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.ET - 新兴技术 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.PL - 编程语言 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 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 q-bio.QM - 定量方法 quant-ph - 量子物理 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]AI and Wargaming
    • [cs.AI]Conditional Hybrid GAN for Sequence Generation
    • [cs.AI]EM-RBR: a reinforced framework for knowledge graph completion from reasoning perspective
    • [cs.AI]On the Tractability of SHAP Explanations
    • [cs.AI]Probably Approximately Correct Explanations of Machine Learning Models via Syntax-Guided Synthesis
    • [cs.AI]RLzoo: A Comprehensive and Adaptive Reinforcement Learning Library
    • [cs.AI]TotalBotWar: A New Pseudo Real-time Multi-action Game Challenge and Competition for AI
    • [cs.CL]Dr. Summarize: Global Summarization of Medical Dialogue by Exploiting Local Structures
    • [cs.CL]FarsTail: A Persian Natural Language Inference Dataset
    • [cs.CL]Generating similes like a Pro: A Style Transfer Approach for Simile Generation
    • [cs.CL]Generation-Augmented Retrieval for Open-domain Question Answering
    • [cs.CL]Hierarchical GPT with Congruent Transformers for Multi-Sentence Language Models
    • [cs.CL]NEU at WNUT-2020 Task 2: Data Augmentation To Tell BERT That Death Is Not Necessarily Informative
    • [cs.CL]Principal Components of the Meaning
    • [cs.CL]RECON: Relation Extraction using Knowledge Graph Context in a Graph Neural Network
    • [cs.CL]Small but Mighty: New Benchmarks for Split and Rephrase
    • [cs.CL]The birth of Romanian BERT
    • [cs.CL]Unsupervised Parallel Corpus Mining on Web Data
    • [cs.CL]fastHan: A BERT-based Joint Many-Task Toolkit for Chinese NLP
    • [cs.CR]The Hidden Vulnerability of Watermarking for Deep Neural Networks
    • [cs.CV]$σ^2$R Loss: a Weighted Loss by Multiplicative Factors using Sigmoidal Functions
    • [cs.CV]6-DoF Grasp Planning using Fast 3D Reconstruction and Grasp Quality CNN
    • [cs.CV]Accelerating Search on Binary Codes in Weighted Hamming Space
    • [cs.CV]Commands 4 Autonomous Vehicles (C4AV) Workshop Summary
    • [cs.CV]Conditional Image Generation with One-Vs-All Classifier
    • [cs.CV]Consistency Regularization with High-dimensional Non-adversarial Source-guided Perturbation for Unsupervised Domain Adaptation in Segmentation
    • [cs.CV]Contextual Semantic Interpretability
    • [cs.CV]Deep Learning for 3D Point Cloud Understanding: A Survey
    • [cs.CV]DeepRemaster: Temporal Source-Reference Attention Networks for Comprehensive Video Enhancement
    • [cs.CV]DeltaGAN: Towards Diverse Few-shot Image Generation with Sample-Specific Delta
    • [cs.CV]Densely Guided Knowledge Distillation using Multiple Teacher Assistants
    • [cs.CV]Face Sketch Synthesis with Style Transfer using Pyramid Column Feature
    • [cs.CV]Faster Gradient-based NAS Pipeline Combining Broad Scalable Architecture with Confident Learning Rate
    • [cs.CV]IDA: Improved Data Augmentation Applied to Salient Object Detection
    • [cs.CV]Identification of Abnormal States in Videos of Ants Undergoing Social Phase Change
    • [cs.CV]Image Captioning with Attention for Smart Local Tourism using EfficientNet
    • [cs.CV]Learning Emotional-Blinded Face Representations
    • [cs.CV]Learning Unseen Emotions from Gestures via Semantically-Conditioned Zero-Shot Perception with Adversarial Autoencoders
    • [cs.CV]Light Direction and Color Estimation from Single Image with Deep Regression
    • [cs.CV]MUTANT: A Training Paradigm for Out-of-Distribution Generalization in Visual Question Answering
    • [cs.CV]Moving object detection for visual odometry in a dynamic environment based on occlusion accumulation
    • [cs.CV]Multi-Resolution Graph Neural Network for Large-Scale Pointcloud Segmentation
    • [cs.CV]Objective, Probabilistic, and Generalized Noise Level Dependent Classifications of sets of more or less 2D Periodic Images into Plane Symmetry Groups
    • [cs.CV]PMVOS: Pixel-Level Matching-Based Video Object Segmentation
    • [cs.CV]Performance Monitoring of Object Detection During Deployment
    • [cs.CV]Preparing for the Worst: Making Networks Less Brittle with Adversarial Batch Normalization
    • [cs.CV]Progressive Semantic-Aware Style Transformation for Blind Face Restoration
    • [cs.CV]Reinforcement Learning for Weakly Supervised Temporal Grounding of Natural Language in Untrimmed Videos
    • [cs.CV]Searching for Low-Bit Weights in Quantized Neural Networks
    • [cs.CV]Smartphone Camera De-identification while Preserving Biometric Utility
    • [cs.CV]Synthetic Convolutional Features for Improved Semantic Segmentation
    • [cs.CV]TopNet: Topology Preserving Metric Learning for Vessel Tree Reconstruction and Labelling
    • [cs.CY]Making Sense of the Robotized Pandemic Response: A Comparison of Global and Canadian Robot Deployments and Success Factors
    • [cs.DC]Accelerating Domain Propagation: an Efficient GPU-Parallel Algorithm over Sparse Matrices
    • [cs.DC]Approximate Majority With Catalytic Inputs
    • [cs.DC]Building Containerized Environments for Reproducibility and Traceability of Scientific Workflows
    • [cs.DC]C-Balancer: A System for Container Profiling and Scheduling
    • [cs.DC]Prisoners, Rooms, and Lightswitches
    • [cs.ET]On the spatiotemporal behavior in biology-mimicking computing systems
    • [cs.IR]A Knowledge Graph based Approach for Mobile Application Recommendation
    • [cs.IT]Bounds for Learning Lossless Source Coding
    • [cs.IT]Higher Rates and Information-Theoretic Analysis for the RLWE Channel
    • [cs.IT]Improved Coding over Sets for DNA-Based Data Storage
    • [cs.IT]Improved recovery guarantees and sampling strategies for TV minimization in compressive imaging
    • [cs.IT]Low Density Parity Check Code (LDPC Codes) Overview
    • [cs.IT]On More General Distributions of Random Binning for Slepian-Wolf Encoding
    • [cs.IT]On the Boomerang Uniformity of Permutations of Low Carlitz Rank
    • [cs.IT]On the Capacity Enlargement of Gaussian Broadcast Channels with Passive Noisy Feedback
    • [cs.IT]Practical Dynamic SC-Flip Polar Decoders: Algorithm and Implementation
    • [cs.IT]Quickest Change Detection with Privacy Constraint
    • [cs.IT]The Capacity of Multi-user Private Information Retrieval for Computationally Limited Databases
    • [cs.IT]The Stability of Low-Density Parity-Check Codes and Some of Its Consequences
    • [cs.IT]The basins of attraction of the global minimizers of non-convex inverse problems with low-dimensional models in infinite dimension
    • [cs.LG]A Framework of Randomized Selection Based Certified Defenses Against Data Poisoning Attacks
    • [cs.LG]Compact Learning for Multi-Label Classification
    • [cs.LG]Federated Learning with Nesterov Accelerated Gradient Momentum Method
    • [cs.LG]GRAC: Self-Guided and Self-Regularized Actor-Critic
    • [cs.LG]GrateTile: Efficient Sparse Tensor Tiling for CNN Processing
    • [cs.LG]HTMRL: Biologically Plausible Reinforcement Learning with Hierarchical Temporal Memory
    • [cs.LG]Pruning Neural Networks at Initialization: Why are We Missing the Mark?
    • [cs.LG]Recurrent Graph Tensor Networks
    • [cs.LG]Search and Rescue with Airborne Optical Sectioning
    • [cs.LG]The Next Big Thing(s) in Unsupervised Machine Learning: Five Lessons from Infant Learning
    • [cs.LG]Time-series Imputation and Prediction with Bi-Directional Generative Adversarial Networks
    • [cs.NE]A Study of Genetic Algorithms for Hyperparameter Optimization of Neural Networks in Machine Translation
    • [cs.NE]Generating Efficient DNN-Ensembles with Evolutionary Computation
    • [cs.NE]Low-Power Low-Latency Keyword Spotting and Adaptive Control with a SpiNNaker 2 Prototype and Comparison with Loihi
    • [cs.PL]A Visual Language for Composable Inductive Programming
    • [cs.RO]Counterfactual Explanation and Causal Inference in Service of Robustness in Robot Control
    • [cs.RO]Leveraging Multiple Environments for Learning and Decision Making: a Dismantling Use Case
    • [cs.RO]Multi-modal Experts Network for Autonomous Driving
    • [cs.RO]Pedestrian Motion Tracking by Using Inertial Sensors on the Smartphone
    • [cs.RO]Pose Correction Algorithm for Relative Frames between Keyframes in SLAM
    • [cs.SD]Optimizing Speech Emotion Recognition using Manta-Ray Based Feature Selection
    • [cs.SE]Gateway Controller with Deep Sensing: Learning to be Autonomic in Intelligent Internet of Things
    • [cs.SE]Serverless Applications: Why, When, and How?
    • [cs.SE]Towards Full-line Code Completion with Neural Language Models
    • [cs.SI]A Social Network of Russian “Kompromat”
    • [cs.SI]Impact and dynamics of hate and counter speech online
    • [cs.SI]The Infinity Mirror Test for Graph Models
    • [eess.AS]X-DC: Explainable Deep Clustering based on Learnable Spectrogram Templates
    • [eess.IV]AdderSR: Towards Energy Efficient Image Super-Resolution
    • [eess.IV]An Analysis by Synthesis Method that Allows Accurate Spatial Modeling of Thickness of Cortical Bone from Clinical QCT
    • [eess.IV]Predicting molecular phenotypes from histopathology images: a transcriptome-wide expression-morphology analysis in breast cancer
    • [eess.IV]Residual Spatial Attention Network for Retinal Vessel Segmentation
    • [eess.IV]SCREENet: A Multi-view Deep Convolutional Neural Network for Classification of High-resolution Synthetic Mammographic Screening Scans
    • [eess.SP]Asymptotic Analysis of ADMM for Compressed Sensing
    • [eess.SP]Automated Stroke Rehabilitation Assessment using Wearable Accelerometers in Free-Living Environments
    • [math.OC]Modifier Adaptation Meets Bayesian Optimization and Derivative-Free Optimization
    • [math.OC]Observers Design for Inertial Navigation Systems: A Brief Tutorial
    • [math.OC]SISTA: learning optimal transport costs under sparsity constraints
    • [math.PR]A computational framework for evaluating the role of mobility on the propagation of epidemics on point processes
    • [math.ST]A note on optimal designs for estimating the slope of a polynomial regression
    • [math.ST]Forecasting time series with encoder-decoder neural networks
    • [q-bio.QM]Chemical Property Prediction Under Experimental Biases
    • [quant-ph]Equivalence of three quantum algorithms: Privacy amplification, error correction, and data compression
    • [stat.AP]Estimating the treatment effect of the juvenile stay-at-home order on SARS-CoV-2 infection spread in Saline County, Arkansas
    • [stat.AP]On the limitations of probabilistic claims about the probative value of mixed DNA profile evidence
    • [stat.ME]Additive Models for Symmetric Positive-Definite Matrices, Riemannian Manifolds and Lie groups
    • [stat.ME]An Independence Test Based on Recurrence Rates. An empirical study and applications to real data
    • [stat.ME]Detection of Change Points in Piecewise Polynomial Signals Using Trend Filtering
    • [stat.ME]Estimation of Health and Demographic Indicators with Incomplete Geographic Information
    • [stat.ME]Multivariate binary probability distribution in the Grassmann formalism
    • [stat.ME]Nonparametric estimation of directional highest density regions
    • [stat.ME]Sequential changepoint detection for label shift in classification
    • [stat.ME]The assessment of replication success based on relative effect size
    • [stat.ML]Causal Clustering for 1-Factor Measurement Models on Data with Various Types
    • [stat.ML]Deviation bound for non-causal machine learning

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    • [cs.AI]AI and Wargaming
    James Goodman, Sebastian Risi, Simon Lucas
    http://arxiv.org/abs/2009.08922v1

    • [cs.AI]Conditional Hybrid GAN for Sequence Generation
    Yi Yu, Abhishek Srivastava, Rajiv Ratn Shah
    http://arxiv.org/abs/2009.08616v1

    • [cs.AI]EM-RBR: a reinforced framework for knowledge graph completion from reasoning perspective
    Zhaochong An, Bozhou Chen, Houde Quan, Qihui Lin, Hongzhi Wang
    http://arxiv.org/abs/2009.08656v1

    • [cs.AI]On the Tractability of SHAP Explanations
    Guy Van den Broeck, Anton Lykov, Maximilian Schleich, Dan Suciu
    http://arxiv.org/abs/2009.08634v1

    • [cs.AI]Probably Approximately Correct Explanations of Machine Learning Models via Syntax-Guided Synthesis
    Daniel Neider, Bishwamittra Ghosh
    http://arxiv.org/abs/2009.08770v1

    • [cs.AI]RLzoo: A Comprehensive and Adaptive Reinforcement Learning Library
    Zihan Ding, Tianyang Yu, Yanhua Huang, Hongming Zhang, Luo Mai, Hao Dong
    http://arxiv.org/abs/2009.08644v1

    • [cs.AI]TotalBotWar: A New Pseudo Real-time Multi-action Game Challenge and Competition for AI
    Alejandro Estaben, César Díaz, Raul Montoliu, Diego Pérez-Liebana
    http://arxiv.org/abs/2009.08696v1

    • [cs.CL]Dr. Summarize: Global Summarization of Medical Dialogue by Exploiting Local Structures
    Anirudh Joshi, Namit Katariya, Xavier Amatriain, Anitha Kannan
    http://arxiv.org/abs/2009.08666v1

    • [cs.CL]FarsTail: A Persian Natural Language Inference Dataset
    Hossein Amirkhani, Mohammad Azari Jafari, Azadeh Amirak, Zohreh Pourjafari, Soroush Faridan Jahromi, Zeinab Kouhkan
    http://arxiv.org/abs/2009.08820v1

    • [cs.CL]Generating similes like a Pro: A Style Transfer Approach for Simile Generation
    Tuhin Chakrabarty, Smaranda Muresan, Nanyun Peng
    http://arxiv.org/abs/2009.08942v1

    • [cs.CL]Generation-Augmented Retrieval for Open-domain Question Answering
    Yuning Mao, Pengcheng He, Xiaodong Liu, Yelong Shen, Jianfeng Gao, Jiawei Han, Weizhu Chen
    http://arxiv.org/abs/2009.08553v1

    • [cs.CL]Hierarchical GPT with Congruent Transformers for Multi-Sentence Language Models
    Jihyeon Roh, Huiseong Gim, Soo-Young Lee
    http://arxiv.org/abs/2009.08636v1

    • [cs.CL]NEU at WNUT-2020 Task 2: Data Augmentation To Tell BERT That Death Is Not Necessarily Informative
    Kumud Chauhan
    http://arxiv.org/abs/2009.08590v1

    • [cs.CL]Principal Components of the Meaning
    Neslihan Suzen, Alexander Gorban, Jeremy Levesley, Evgeny Mirkes
    http://arxiv.org/abs/2009.08859v1

    • [cs.CL]RECON: Relation Extraction using Knowledge Graph Context in a Graph Neural Network
    Anson Bastos, Abhishek Nadgeri, Kuldeep Singh, Isaiah Onando Mulang’, Saeedeh Shekarpour, Johannes Hoffart
    http://arxiv.org/abs/2009.08694v1

    • [cs.CL]Small but Mighty: New Benchmarks for Split and Rephrase
    Li Zhang, Huaiyu Zhu, Siddhartha Brahma, Yunyao Li
    http://arxiv.org/abs/2009.08560v1

    • [cs.CL]The birth of Romanian BERT
    Stefan Daniel Dumitrescu, Andrei-Marius Avram, Sampo Pyysalo
    http://arxiv.org/abs/2009.08712v1

    • [cs.CL]Unsupervised Parallel Corpus Mining on Web Data
    Guokun Lai, Zihang Dai, Yiming Yang
    http://arxiv.org/abs/2009.08595v1

    • [cs.CL]fastHan: A BERT-based Joint Many-Task Toolkit for Chinese NLP
    Zhichao Geng, Hang Yan, Xipeng Qiu, Xuanjing Huang
    http://arxiv.org/abs/2009.08633v1

    • [cs.CR]The Hidden Vulnerability of Watermarking for Deep Neural Networks
    Shangwei Guo, Tianwei Zhang, Han Qiu, Yi Zeng, Tao Xiang, Yang Liu
    http://arxiv.org/abs/2009.08697v1

    • [cs.CV]$σ^2$R Loss: a Weighted Loss by Multiplicative Factors using Sigmoidal Functions
    Riccardo La Grassa, Ignazio Gallo, Nicola Landro
    http://arxiv.org/abs/2009.08796v1

    • [cs.CV]6-DoF Grasp Planning using Fast 3D Reconstruction and Grasp Quality CNN
    Yahav Avigal, Samuel Paradis, Harry Zhang
    http://arxiv.org/abs/2009.08618v1

    • [cs.CV]Accelerating Search on Binary Codes in Weighted Hamming Space
    Zhenyu Weng, Yuesheng Zhu, Ruixin Liu
    http://arxiv.org/abs/2009.08591v1

    • [cs.CV]Commands 4 Autonomous Vehicles (C4AV) Workshop Summary
    Thierry Deruyttere, Simon Vandenhende, Dusan Grujicic, Yu Liu, Luc Van Gool, Matthew Blaschko, Tinne Tuytelaars, Marie-Francine Moens
    http://arxiv.org/abs/2009.08792v1

    • [cs.CV]Conditional Image Generation with One-Vs-All Classifier
    Xiangrui Xu, Yaqin Li, Cao Yuan
    http://arxiv.org/abs/2009.08688v1

    • [cs.CV]Consistency Regularization with High-dimensional Non-adversarial Source-guided Perturbation for Unsupervised Domain Adaptation in Segmentation
    Kaihong Wang, Chenhongyi Yang, Margrit Betke
    http://arxiv.org/abs/2009.08610v1

    • [cs.CV]Contextual Semantic Interpretability
    Diego Marcos, Ruth Fong, Sylvain Lobry, Remi Flamary, Nicolas Courty, Devis Tuia
    http://arxiv.org/abs/2009.08720v1

    • [cs.CV]Deep Learning for 3D Point Cloud Understanding: A Survey
    Haoming Lu, Humphrey Shi
    http://arxiv.org/abs/2009.08920v1

    • [cs.CV]DeepRemaster: Temporal Source-Reference Attention Networks for Comprehensive Video Enhancement
    Satoshi Iizuka, Edgar Simo-Serra
    http://arxiv.org/abs/2009.08692v1

    • [cs.CV]DeltaGAN: Towards Diverse Few-shot Image Generation with Sample-Specific Delta
    Yan Hong, Li Niu, Jianfu Zhang, Jing Liang, Liqing Zhang
    http://arxiv.org/abs/2009.08753v1

    • [cs.CV]Densely Guided Knowledge Distillation using Multiple Teacher Assistants
    Wonchul Son, Jaemin Na, Wonjun Hwang
    http://arxiv.org/abs/2009.08825v1

    • [cs.CV]Face Sketch Synthesis with Style Transfer using Pyramid Column Feature
    Chaofeng Chen, Xiao Tan, Kwan-Yee K. Wong
    http://arxiv.org/abs/2009.08679v1

    • [cs.CV]Faster Gradient-based NAS Pipeline Combining Broad Scalable Architecture with Confident Learning Rate
    Ding Zixiang, Chen Yaran, Li Nannan, Zhao Dongbin
    http://arxiv.org/abs/2009.08886v1

    • [cs.CV]IDA: Improved Data Augmentation Applied to Salient Object Detection
    Daniel V. Ruiz, Bruno A. Krinski, Eduardo Todt
    http://arxiv.org/abs/2009.08845v1

    • [cs.CV]Identification of Abnormal States in Videos of Ants Undergoing Social Phase Change
    Taeyeong Choi, Benjamin Pyenson, Juergen Liebig, Theodore P. Pavlic
    http://arxiv.org/abs/2009.08626v1

    • [cs.CV]Image Captioning with Attention for Smart Local Tourism using EfficientNet
    Dhomas Hatta Fudholi, Yurio Windiatmoko, Nurdi Afrianto, Prastyo Eko Susanto, Magfirah Suyuti, Ahmad Fathan Hidayatullah, Ridho Rahmadi
    http://arxiv.org/abs/2009.08899v1

    • [cs.CV]Learning Emotional-Blinded Face Representations
    Alejandro Peña, Julian Fierrez, Agata Lapedriza, Aythami Morales
    http://arxiv.org/abs/2009.08704v1

    • [cs.CV]Learning Unseen Emotions from Gestures via Semantically-Conditioned Zero-Shot Perception with Adversarial Autoencoders
    Abhishek Banerjee, Uttaran Bhattacharya, Aniket Bera
    http://arxiv.org/abs/2009.08906v1

    • [cs.CV]Light Direction and Color Estimation from Single Image with Deep Regression
    Hassan A. Sial, Ramon Baldrich, Maria Vanrell, Dimitris Samaras
    http://arxiv.org/abs/2009.08941v1

    • [cs.CV]MUTANT: A Training Paradigm for Out-of-Distribution Generalization in Visual Question Answering
    Tejas Gokhale, Pratyay Banerjee, Chitta Baral, Yezhou Yang
    http://arxiv.org/abs/2009.08566v1

    • [cs.CV]Moving object detection for visual odometry in a dynamic environment based on occlusion accumulation
    Haram Kim, Pyojin Kim, H. Jin Kim
    http://arxiv.org/abs/2009.08746v1

    • [cs.CV]Multi-Resolution Graph Neural Network for Large-Scale Pointcloud Segmentation
    Liuyue Xie, Tomotake Furuhata, Kenji Shimada
    http://arxiv.org/abs/2009.08924v1

    • [cs.CV]Objective, Probabilistic, and Generalized Noise Level Dependent Classifications of sets of more or less 2D Periodic Images into Plane Symmetry Groups
    Andrew Dempsey, Peter Moeck
    http://arxiv.org/abs/2009.08539v1

    • [cs.CV]PMVOS: Pixel-Level Matching-Based Video Object Segmentation
    Suhwan Cho, Heansung Lee, Sungmin Woo, Sungjun Jang, Sangyoun Lee
    http://arxiv.org/abs/2009.08855v1

    • [cs.CV]Performance Monitoring of Object Detection During Deployment
    Quazi Marufur Rahman, Niko Sünderhauf, Feras Dayoub
    http://arxiv.org/abs/2009.08650v1

    • [cs.CV]Preparing for the Worst: Making Networks Less Brittle with Adversarial Batch Normalization
    Manli Shu, Zuxuan Wu, Micah Goldblum, Tom Goldstein
    http://arxiv.org/abs/2009.08965v1

    • [cs.CV]Progressive Semantic-Aware Style Transformation for Blind Face Restoration
    Chaofeng Chen, Xiaoming Li, Lingbo Yang, Xianhui Lin, Lei Zhang, Kwan-Yee K. Wong
    http://arxiv.org/abs/2009.08709v1

    • [cs.CV]Reinforcement Learning for Weakly Supervised Temporal Grounding of Natural Language in Untrimmed Videos
    Jie Wu, Guanbin Li, Xiaoguang Han, Liang Lin
    http://arxiv.org/abs/2009.08614v1

    • [cs.CV]Searching for Low-Bit Weights in Quantized Neural Networks
    Zhaohui Yang, Yunhe Wang, Kai Han, Chunjing Xu, Chao Xu, Dacheng Tao, Chang Xu
    http://arxiv.org/abs/2009.08695v1

    • [cs.CV]Smartphone Camera De-identification while Preserving Biometric Utility
    Sudipta Banerjee, Arun Ross
    http://arxiv.org/abs/2009.08511v1

    • [cs.CV]Synthetic Convolutional Features for Improved Semantic Segmentation
    Yang He, Bernt Schiele, Mario Fritz
    http://arxiv.org/abs/2009.08849v1

    • [cs.CV]TopNet: Topology Preserving Metric Learning for Vessel Tree Reconstruction and Labelling
    Deepak Keshwani, Yoshiro Kitamura, Satoshi Ihara, Satoshi Iizuka, Edgar Simo-Serra
    http://arxiv.org/abs/2009.08674v1

    • [cs.CY]Making Sense of the Robotized Pandemic Response: A Comparison of Global and Canadian Robot Deployments and Success Factors
    T. Barfoot, J. Burgner-Kahrs, E. Diller, A. Garg, A. Goldenberg, J. Kelly, X. Liu, H. E. Naguib, G. Nejat, A. P. Schoellig, F. Shkurti, H. Siegel, Y. Sun, S. L. Waslander.
    http://arxiv.org/abs/2009.08577v1

    • [cs.DC]Accelerating Domain Propagation: an Efficient GPU-Parallel Algorithm over Sparse Matrices
    Boro Sofranac, Ambros Gleixner, Sebastian Pokutta
    http://arxiv.org/abs/2009.07785v2

    • [cs.DC]Approximate Majority With Catalytic Inputs
    Talley Amir, James Aspnes, John Lazarsfeld
    http://arxiv.org/abs/2009.08847v1

    • [cs.DC]Building Containerized Environments for Reproducibility and Traceability of Scientific Workflows
    Paula Olaya, Jay Lofstead, Michela Taufer
    http://arxiv.org/abs/2009.08495v1

    • [cs.DC]C-Balancer: A System for Container Profiling and Scheduling
    Akshay Dhumal, Dharanipragada Janakiram
    http://arxiv.org/abs/2009.08912v1

    • [cs.DC]Prisoners, Rooms, and Lightswitches
    Daniel M. Kane, Scott Duke Kominers
    http://arxiv.org/abs/2009.08575v1

    • [cs.ET]On the spatiotemporal behavior in biology-mimicking computing systems
    János Végh, Ádám J. Berki
    http://arxiv.org/abs/2009.08841v1

    • [cs.IR]A Knowledge Graph based Approach for Mobile Application Recommendation
    Mingwei Zhang, Jiawei Zhao, Hai Dong, Ke Deng, Ying Liu
    http://arxiv.org/abs/2009.08621v1

    • [cs.IT]Bounds for Learning Lossless Source Coding
    Anders Host-Madsen
    http://arxiv.org/abs/2009.08562v1

    • [cs.IT]Higher Rates and Information-Theoretic Analysis for the RLWE Channel
    Georg Maringer, Sven Puchinger, Antonia Wachter-Zeh
    http://arxiv.org/abs/2009.08681v1

    • [cs.IT]Improved Coding over Sets for DNA-Based Data Storage
    Hengjia Wei, Moshe Schwartz
    http://arxiv.org/abs/2009.08816v1

    • [cs.IT]Improved recovery guarantees and sampling strategies for TV minimization in compressive imaging
    Ben Adcock, Nick Dexter, Qinghong Xu
    http://arxiv.org/abs/2009.08555v1

    • [cs.IT]Low Density Parity Check Code (LDPC Codes) Overview
    Saumya Borwankar, Dhruv Shah
    http://arxiv.org/abs/2009.08645v1

    • [cs.IT]On More General Distributions of Random Binning for Slepian-Wolf Encoding
    Neri Merhav
    http://arxiv.org/abs/2009.08839v1

    • [cs.IT]On the Boomerang Uniformity of Permutations of Low Carlitz Rank
    Jaeseong Jeong, Namhun Koo, Soonhak Kwon
    http://arxiv.org/abs/2009.08612v1

    • [cs.IT]On the Capacity Enlargement of Gaussian Broadcast Channels with Passive Noisy Feedback
    Aditya Narayan Ravi, Sibi Raj B. Pillai, Vinod Prabhakaran, Michèle Wigger
    http://arxiv.org/abs/2009.08765v1

    • [cs.IT]Practical Dynamic SC-Flip Polar Decoders: Algorithm and Implementation
    Furkan Ercan, Thibaud Tonnellier, Nghia Doan, Warren J. Gross
    http://arxiv.org/abs/2009.08547v1

    • [cs.IT]Quickest Change Detection with Privacy Constraint
    Tze Siong Lau, Wee Peng Tay
    http://arxiv.org/abs/2009.08963v1

    • [cs.IT]The Capacity of Multi-user Private Information Retrieval for Computationally Limited Databases
    William Barnhart, Zhi Tian
    http://arxiv.org/abs/2009.08582v1

    • [cs.IT]The Stability of Low-Density Parity-Check Codes and Some of Its Consequences
    Wei Liu, Rüdiger Urbanke
    http://arxiv.org/abs/2009.08640v1

    • [cs.IT]The basins of attraction of the global minimizers of non-convex inverse problems with low-dimensional models in infinite dimension
    Yann Traonmilin, Jean-François Aujol, Arthur Leclaire
    http://arxiv.org/abs/2009.08670v1

    • [cs.LG]A Framework of Randomized Selection Based Certified Defenses Against Data Poisoning Attacks
    Ruoxin Chen, Jie Li, Chentao Wu, Bin Sheng, Ping Li
    http://arxiv.org/abs/2009.08739v1

    • [cs.LG]Compact Learning for Multi-Label Classification
    Jiaqi Lv, Tianran Wu, Chenglun Peng, Yunpeng Liu, Ning Xu, Xin Geng
    http://arxiv.org/abs/2009.08607v1

    • [cs.LG]Federated Learning with Nesterov Accelerated Gradient Momentum Method
    Zhengjie Yang, Wei Bao, Dong Yuan, Nguyen H. Tran, Albert Y. Zomaya
    http://arxiv.org/abs/2009.08716v1

    • [cs.LG]GRAC: Self-Guided and Self-Regularized Actor-Critic
    Lin Shao, Yifan You, Mengyuan Yan, Qingyun Sun, Jeannette Bohg
    http://arxiv.org/abs/2009.08973v1

    • [cs.LG]GrateTile: Efficient Sparse Tensor Tiling for CNN Processing
    Yu-Sheng Lin, Hung Chang Lu, Yang-Bin Tsao, Yi-Min Chih, Wei-Chao Chen, Shao-Yi Chien
    http://arxiv.org/abs/2009.08685v1

    • [cs.LG]HTMRL: Biologically Plausible Reinforcement Learning with Hierarchical Temporal Memory
    Jakob Struye, Kevin Mets, Steven Latré
    http://arxiv.org/abs/2009.08880v1

    • [cs.LG]Pruning Neural Networks at Initialization: Why are We Missing the Mark?
    Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin
    http://arxiv.org/abs/2009.08576v1

    • [cs.LG]Recurrent Graph Tensor Networks
    Yao Lei Xu, Danilo P. Mandic
    http://arxiv.org/abs/2009.08727v1

    • [cs.LG]Search and Rescue with Airborne Optical Sectioning
    David C. Schedl, Indrajit Kurmi, Oliver Bimber
    http://arxiv.org/abs/2009.08835v1

    • [cs.LG]The Next Big Thing(s) in Unsupervised Machine Learning: Five Lessons from Infant Learning
    Lorijn Zaadnoordijk, Tarek R. Besold, Rhodri Cusack
    http://arxiv.org/abs/2009.08497v1

    • [cs.LG]Time-series Imputation and Prediction with Bi-Directional Generative Adversarial Networks
    Mehak Gupta, Rahmatollah Beheshti
    http://arxiv.org/abs/2009.08900v1

    • [cs.NE]A Study of Genetic Algorithms for Hyperparameter Optimization of Neural Networks in Machine Translation
    Keshav Ganapathy
    http://arxiv.org/abs/2009.08928v1

    • [cs.NE]Generating Efficient DNN-Ensembles with Evolutionary Computation
    Marc Ortiz, Florian Scheidegger, Marc Casas, Cristiano Malossi, Eduard Ayguadé
    http://arxiv.org/abs/2009.08698v1

    • [cs.NE]Low-Power Low-Latency Keyword Spotting and Adaptive Control with a SpiNNaker 2 Prototype and Comparison with Loihi
    Yexin Yan, Terrence C. Stewart, Xuan Choo, Bernhard Vogginger, Johannes Partzsch, Sebastian Hoeppner, Florian Kelber, Chris Eliasmith, Steve Furber, Christian Mayr
    http://arxiv.org/abs/2009.08921v1

    • [cs.PL]A Visual Language for Composable Inductive Programming
    Edward McDaid, Sarah McDaid
    http://arxiv.org/abs/2009.08700v1

    • [cs.RO]Counterfactual Explanation and Causal Inference in Service of Robustness in Robot Control
    Simón C. Smith, Subramanian Ramamoorthy
    http://arxiv.org/abs/2009.08856v1

    • [cs.RO]Leveraging Multiple Environments for Learning and Decision Making: a Dismantling Use Case
    Alejandro Suárez-Hernández, Thierry Gaugry, Javier Segovia-Aguas, Antonin Bernardin, Carme Torras, Maud Marchal, Guillem Alenyà
    http://arxiv.org/abs/2009.08837v1

    • [cs.RO]Multi-modal Experts Network for Autonomous Driving
    Shihong Fang, Anna Choromanska
    http://arxiv.org/abs/2009.08876v1

    • [cs.RO]Pedestrian Motion Tracking by Using Inertial Sensors on the Smartphone
    Yingying Wang, Hu Cheng, Max Q. H. Meng
    http://arxiv.org/abs/2009.08824v1

    • [cs.RO]Pose Correction Algorithm for Relative Frames between Keyframes in SLAM
    Youngseok Jang, Hojoon Shin, H. Jin Kim
    http://arxiv.org/abs/2009.08724v1

    • [cs.SD]Optimizing Speech Emotion Recognition using Manta-Ray Based Feature Selection
    Soham Chattopadhyay, Arijit Dey, Hritam Basak
    http://arxiv.org/abs/2009.08909v1

    • [cs.SE]Gateway Controller with Deep Sensing: Learning to be Autonomic in Intelligent Internet of Things
    Rahim Rahmani, Ramin Firouzi
    http://arxiv.org/abs/2009.08646v1

    • [cs.SE]Serverless Applications: Why, When, and How?
    Simon Eismann, Joel Scheuner, Erwin van Eyk, Maximilian Schwinger, Johannes Grohmann, Cristina L. Abad, Alexandru Iosup
    http://arxiv.org/abs/2009.08173v2

    • [cs.SE]Towards Full-line Code Completion with Neural Language Models
    Wenhan Wang, Sijie Shen, Ge Li, Zhi Jin
    http://arxiv.org/abs/2009.08603v1

    • [cs.SI]A Social Network of Russian “Kompromat”
    Dmitry Zinoviev
    http://arxiv.org/abs/2009.08631v1

    • [cs.SI]Impact and dynamics of hate and counter speech online
    Joshua Garland, Keyan Ghazi-Zahedi, Jean-Gabriel Young, Laurent Hébert-Dufresne, Mirta Galesic
    http://arxiv.org/abs/2009.08392v2

    • [cs.SI]The Infinity Mirror Test for Graph Models
    Satyaki Sikdar, Daniel Gonzalez, Trenton Ford, Tim Weninger
    http://arxiv.org/abs/2009.08925v1

    • [eess.AS]X-DC: Explainable Deep Clustering based on Learnable Spectrogram Templates
    Chihiro Watanabe, Hirokazu Kameoka
    http://arxiv.org/abs/2009.08661v1

    • [eess.IV]AdderSR: Towards Energy Efficient Image Super-Resolution
    Dehua Song, Yunhe Wang, Hanting Chen, Chang Xu, Chunjing Xu, DaCheng Tao
    http://arxiv.org/abs/2009.08891v1

    • [eess.IV]An Analysis by Synthesis Method that Allows Accurate Spatial Modeling of Thickness of Cortical Bone from Clinical QCT
    Stefan Reinhold, Timo Damm, Sebastian Büsse, Stanislav N. Gorb, Claus-C. Glüer, Reinhard Koch
    http://arxiv.org/abs/2009.08664v1

    • [eess.IV]Predicting molecular phenotypes from histopathology images: a transcriptome-wide expression-morphology analysis in breast cancer
    Yinxi Wang, Kimmo Kartasalo, Masi Valkonen, Christer Larsson, Pekka Ruusuvuori, Johan Hartman, Mattias Rantalainen
    http://arxiv.org/abs/2009.08917v1

    • [eess.IV]Residual Spatial Attention Network for Retinal Vessel Segmentation
    Changlu Guo, Márton Szemenyei, Yugen Yi, Wei Zhou, Haodong Bian
    http://arxiv.org/abs/2009.08829v1

    • [eess.IV]SCREENet: A Multi-view Deep Convolutional Neural Network for Classification of High-resolution Synthetic Mammographic Screening Scans
    Saeed Seyyedi, Margaret J. Wong, Debra M. Ikeda, Curtis P. Langlotz
    http://arxiv.org/abs/2009.08563v1

    • [eess.SP]Asymptotic Analysis of ADMM for Compressed Sensing
    Ryo Hayakawa
    http://arxiv.org/abs/2009.08545v1

    • [eess.SP]Automated Stroke Rehabilitation Assessment using Wearable Accelerometers in Free-Living Environments
    Xi Chen, Yu Guan, Jian-Qing Shi, Xiu-Li Du, Janet Eyre
    http://arxiv.org/abs/2009.08798v1

    • [math.OC]Modifier Adaptation Meets Bayesian Optimization and Derivative-Free Optimization
    Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis, Eric Bradford, Jose Eduardo Alves Graciano, Benoit Chachuat
    http://arxiv.org/abs/2009.08819v1

    • [math.OC]Observers Design for Inertial Navigation Systems: A Brief Tutorial
    Miaomiao Wang, Abdelhamid Tayebi
    http://arxiv.org/abs/2009.08569v1

    • [math.OC]SISTA: learning optimal transport costs under sparsity constraints
    Guillaume Carlier, Arnaud Dupuy, Alfred Galichon, Yifei Sun
    http://arxiv.org/abs/2009.08564v1

    • [math.PR]A computational framework for evaluating the role of mobility on the propagation of epidemics on point processes
    François Baccelli, Nithin Ramesan
    http://arxiv.org/abs/2009.08515v1

    • [math.ST]A note on optimal designs for estimating the slope of a polynomial regression
    Holger Dette, Viatcheslav B. Melas, Petr Shpilev
    http://arxiv.org/abs/2009.08853v1

    • [math.ST]Forecasting time series with encoder-decoder neural networks
    Nathawut Phandoidaen, Stefan Richter
    http://arxiv.org/abs/2009.08848v1

    • [q-bio.QM]Chemical Property Prediction Under Experimental Biases
    Yang Liu, Hisashi Kashima
    http://arxiv.org/abs/2009.08687v1

    • [quant-ph]Equivalence of three quantum algorithms: Privacy amplification, error correction, and data compression
    Toyohiro Tsurumaru
    http://arxiv.org/abs/2009.08823v1

    • [stat.AP]Estimating the treatment effect of the juvenile stay-at-home order on SARS-CoV-2 infection spread in Saline County, Arkansas
    Neil Hwang, Shirshendu Chatterjee, Yanming Di, Sharmodeep Bhattacharyya
    http://arxiv.org/abs/2009.08691v1

    • [stat.AP]On the limitations of probabilistic claims about the probative value of mixed DNA profile evidence
    Norman Fenton, Allan Jamieson, Sara Gomes, Martin Neil
    http://arxiv.org/abs/2009.08850v1

    • [stat.ME]Additive Models for Symmetric Positive-Definite Matrices, Riemannian Manifolds and Lie groups
    Zhenhua Lin, Hans-Georg Müller, Byeong U. Park
    http://arxiv.org/abs/2009.08789v1

    • [stat.ME]An Independence Test Based on Recurrence Rates. An empirical study and applications to real data
    Juan Kalemkerian, Diego Fernández
    http://arxiv.org/abs/2009.08883v1

    • [stat.ME]Detection of Change Points in Piecewise Polynomial Signals Using Trend Filtering
    Reza V. Mehrizi, Shojaeddin Chenouri
    http://arxiv.org/abs/2009.08573v1

    • [stat.ME]Estimation of Health and Demographic Indicators with Incomplete Geographic Information
    Katie Wilson, Jon Wakefield
    http://arxiv.org/abs/2009.08543v1

    • [stat.ME]Multivariate binary probability distribution in the Grassmann formalism
    Takashi Arai
    http://arxiv.org/abs/2009.08482v1

    • [stat.ME]Nonparametric estimation of directional highest density regions
    Paula Saavedra-Nieves, Rosa María Crujeiras
    http://arxiv.org/abs/2009.08915v1

    • [stat.ME]Sequential changepoint detection for label shift in classification
    Ciaran Evans, Max G’Sell
    http://arxiv.org/abs/2009.08592v1

    • [stat.ME]The assessment of replication success based on relative effect size
    Leonhard Held, Charlotte Micheloud, Samuel Pawel
    http://arxiv.org/abs/2009.07782v2

    • [stat.ML]Causal Clustering for 1-Factor Measurement Models on Data with Various Types
    Shuyan Wang
    http://arxiv.org/abs/2009.08606v1

    • [stat.ML]Deviation bound for non-causal machine learning
    Rémy Garnier, Raphaël Langhendries
    http://arxiv.org/abs/2009.08905v1