlo comparison of categorical tests of independence
• [stat.ME]An Approximate Quasi-Likelihood Approach for Error-Prone Failure Time Outcomes and Exposures
• [stat.ME]Bayesian model selection approach for colored graphical Gaussian models
• [stat.ME]Classification of Functional Data by Detecting the Discrepancy of Second Moment Structure of Scaled functions
• [stat.ME]Duality between Approximate Bayesian Methods and Prior Robustness
• [stat.ME]Integrative High Dimensional Multiple Testing with Heterogeneity under Data Sharing Constraints
• [stat.ME]On Interactions Between Observed and Unobserved Covariates in Matched Observational Studies
• [stat.ME]Pattern graphs: a graphical approach to nonmonotone missing data
• [stat.ME]Sequential online subsampling for thinning experimental designs
• [stat.ME]Stochastic modeling and estimation of COVID-19 population dynamics
• [stat.ML]Identification Methods With Arbitrary Interventional Distributions as Inputs
• [stat.ML]Projection Pursuit Gaussian Process Regression
• [stat.ML]Randomized Kernel Multi-view Discriminant Analysis
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• [cs.AI]Action Space Shaping in Deep Reinforcement Learning
Anssi Kanervisto, Christian Scheller, Ville Hautamäki
http://arxiv.org/abs/2004.00980v1
• [cs.AI]An anytime tree search algorithm for the 2018 ROADEF/EURO challenge glass cutting problem
Luc Libralesso, Florian Fontan
http://arxiv.org/abs/2004.00963v1
• [cs.AI]Benchmarking End-to-End Behavioural Cloning on Video Games
Anssi Kanervisto, Joonas Pussinen, Ville Hautamäki
http://arxiv.org/abs/2004.00981v1
• [cs.AI]Bias in Machine Learning What is it Good (and Bad) for?
Thomas Hellström, Virginia Dignum, Suna Bensch
http://arxiv.org/abs/2004.00686v1
• [cs.AI]Improving Confidence in the Estimation of Values and Norms
Luciano Cavalcante Siebert, Rijk Mercuur, Virginia Dignum, Jeroen van den Hoven, Catholijn Jonker
http://arxiv.org/abs/2004.01056v1
• [cs.AI]Improving the Utility of Knowledge Graph Embeddings with Calibration
Tara Safavi, Danai Koutra, Edgar Meij
http://arxiv.org/abs/2004.01168v1
• [cs.AI]Information State Embedding in Partially Observable Cooperative Multi-Agent Reinforcement Learning
Weichao Mao, Kaiqing Zhang, Erik Miehling, Tamer Başar
http://arxiv.org/abs/2004.01098v1
• [cs.AI]Mimicking Evolution with Reinforcement Learning
João P. Abrantes, Arnaldo J. Abrantes, Frans A. Oliehoek
http://arxiv.org/abs/2004.00048v1
• [cs.AI]Personal Health Knowledge Graphs for Patients
Nidhi Rastogi, Mohammed J. Zaki
http://arxiv.org/abs/2004.00071v1
• [cs.AI]Software Language Comprehension using a Program-Derived Semantic Graph
Roshni G. Iyer, Yizhou Sun, Wei Wang, Justin Gottschlich
http://arxiv.org/abs/2004.00768v1
• [cs.CL]Causal Inference of Script Knowledge
Noah Weber, Rachel Rudinger, Benjamin Van Durme
http://arxiv.org/abs/2004.01174v1
• [cs.CL]Give your Text Representation Models some Love: the Case for Basque
Rodrigo Agerri, Iñaki San Vicente, Jon Ander Campos, Ander Barrena, Xabier Saralegi, Aitor Soroa, Eneko Agirre
http://arxiv.org/abs/2004.00033v2
• [cs.CL]How Furiously Can Colourless Green Ideas Sleep? Sentence Acceptability in Context
Jey Han Lau, Carlos S. Armendariz, Shalom Lappin, Matthew Purver, Chang Shu
http://arxiv.org/abs/2004.00881v1
• [cs.CL]Igbo-English Machine Translation: An Evaluation Benchmark
Ignatius Ezeani, Paul Rayson, Ikechukwu Onyenwe, Chinedu Uchechukwu, Mark Hepple
http://arxiv.org/abs/2004.00648v1
• [cs.CL]Mapping Languages and Demographics with Georeferenced Corpora
Jonathan Dunn, Ben Adams
http://arxiv.org/abs/2004.00809v1
• [cs.CL]Mapping Languages: The Corpus of Global Language Use
Jonathan Dunn
http://arxiv.org/abs/2004.00798v1
• [cs.CL]NUBES: A Corpus of Negation and Uncertainty in Spanish Clinical Texts
Salvador Lima, Naiara Perez, Montse Cuadros, German Rigau
http://arxiv.org/abs/2004.01092v1
• [cs.CL]Revisiting the linearity in cross-lingual embedding mappings: from a perspective of word analogies
Xutan Peng, Chenghua Lin, Mark Stevenson, Chen li
http://arxiv.org/abs/2004.01079v1
• [cs.CR]Topological Properties of Multi-Party Blockchain Transactions
Dongfang Zhao
http://arxiv.org/abs/2004.01045v1
• [cs.CV]Adversarial Learning for Personalized Tag Recommendation
Erik Quintanilla, Yogesh Rawat, Andrey Sakryukin, Mubarak Shah, Mohan Kankanhalli
http://arxiv.org/abs/2004.00698v1
• [cs.CV]Alleviating Semantic-level Shift: A Semi-supervised Domain Adaptation Method for Semantic Segmentation
Zhonghao Wang, Yunchao Wei, Rogerior Feris, Jinjun Xiong, Wen-Mei Hwu, Thomas S. Huang, Honghui Shi
http://arxiv.org/abs/2004.00794v1
• [cs.CV]An Attention-Based Deep Learning Model for Multiple Pedestrian Attributes Recognition
Ehsan Yaghoubi, Diana Borza, João Neves, Aruna Kumar, Hugo Proença
http://arxiv.org/abs/2004.01110v1
• [cs.CV]Articulation-aware Canonical Surface Mapping
Nilesh Kulkarni, Abhinav Gupta, David F. Fouhey, Shubham Tulsiani
http://arxiv.org/abs/2004.00614v2
• [cs.CV]BUDA: Boundless Unsupervised Domain Adaptation in Semantic Segmentation
Maxime Bucher, Tuan-Hung Vu, Matthieu Cord, Patrick Pérez
http://arxiv.org/abs/2004.01130v1
• [cs.CV]Background Matting: The World is Your Green Screen
Soumyadip Sengupta, Vivek Jayaram, Brian Curless, Steve Seitz, Ira Kemelmacher-Shlizerman
http://arxiv.org/abs/2004.00626v1
• [cs.CV]Bodies at Rest: 3D Human Pose and Shape Estimation from a Pressure Image using Synthetic Data
Henry M. Clever, Zackory Erickson, Ariel Kapusta, Greg Turk, C. Karen Liu, Charles C. Kemp
http://arxiv.org/abs/2004.01166v1
• [cs.CV]Boosting Deep Hyperspectral Image Classification with Spectral Unmixing
Alan J. X. Guo, Fei Zhu
http://arxiv.org/abs/2004.00583v2
• [cs.CV]Consistent Multiple Sequence Decoding
Bicheng Xu, Leonid Sigal
http://arxiv.org/abs/2004.00760v1
• [cs.CV]Controllable Orthogonalization in Training DNNs
Lei Huang, Li Liu, Fan Zhu, Diwen Wan, Zehuan Yuan, Bo Li, Ling Shao
http://arxiv.org/abs/2004.00917v1
• [cs.CV]DOPS: Learning to Detect 3D Objects and Predict their 3D Shapes
Mahyar Najibi, Guangda Lai, Abhijit Kundu, Zhichao Lu, Vivek Rathod, Tom Funkhouser, Caroline Pantofaru, David Ross, Larry S. Davis, Alireza Fathi
http://arxiv.org/abs/2004.01170v1
• [cs.CV]DualConvMesh-Net: Joint Geodesic and Euclidean Convolutions on 3D Meshes
Jonas Schult, Francis Engelmann, Theodora Kontogianni, Bastian Leibe
http://arxiv.org/abs/2004.01002v1
• [cs.CV]Effect of Annotation Errors on Drone Detection with YOLOv3
Aybora Koksal, Kutalmis Gokalp Ince, A. Aydin Alatan
http://arxiv.org/abs/2004.01059v1
• [cs.CV]Face Quality Estimation and Its Correlation to Demographic and Non-Demographic Bias in Face Recognition
Philipp Terhörst, Jan Niklas Kolf, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
http://arxiv.org/abs/2004.01019v1
• [cs.CV]Generalized Zero-Shot Learning Via Over-Complete Distribution
Rohit Keshari, Richa Singh, Mayank Vatsa
http://arxiv.org/abs/2004.00666v1
• [cs.CV]Graph-based fusion for change detection in multi-spectral images
David Alejandro Jimenez Sierra, Hernán Darío Benítez Restrepo, Hernán Darío Vargas Cardonay, Jocelyn Chanussot
http://arxiv.org/abs/2004.00786v1
• [cs.CV]Improving 3D Object Detection through Progressive Population Based Augmentation
Shuyang Cheng, Zhaoqi Leng, Ekin Dogus Cubuk, Barret Zoph, Chunyan Bai, Jiquan Ngiam, Yang Song, Benjamin Caine, Vijay Vasudevan, Congcong Li, Quoc V. Le, Jonathon Shlens, Dragomir Anguelov
http://arxiv.org/abs/2004.00831v1
• [cs.CV]Learning Longterm Representations for Person Re-Identification Using Radio Signals
Lijie Fan, Tianhong Li, Rongyao Fang, Rumen Hristov, Yuan Yuan, Dina Katabi
http://arxiv.org/abs/2004.01091v1
• [cs.CV]Learning Unsupervised Hierarchical Part Decomposition of 3D Objects from a Single RGB Image
Despoina Paschalidou, Luc van Gool, Andreas Geiger
http://arxiv.org/abs/2004.01176v1
• [cs.CV]Learning to See Through Obstructions
Yu-Lun Liu, Wei-Sheng Lai, Ming-Hsuan Yang, Yung-Yu Chuang, Jia-Bin Huang
http://arxiv.org/abs/2004.01180v1
• [cs.CV]Learning to Segment the Tail
Xinting Hu, Yi Jiang, Kaihua Tang, Jingyuan Chen, Chunyan Miao, Hanwang Zhang
http://arxiv.org/abs/2004.00900v1
• [cs.CV]MCEN: Bridging Cross-Modal Gap between Cooking Recipes and Dish Images with Latent Variable Model
Han Fu, Rui Wu, Chenghao Liu, Jianling Sun
http://arxiv.org/abs/2004.01095v1
• [cs.CV]Map-Enhanced Ego-Lane Detection in the Missing Feature Scenarios
Xiaoliang Wang, Yeqiang Qian, Chunxiang Wang, Ming Yang
http://arxiv.org/abs/2004.01101v1
• [cs.CV]Memory-Efficient Incremental Learning Through Feature Adaptation
Ahmet Iscen, Jeffrey Zhang, Svetlana Lazebnik, Cordelia Schmid
http://arxiv.org/abs/2004.00713v1
• [cs.CV]Model-based disentanglement of lens occlusions
Fabio Pizzati, Pietro Cerri, Raoul de Charette
http://arxiv.org/abs/2004.01071v1
• [cs.CV]Monocular Camera Localization in Prior LiDAR Maps with 2D-3D Line Correspondences
Huai Yu, Weikun Zhen, Wen Yang, Ji Zhang, Sebastian Scherer
http://arxiv.org/abs/2004.00740v1
• [cs.CV]Objects of violence: synthetic data for practical ML in human rights investigations
Lachlan Kermode, Jan Freyberg, Alican Akturk, Robert Trafford, Denis Kochetkov, Rafael Pardinas, Eyal Weizman, Julien Cornebise
http://arxiv.org/abs/2004.01030v1
• [cs.CV]Occlusion-Aware Depth Estimation with Adaptive Normal Constraints
Xiaoxiao Long, Lingjie Liu, Christian Theobalt, Wenping Wang
http://arxiv.org/abs/2004.00845v1
• [cs.CV]PaStaNet: Toward Human Activity Knowledge Engine
Yong-Lu Li, Liang Xu, Xinpeng Liu, Xijie Huang, Yue Xu, Shiyi Wang, Hao-Shu Fang, Ze Ma, Mingyang Chen, Cewu Lu
http://arxiv.org/abs/2004.00945v1
• [cs.CV]Physically Realizable Adversarial Examples for LiDAR Object Detection
James Tu, Mengye Ren, Siva Manivasagam, Ming Liang, Bin Yang, Richard Du, Frank Cheng, Raquel Urtasun
http://arxiv.org/abs/2004.00543v2
• [cs.CV]Pixel-BERT: Aligning Image Pixels with Text by Deep Multi-Modal Transformers
Zhicheng Huang, Zhaoyang Zeng, Bei Liu, Dongmei Fu, Jianlong Fu
http://arxiv.org/abs/2004.00849v1
• [cs.CV]ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis
Eu Wern Teh, Terrance DeVries, Graham W. Taylor
http://arxiv.org/abs/2004.01113v1
• [cs.CV]Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition
Luming Tang, Davis Wertheimer, Bharath Hariharan
http://arxiv.org/abs/2004.00705v1
• [cs.CV]Robust Single Rotation Averaging
Seong Hun Lee, Javier Civera
http://arxiv.org/abs/2004.00732v1
• [cs.CV]Robust Single-Image Super-Resolution via CNNs and TV-TV Minimization
Marija Vella, João F. C. Mota
http://arxiv.org/abs/2004.00843v1
• [cs.CV]SSHFD: Single Shot Human Fall Detection with Occluded Joints Resilience
Umar Asif, Stefan Von Cavallar, Jianbin Tang, Stefan Harre
http://arxiv.org/abs/2004.00797v1
• [cs.CV]Scene-Adaptive Video Frame Interpolation via Meta-Learning
Myungsub Choi, Janghoon Choi, Sungyong Baik, Tae Hyun Kim, Kyoung Mu Lee
http://arxiv.org/abs/2004.00779v1
• [cs.CV]Synchronizing Probability Measures on Rotations via Optimal Transport
Tolga Birdal, Michael Arbel, Umut Şimşekli, Leonidas Guibas
http://arxiv.org/abs/2004.00663v1
• [cs.CV]Tracking Objects as Points
Xingyi Zhou, Vladlen Koltun, Philipp Krähenbühl
http://arxiv.org/abs/2004.01177v1
• [cs.CV]Tracking by Instance Detection: A Meta-Learning Approach
Guangting Wang, Chong Luo, Xiaoyan Sun, Zhiwei Xiong, Wenjun Zeng
http://arxiv.org/abs/2004.00830v1
• [cs.CV]Unsupervised Real-world Image Super Resolution via Domain-distance Aware Training
Yunxuan Wei, Shuhang Gu, Yawei Li, Longcun Jin
http://arxiv.org/abs/2004.01178v1
• [cs.CY]A County-level Dataset for Informing the United States’ Response to COVID-19
Benjamin D. Killeen, Jie Ying Wu, Kinjal Shah, Anna Zapaishchykova, Philipp Nikutta, Aniruddha Tamhane, Shreya Chakraborty, Jinchi Wei, Tiger Gao, Mareike Thies, Mathias Unberath
http://arxiv.org/abs/2004.00756v1
• [cs.CY]Best Practices for Transparency in Machine Generated Personalization
Laura Schelenz, Avi Segal, Kobi Gal
http://arxiv.org/abs/2004.00935v1
• [cs.CY]Combating The Machine Ethics Crisis: An Educational Approach
Tai Vu
http://arxiv.org/abs/2004.00817v1
• [cs.CY]Patterns of population displacement during mega-fires in California detected using Facebook Disaster Maps
Shenyue Jia, Seung Hee Kim, Son V. Nghiem, Paul Doherty, Menas Kafatos
http://arxiv.org/abs/2004.01084v1
• [cs.CY]Robots in the Danger Zone: Exploring Public Perception through Engagement
David A. Robb, Muneeb I. Ahmad, Carlo Tiseo, Simona Aracri, Alistair C. McConnell, Vincent Page, Christian Dondrup, Francisco J. Chiyah Garcia, Hai-Nguyen Nguyen, Èric Pairet, Paola Ardón Ramírez, Tushar Semwal, Hazel M. Taylor, Lindsay J. Wilson, David Lane, Helen Hastie, Katrin Lohan
http://arxiv.org/abs/2004.00689v1
• [cs.CY]The Covid19Impact Survey: Assessing the Pulse of the COVID-19 Pandemic in Spain via 24 questions
Nuria Oliver, Xavier Barber, Kirsten Roomp, Kristof Roomp
http://arxiv.org/abs/2004.01014v1
• [cs.DC]A Blockchain-based Decentralized Federated Learning Framework with Committee Consensus
Yuzheng Li, Chuan Chen, Nan Liu, Huawei Huang, Zibin Zheng, Qiang Yan
http://arxiv.org/abs/2004.00773v1
• [cs.DC]Building a Shared Resource HPC Center Across University Schools and Institutes: A Case Study
Glen MacLachlan, Jason Hurlburt, Marco Suarez, Kai Leung Wong, William Burke, Terrence Lewis, Andrew Gallo, Jaroslav Flidr, Raoul Gabiam, Janis Nicholas, Brian Ensor
http://arxiv.org/abs/2003.13629v2
• [cs.DC]Scheduling Parallel-Task Jobs Subject to Packing and Placement Constraints
Mehrnoosh Shafiee, Javad Ghaderi
http://arxiv.org/abs/2004.00518v2
• [cs.GT]No-regret learning dynamics for extensive-form correlated and coarse correlated equilibria
Andrea Celli, Alberto Marchesi, Gabriele Farina, Nicola Gatti
http://arxiv.org/abs/2004.00603v2
• [cs.GT]Provable Sample Complexity Guarantees for Learning of Continuous-Action Graphical Games with Nonparametric Utilities
Adarsh Barik, Jean Honorio
http://arxiv.org/abs/2004.01022v1
• [cs.HC]A Survey on Conversational Recommender Systems
Dietmar Jannach, Ahtsham Manzoor, Wanling Cai, Li Chen
http://arxiv.org/abs/2004.00646v1
• [cs.IT]An Upgrading Algorithm with Optimal Power Law
Or Ordentlich, Ido Tal
http://arxiv.org/abs/2004.00869v1
• [cs.IT]Analysis of Multi-Messages Retransmission Schemes
Alla Khreis, Francesca Bassi, Philippe Ciblat, Pierre Duhamel
http://arxiv.org/abs/2004.01090v1
• [cs.IT]Fundamental Limits of Distributed Encoding
Nastaran Abadi Khooshemehr, Mohammad Ali Maddah-Ali
http://arxiv.org/abs/2004.00811v1
• [cs.IT]Gopala-Hemachandra codes revisited
L. Childers, K. Gopalakrishnan
http://arxiv.org/abs/2004.00821v1
• [cs.IT]Repetition-based NOMA Transmission and Its Outage Probability Analysis
Jinho Choi
http://arxiv.org/abs/2004.00813v1
• [cs.IT]Strong Converse for Testing Against Independence over a Noisy channel
Sreejith Sreekumar, Deniz Gündüz
http://arxiv.org/abs/2004.00775v1
• [cs.LG]Augmented Q Imitation Learning (AQIL)
Xiao Lei Zhang, Anish Agarwal
http://arxiv.org/abs/2004.00993v1
• [cs.LG]Average Reward Adjusted Discounted Reinforcement Learning: Near-Blackwell-Optimal Policies for Real-World Applications
Manuel Schneckenreither
http://arxiv.org/abs/2004.00857v1
• [cs.LG]DeepSumm — Deep Code Summaries using Neural Transformer Architecture
Vivek Gupta
http://arxiv.org/abs/2004.00998v1
• [cs.LG]Exploration of Reinforcement Learning for Event Camera using Car-like Robots
Riku Arakawa, Shintaro Shiba
http://arxiv.org/abs/2004.00801v1
• [cs.LG]Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation
Mengyue Yang, Qingyang Li, Zhiwei Qin, Jieping Ye
http://arxiv.org/abs/2004.01136v1
• [cs.LG]In Automation We Trust: Investigating the Role of Uncertainty in Active Learning Systems
Michael L. Iuzzolino, Tetsumichi Umada, Nisar R. Ahmed, Danielle A. Szafir
http://arxiv.org/abs/2004.00762v1
• [cs.LG]Learning Representations For Images With Hierarchical Labels
Ankit Dhall
http://arxiv.org/abs/2004.00909v1
• [cs.LG]Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T)
Arturo Marban, Daniel Becking, Simon Wiedemann, Wojciech Samek
http://arxiv.org/abs/2004.01077v1
• [cs.LG]Learning to Ask Medical Questions using Reinforcement Learning
Uri Shaham, Tom Zahavy, Cesar Caraballo, Shiwani Mahajan, Daisy Massey, Harlan Krumholz
http://arxiv.org/abs/2004.00994v1
• [cs.LG]Learning to cooperate: Emergent communication in multi-agent navigation
Ivana Kajić, Eser Aygün, Doina Precup
http://arxiv.org/abs/2004.01097v1
• [cs.LG]Mirrorless Mirror Descent: A More Natural Discretization of Riemannian Gradient Flow
Suriya Gunasekar, Blake Woodworth, Nathan Srebro
http://arxiv.org/abs/2004.01025v1
• [cs.LG]Object-Centric Image Generation with Factored Depths, Locations, and Appearances
Titas Anciukevicius, Christoph H. Lampert, Paul Henderson
http://arxiv.org/abs/2004.00642v1
• [cs.LG]Predicting Injectable Medication Adherence via a Smart Sharps Bin and Machine Learning
Yingqi Gu, Akshay Zalkikar, Lara Kelly, Kieran Daly, Tomas E. Ward
http://arxiv.org/abs/2004.01144v1
• [cs.LG]Predictive Bandits
Simon Lindståhl, Alexandre Proutiere, Andreas Johnsson
http://arxiv.org/abs/2004.01141v1
• [cs.LG]Sequential Feature Classification in the Context of Redundancies
Lukas Pfannschmidt, Barbara Hammer
http://arxiv.org/abs/2004.00658v1
• [cs.LG]Sum-product networks: A survey
Iago París, Raquel Sánchez-Cauce, Francisco Javier Díez
http://arxiv.org/abs/2004.01167v1
• [cs.LG]Surrogate-assisted performance tuning of knowledge discovery algorithms: application to clinical pathway evolutionary modeling
Anastasia A. Funkner, Aleksey N. Yakovlev, Sergey V. Kovalchuk
http://arxiv.org/abs/2004.01123v1
• [cs.LG]Understanding Global Feature Contributions Through Additive Importance Measures
Ian Covert, Scott Lundberg, Su-In Lee
http://arxiv.org/abs/2004.00668v1
• [cs.MA]Generate Country-Scale Networks of Interaction from Scattered Statistics
Samuel Thiriot, Jean-Daniel Kant
http://arxiv.org/abs/2004.01031v1
• [cs.MM]Multi-Modal Video Forensic Platform for Investigating Post-Terrorist Attack Scenarios
Alexander Schindler, Andrew Lindley, Anahid Jalali, Martin Boyer, Sergiu Gordea, Ross King
http://arxiv.org/abs/2004.01023v1
• [cs.NE]Device-aware inference operations in SONOS nonvolatile memory arrays
Christopher H. Bennett, T. Patrick Xiao, Ryan Dellana, Vineet Agrawal, Ben Feinberg, Venkatraman Prabhakar, Krishnaswamy Ramkumar, Long Hinh, Swatilekha Saha, Vijay Raghavan, Ramesh Chettuvetty, Sapan Agarwal, Matthew J. Marinella
http://arxiv.org/abs/2004.00802v1
• [cs.NE]Projected Neural Network for a Class of Sparse Regression with Cardinality Penalty
Wenjing Li, Wei Bian
http://arxiv.org/abs/2004.00858v1
• [cs.NI]IoT-Flock: An Open-source Framework for IoT Traffic Generation
Syed Ghazanfar, Faisal Hussain, Atiq Ur Rehman, Ubaid U. Fayyaz, Farrukh Shahzad, Ghalib A. Shah
http://arxiv.org/abs/2004.00844v1
• [cs.NI]Network Orchestration in Mobile Networks via a Synergy of Model-driven and AI-based Techniques
Yantong Wang, Vasilis Friderikos
http://arxiv.org/abs/2004.00660v1
• [cs.PL]On the Principles of Differentiable Quantum Programming Languages
Shaopeng Zhu, Shih-Han Hung, Shouvanik Chakrabarti, Xiaodi Wu
http://arxiv.org/abs/2004.01122v1
• [cs.PL]Proceedings of the 12th International Workshop on Programming Language Approaches to Concurrency- and Communication-cEntric Software
Stephanie Balzer, Luca Padovani
http://arxiv.org/abs/2004.01062v1
• [cs.RO]A Sensorized Multicurved Robot Finger with Data-driven Touch Sensing via Overlapping Light Signals
Pedro Piacenza, Keith Behrman, Benedikt Schifferer, Ioannis Kymissis, Matei Ciocarlie
http://arxiv.org/abs/2004.00685v1
• [cs.RO]A reconfigurable robot workcell for quick set-up of assembly processes
Timotej Gašpar, Miha Deniša, Aleš Ude
http://arxiv.org/abs/2004.00865v1
• [cs.RO]CLASH WRIST — A hardware to increase the capability of CLASH fruit gripper to use environment constraints exploration
Werner Friedl, Maximo A. Roa
http://arxiv.org/abs/2004.00880v1
• [cs.RO]Constrained-Space Optimization and Reinforcement Learning for Complex Tasks
Ya-Yen Tsai, Bo Xiao, Edward Johns, Guang-Zhong Yang
http://arxiv.org/abs/2004.00716v1
• [cs.RO]Enabling End-Users to Deploy Flexible Human-Robot Teams to Factories of the Future
Dominik Riedelbauch, Johannes Hartwig, Dominik Henrich
http://arxiv.org/abs/2004.00862v1
• [cs.RO]Go Fetch: Mobile Manipulation in Unstructured Environments
Kenneth Blomqvist, Michel Breyer, Andrei Cramariuc, Julian Förster, Margarita Grinvald, Florian Tschopp, Jen Jen Chung, Lionel Ott, Juan Nieto, Roland Siegwart
http://arxiv.org/abs/2004.00899v1
• [cs.RO]Human-Guided Planner for Non-Prehensile Manipulation
Rafael Papallas, Mehmet R. Dogar
http://arxiv.org/abs/2004.00946v1
• [cs.RO]Learned and Controlled Autonomous Robotic Exploration in an Extreme, Unknown Environment
Frances Zhu, D. Sawyer Elliott, ZhiDi Yang, Haoyuan Zheng
http://arxiv.org/abs/2004.00749v1
• [cs.RO]Learning Agile Robotic Locomotion Skills by Imitating Animals
Xue Bin Peng, Erwin Coumans, Tingnan Zhang, Tsang-Wei Lee, Jie Tan, Sergey Levine
http://arxiv.org/abs/2004.00784v1
• [cs.RO]Multimodal Material Classification for Robots using Spectroscopy and High Resolution Texture Imaging
Zackory Erickson, Eliot Xing, Bharat Srirangam, Sonia Chernova, Charles C. Kemp
http://arxiv.org/abs/2004.01160v1
• [cs.SC]Explosive Proofs of Mathematical Truths
Scott Viteri, Simon DeDeo
http://arxiv.org/abs/2004.00055v1
• [cs.SE]FaaSten Your Decisions: Classification Framework and Technology Review of Function-as-a-Service Platforms
Vladimir Yussupov, Jacopo Soldani, Uwe Breitenbücher, Antonio Brogi, Frank Leymann
http://arxiv.org/abs/2004.00969v1
• [cs.SI]#ArsonEmergency and Australia’s “Black Summer”: Polarisation and misinformation on social media
Derek Weber, Mehwish Nasim, Lucia Falzon, Lewis Mitchell
http://arxiv.org/abs/2004.00742v1
• [cs.SI]A k-hop Collaborate Game Model: Extended to Community Budgets and Adaptive Non-Submodularity
Jianxiong Guo, Weili Wu
http://arxiv.org/abs/2004.00893v1
• [cs.SI]Analysing the Extent of Misinformation in Cancer Related Tweets
Rakesh Bal, Sayan Sinha, Swastika Dutta, Rishabh Joshi, Sayan Ghosh, Ritam Dutt
http://arxiv.org/abs/2003.13657v3
• [cs.SI]Modeling Dynamic Heterogeneous Network for Link Prediction using Hierarchical Attention with Temporal RNN
Hansheng Xue, Luwei Yang, Wen Jiang, Yi Wei, Yi Hu, Yu Lin
http://arxiv.org/abs/2004.01024v1
• [cs.SI]Spotting political social bots in Twitter: A use case of the 2019 Spanish general election
Javier Pastor-Galindo, Mattia Zago, Pantaleone Nespoli, Sergio López Bernal, Alberto Huertas Celdrán, Manuel Gil Pérez, José A. Ruipérez-Valiente, Gregorio Martínez Pérez, Félix Gómez Mármol
http://arxiv.org/abs/2004.00931v1
• [cs.SI]The Paradox of Information Access: On Modeling Social-Media-Induced Polarization
Chao Xu, Jinyang Li, Tarek Abdelzaher, Heng Ji, Boleslaw K. Szymanski, John Dellaverson
http://arxiv.org/abs/2004.01106v1
• [eess.AS]Improving auditory attention decoding performance of linear and non-linear methods using state-space model
Ali Aroudi, Tobias de Taillez, Simon Doclo
http://arxiv.org/abs/2004.00910v1
• [eess.IV]End-To-End Convolutional Neural Network for 3D Reconstruction of Knee Bones From Bi-Planar X-Ray Images
Yoni Kasten, Daniel Doktofsky, Ilya Kovler
http://arxiv.org/abs/2004.00871v1
• [eess.IV]Image Denoising Using Sparsifying Transform Learning and Weighted Singular Values Minimization
Yanwei Zhao, Ping Yang, Qiu Guan, Jianwei Zheng, Wanliang Wang
http://arxiv.org/abs/2004.00753v1
• [eess.IV]Introducing Anisotropic Minkowski Functionals for Local Structure Analysis and Prediction of Biomechanical Strength of Proximal Femur Specimens
Titas De
http://arxiv.org/abs/2004.01029v1
• [eess.IV]Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipeline
Yu-Lun Liu, Wei-Sheng Lai, Yu-Sheng Chen, Yi-Lung Kao, Ming-Hsuan Yang, Yung-Yu Chuang, Jia-Bin Huang
http://arxiv.org/abs/2004.01179v1
• [eess.SP]Enhance the performance of navigation: A two-stage machine learning approach
Yimin Fan, Zhiyuan Wang, Yuanpeng Lin, Haisheng Tan
http://arxiv.org/abs/2004.00879v1
• [eess.SY]Near Optimality and Tractability in Stochastic Nonlinear Control
Mohamed Naveed Gul Mohamed, Suman Chakravorty
http://arxiv.org/abs/2004.01041v1
• [eess.SY]Safe Feedback Motion Planning: A Contraction Theory and $\mathcal{L}_1$-Adaptive Control Based Approach
Arun Lakshmanan, Aditya Gahlawat, Naira Hovakimyan
http://arxiv.org/abs/2004.01142v1
• [eess.SY]Safe Reinforcement Learning via Projection on a Safe Set: How to Achieve Optimality?
Sebastien Gros, Mario Zanon, Alberto Bemporad
http://arxiv.org/abs/2004.00915v1
• [math.CO]Markov Chain-based Sampling for Exploring RNA Secondary Structure under the Nearest Neighbor Thermodynamic Model
Anna Kirkpatrick, Kalen Patton
http://arxiv.org/abs/2004.01089v1
• [math.CO]Power Hadamard matrices and Plotkin-optimal p-ary codes
Damla Acar, Oğuz Yayla
http://arxiv.org/abs/2004.00771v1
• [math.NA]Bayesian ODE Solvers: The Maximum A Posteriori Estimate
Filip Tronarp, Simo Sarkka, Philipp Hennig
http://arxiv.org/abs/2004.00623v1
• [math.OC]Fractional Deep Neural Network via Constrained Optimization
Harbir Antil, Ratna Khatri, Rainald Löhner, Deepanshu Verma
http://arxiv.org/abs/2004.00719v1
• [math.PR]Kernel autocovariance operators of stationary processes: Estimation and convergence
Mattes Mollenhauer, Stefan Klus, Christof Schütte, Péter Koltai
http://arxiv.org/abs/2004.00891v1
• [math.PR]Stopping explosion by penalising transmission to hubs in scale-free spatial random graphs
Júlia Komjáthy, John Lapinskas, Johannes Lengler
http://arxiv.org/abs/2004.01149v1
• [nlin.AO]Neuronal Sequence Models for Bayesian Online Inference
Sascha Frölich, Dimitrije Marković, Stefan J. Kiebel
http://arxiv.org/abs/2004.00930v1
• [q-bio.NC]A macro agent and its actions
Larissa Albantakis, Francesco Massari, Maggie Beheler-Amass, Giulio Tononi
http://arxiv.org/abs/2004.00058v1
• [q-bio.PE]Coronavirus Covid-19 spreading in Italy: optimizing an epidemiological model with dynamic social distancing through Differential Evolution
I. De Falco, A. Della Cioppa, U. Scafuri, E. Tarantino
http://arxiv.org/abs/2004.00553v2
• [q-bio.QM]DeepSIBA: Chemical Structure-based Inference of Biological Alterations
C. Fotis, N. Meimetis, A. Sardis, L. G. Alexopoulos
http://arxiv.org/abs/2004.01028v1
• [quant-ph]Single Quantum Deletion Error-Correcting Codes
Ayumu Nakayama, Manabu Hagiwara
http://arxiv.org/abs/2004.00814v1
• [stat.AP]Detecting Suspected Epidemic Cases Using Trajectory Big Data
Chuansai Zhou, Wen Yuan, Jun Wang, Haiyong Xu, Yong Jiang, Xinmin Wang, Qiuzi Han Wen, Pingwen Zhang
http://arxiv.org/abs/2004.00908v1
• [stat.AP]Incorporating travel behavior regularity into passenger flow forecasting
Zhanhong Cheng, Martin Trepanier, Lijun Sun
http://arxiv.org/abs/2004.00992v1
• [stat.AP]Spatiotemporal analysis of urban heatwaves using Tukey g-and-h random field models
Daisuke Murakami, Gareth W. Peters, Tomoko Matsui, Yoshiki Yamagata
http://arxiv.org/abs/2004.00852v1
• [stat.CO]An approximate {KLD} based experimental design for models with intractable likelihoods
Ziqiao Ao, Jinglai Li
http://arxiv.org/abs/2004.00715v1
• [stat.CO]Distributed Bayesian clustering
Hanyu Song, Yingjian Wang, David B. Dunson
http://arxiv.org/abs/2003.13936v1
• [stat.ME]A Monte Carlo comparison of categorical tests of independence
Abdulaziz Alenazi
http://arxiv.org/abs/2004.00973v1
• [stat.ME]An Approximate Quasi-Likelihood Approach for Error-Prone Failure Time Outcomes and Exposures
Lillian A. Boe, Lesley F. Tinker, Pamela A. Shaw
http://arxiv.org/abs/2004.01112v1
• [stat.ME]Bayesian model selection approach for colored graphical Gaussian models
Qiong Li, Xin Gao, Helene Massam
http://arxiv.org/abs/2004.00764v1
• [stat.ME]Classification of Functional Data by Detecting the Discrepancy of Second Moment Structure of Scaled functions
Shuhao Jiao, Ron D. Frostig, Hernando Ombao
http://arxiv.org/abs/2004.00855v1
• [stat.ME]Duality between Approximate Bayesian Methods and Prior Robustness
Chaitanya Joshi, Fabrizio Ruggeri
http://arxiv.org/abs/2004.00796v1
• [stat.ME]Integrative High Dimensional Multiple Testing with Heterogeneity under Data Sharing Constraints
Molei Liu, Yin Xia, Tianxi Cai, Kelly Cho
http://arxiv.org/abs/2004.00816v1
• [stat.ME]On Interactions Between Observed and Unobserved Covariates in Matched Observational Studies
Siyu Heng, Dylan S. Small
http://arxiv.org/abs/2004.00766v1
• [stat.ME]Pattern graphs: a graphical approach to nonmonotone missing data
Yen-Chi Chen
http://arxiv.org/abs/2004.00744v1
• [stat.ME]Sequential online subsampling for thinning experimental designs
Luc Pronzato, HaiYing Wang
http://arxiv.org/abs/2004.00792v1
• [stat.ME]Stochastic modeling and estimation of COVID-19 population dynamics
Nikolay M. Yanev, Vessela K. Stoimenova, Dimitar V. Atanasov
http://arxiv.org/abs/2004.00941v1
• [stat.ML]Identification Methods With Arbitrary Interventional Distributions as Inputs
Jaron J. R. Lee, Ilya Shpitser
http://arxiv.org/abs/2004.01157v1
• [stat.ML]Projection Pursuit Gaussian Process Regression
Gecheng Chen, Rui Tuo
http://arxiv.org/abs/2004.00667v1
• [stat.ML]Randomized Kernel Multi-view Discriminant Analysis
Xiaoyun Li, Jie Gui, Ping Li
http://arxiv.org/abs/2004.01143v1