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