cs.AI - 人工智能 cs.CC - 计算复杂度 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.DL - 数字图书馆 cs.DS - 数据结构与算法 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 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.OC - 优化与控制 math.ST - 统计理论 q-bio.NC - 神经元与认知 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]DeepEnroll: Patient-Trial Matching with Deep Embedding and Entailment Prediction
    • [cs.AI]GLIB: Exploration via Goal-Literal Babbling for Lifted Operator Learning
    • [cs.AI]I Feel I Feel You: A Theory of Mind Experiment in Games
    • [cs.AI]Learning Distributional Programs for Relational Autocompletion
    • [cs.AI]Model-theoretic Characterizations of Existential Rule Languages
    • [cs.AI]Numerical Abstract Persuasion Argumentation for Expressing Concurrent Multi-Agent Negotiations
    • [cs.AI]Proxy Tasks and Subjective Measures Can Be Misleading in Evaluating Explainable AI Systems
    • [cs.CC]On the computational power and complexity of Spiking Neural Networks
    • [cs.CL]A Study of the Tasks and Models in Machine Reading Comprehension
    • [cs.CL]Action Recognition and State Change Prediction in a Recipe Understanding Task Using a Lightweight Neural Network Model
    • [cs.CL]CheckThat! at CLEF 2020: Enabling the Automatic Identification and Verification of Claims in Social Media
    • [cs.CL]Coordinated Reasoning for Cross-Lingual Knowledge Graph Alignment
    • [cs.CL]Multilingual Denoising Pre-training for Neural Machine Translation
    • [cs.CL]Pre-training via Leveraging Assisting Languages and Data Selection for Neural Machine Translation
    • [cs.CL]Transition-Based Dependency Parsing using Perceptron Learner
    • [cs.CL]Variational Hierarchical Dialog Autoencoder for Dialogue State Tracking Data Augmentation
    • [cs.CR]Information set decoding of Lee-metric codes over finite rings
    • [cs.CR]Nowhere to Hide: Cross-modal Identity Leakage between Biometrics and Devices
    • [cs.CR]Sensor-based Continuous Authentication of Smartphones’ Users Using Behavioral Biometrics: A Survey
    • [cs.CV]A Hypersensitive Breast Cancer Detector
    • [cs.CV]A Large Scale Event-based Detection Dataset for Automotive
    • [cs.CV]Active Perception with A Monocular Camera for Multiscopic Vision
    • [cs.CV]Adaptation of a deep learning malignancy model from full-field digital mammography to digital breast tomosynthesis
    • [cs.CV]Audiovisual SlowFast Networks for Video Recognition
    • [cs.CV]Channel Pruning via Automatic Structure Search
    • [cs.CV]Continual Local Replacement for Few-shot Image Recognition
    • [cs.CV]Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation
    • [cs.CV]Deformation-aware Unpaired Image Translation for Pose Estimation on Laboratory Animals
    • [cs.CV]Detecting Deficient Coverage in Colonoscopies
    • [cs.CV]Disassembling the Dataset: A Camera Alignment Mechanism for Multiple Tasks in Person Re-identification
    • [cs.CV]Filter Sketch for Network Pruning
    • [cs.CV]How Much Position Information Do Convolutional Neural Networks Encode?
    • [cs.CV]ImageBERT: Cross-modal Pre-training with Large-scale Weak-supervised Image-Text Data
    • [cs.CV]Learning to adapt class-specific features across domains for semantic segmentation
    • [cs.CV]Lipreading using Temporal Convolutional Networks
    • [cs.CV]Observer variation-aware medical image segmentation by combining deep learning and surrogate-assisted genetic algorithms
    • [cs.CV]PENet: Object Detection using Points Estimation in Aerial Images
    • [cs.CV]Partially-Shared Variational Auto-encoders for Unsupervised Domain Adaptation with Target Shift
    • [cs.CV]Robust Explanations for Visual Question Answering
    • [cs.CV]Semi-DerainGAN: A New Semi-supervised Single Image Deraining Network
    • [cs.CV]Ternary Feature Masks: continual learning without any forgetting
    • [cs.CV]Weakly-Supervised Lesion Segmentation on CT Scans using Co-Segmentation
    • [cs.CY]ClassCode: An Interactive Teaching and Learning Environment for Programming Education in Classrooms
    • [cs.CY]Online Abuse toward Candidates during the UK General Election 2019: Working Paper
    • [cs.CY]Quantifying Engagement with Citations on Wikipedia
    • [cs.CY]Understanding the Incel Community on YouTube
    • [cs.DC]A Closer Look at Lightweight Graph Reordering
    • [cs.DC]CEFIoT: A Fault-Tolerant IoT Architecture for Edge and Cloud
    • [cs.DC]Coded Computing for Boolean Functions
    • [cs.DC]Communication-Efficient String Sorting
    • [cs.DL]Referencing Source Code Artifacts: a Separate Concern in Software Citation
    • [cs.DS]Bibliography of distributed approximation on structurally sparse graph classes
    • [cs.HC]Facial Feedback for Reinforcement Learning: A Case Study and Offline Analysis Using the TAMER Framework
    • [cs.IR]EventMapper: Detecting Real-World Physical Events Using Corroborative and Probabilistic Sources
    • [cs.IR]Experiments on Manual Thesaurus based Query Expansion for Ad-hoc Monolingual Gujarati Information Retrieval Tasks
    • [cs.IR]Navigation-Based Candidate Expansion and Pretrained Language Models for Citation Recommendation
    • [cs.IT]$O(\log \log n)$ Worst-Case Local Decoding and Update Efficiency for Data Compression
    • [cs.IT]A Signal-Space Distance Measure for Nondispersive Optical Fiber
    • [cs.IT]Communication Efficient Federated Learning over Multiple Access Channels
    • [cs.IT]Convolutional Codes
    • [cs.IT]Receive Antenna Selection for Secure Pre-coding Aided Spatial Modulation
    • [cs.IT]The Capacity of Single-Server Weakly-Private Information Retrieval
    • [cs.LG]A Deep Learning Approach to Behavior-Based Learner Modeling
    • [cs.LG]Ada-LISTA: Learned Solvers Adaptive to Varying Models
    • [cs.LG]Applying Recent Innovations from NLP to MOOC Student Course Trajectory Modeling
    • [cs.LG]BLK-REW: A Unified Block-based DNN Pruning Framework using Reweighted Regularization Method
    • [cs.LG]Best Arm Identification for Cascading Bandits in the Fixed Confidence Setting
    • [cs.LG]Compositional properties of emergent languages in deep learning
    • [cs.LG]Data Selection for Federated Learning with Relevant and Irrelevant Data at Clients
    • [cs.LG]Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case
    • [cs.LG]Expected Information Maximization: Using the I-Projection for Mixture Density Estimation
    • [cs.LG]From abstract items to latent spaces to observed data and back: Compositional Variational Auto-Encoder
    • [cs.LG]FsNet: Feature Selection Network on High-dimensional Biological Data
    • [cs.LG]Information Compensation for Deep Conditional Generative Networks
    • [cs.LG]Intelligent Chest X-ray Worklist Prioritization by CNNs: A Clinical Workflow Simulation
    • [cs.LG]Intermittent Pulling with Local Compensation for Communication-Efficient Federated Learning
    • [cs.LG]Low-Complexity LSTM Training and Inference with FloatSD8 Weight Representation
    • [cs.LG]Massif: Interactive Interpretation of Adversarial Attacks on Deep Learning
    • [cs.LG]Multi-objective Neural Architecture Search via Non-stationary Policy Gradient
    • [cs.LG]RPN: A Residual Pooling Network for Efficient Federated Learning
    • [cs.LG]Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures
    • [cs.LG]Representation Learning for Medical Data
    • [cs.LG]Scaling Laws for Neural Language Models
    • [cs.LG]Semi-supervised Grasp Detection by Representation Learning in a Vector Quantized Latent Space
    • [cs.LG]Stacked Boosters Network Architecture for Short Term Load Forecasting in Buildings
    • [cs.LG]Structured Compression and Sharing of Representational Space for Continual Learning
    • [cs.LG]Towards A Controllable Disentanglement Network
    • [cs.LG]Towards Automatic Clustering Analysis using Traces of Information Gain: The InfoGuide Method
    • [cs.LG]Towards Robust DNNs: An Taylor Expansion-Based Method for Generating Powerful Adversarial Examples
    • [cs.LG]Visual Summary of Value-level Feature Attribution in Prediction Classes with Recurrent Neural Networks
    • [cs.NE]DCT-Conv: Coding filters in convolutional networks with Discrete Cosine Transform
    • [cs.NI]Synchronous Transmissions in Low-Power Wireless: A Survey of Communication Protocols and Network Services
    • [cs.RO]2D-VSR-Sim: an Optimization-friendly Simulator of 2-D Voxel-based Soft Robots
    • [cs.RO]A Probabilistic Framework for Imitating Human Race Driver Behavior
    • [cs.RO]Automatic Differentiation and Continuous Sensitivity Analysis of Rigid Body Dynamics
    • [cs.RO]Fast, Compact and Highly Scalable Visual Place Recognition through Sequence-based Matching of Overloaded Representations
    • [cs.RO]Impact-aware humanoid robot motion generation with a quadratic optimization controller
    • [cs.RO]Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement Learning
    • [cs.RO]Learning Object Placements For Relational Instructions by Hallucinating Scene Representations
    • [cs.RO]Socially intelligent task and motion planning for human-robot interaction
    • [cs.RO]Trajectory Planning for Connected and Automated Vehicles: Cruising, Lane Changing, and Platooning
    • [cs.SD]The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Speech Quality and Testing Framework
    • [cs.SE]Search-Based Software Engineering for Self-Adaptive Systems: One Survey, Five Disappointments and Six Opportunities
    • [cs.SI]Joint Inference on Truth/Rumor and Their Sources in Social Networks
    • [cs.SI]Relational Thematic Clustering with Mutually Preferred Neighbors
    • [cs.SI]The Pushshift Reddit Dataset
    • [cs.SI]The Pushshift Telegram Dataset
    • [eess.AS]Improving speaker discrimination of target speech extraction with time-domain SpeakerBeam
    • [eess.AS]On the human evaluation of audio adversarial examples
    • [eess.IV]A One-Shot Learning Framework for Assessment of Fibrillar Collagen from Second Harmonic Generation Images of an Infarcted Myocardium
    • [eess.IV]A multi-site study of a breast density deep learning model for full-field digital mammography and digital breast tomosynthesis exams
    • [eess.IV]CNN-CASS: CNN for Classification of Coronary Artery Stenosis Score in MPR Images
    • [eess.IV]MRI Banding Removal via Adversarial Training
    • [eess.IV]Segmentation of Retinal Low-Cost Optical Coherence Tomography Images using Deep Learning
    • [eess.IV]Tensor-Based Grading: A Novel Patch-Based Grading Approach for the Analysis of Deformation Fields in Huntington’s Disease
    • [eess.SP]A hemodynamic decomposition model for detecting cognitive load using functional near-infrared spectroscopy
    • [eess.SP]Inference over Wireless IoT Links with Importance-Filtered Updates
    • [eess.SP]Reconfigurable Intelligent Surface assisted Two-Way Communications: Performance Analysis and Optimization
    • [eess.SY]Counter-example Guided Learning of Bounds on Environment Behavior
    • [math.OC]Replica Exchange for Non-Convex Optimization
    • [math.ST]A precise local limit theorem for the multinomial distribution
    • [math.ST]Geometric Conditions for the Discrepant Posterior Phenomenon and Connections to Simpson’s Paradox
    • [q-bio.NC]Towards naturalistic human neuroscience and neuroengineering: behavior mining in long-term video and neural recordings
    • [q-bio.QM]Deep learning-based prediction of response to HER2-targeted neoadjuvant chemotherapy from pre-treatment dynamic breast MRI: A multi-institutional validation study
    • [quant-ph]On lower semicontinuity of the quantum conditional mutual information and its corollaries
    • [stat.AP]A covariance-enhanced approach to multi-tissue joint eQTL mapping with application to transcriptome-wide association studies
    • [stat.AP]Bayesian estimates of transmission line outage rates that consider line dependencies
    • [stat.AP]Statistical post-processing of heat index ensemble forecasts: is there a royal road?
    • [stat.ME]Maximum Likelihood Estimation of Spatially Varying Coefficient Models for Large Data with an Application to Real Estate Price Prediction
    • [stat.ME]On the Hauck-Donner Effect in Wald Tests: Detection, Tipping Points, and Parameter Space Characterization
    • [stat.ME]Shrinkage with Robustness: Log-Adjusted Priors for Sparse Signals
    • [stat.ME]The Reciprocal Bayesian LASSO
    • [stat.ML]A Bayesian Long Short-Term Memory Model for Value at Risk and Expected Shortfall Joint Forecasting
    • [stat.ML]A Multi-Scale Tensor Network Architecture for Classification and Regression
    • [stat.ML]Best Principal Submatrix Selection for the Maximum Entropy Sampling Problem: Scalable Algorithms and Performance Guarantees
    • [stat.ML]Linking Bank Clients using Graph Neural Networks Powered by Rich Transactional Data
    • [stat.ML]Stratified cross-validation for unbiased and privacy-preserving federated learning
    • [stat.ML]Target-Embedding Autoencoders for Supervised Representation Learning

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

    • [cs.AI]DeepEnroll: Patient-Trial Matching with Deep Embedding and Entailment Prediction
    Xingyao Zhang, Cao Xiao, Lucas M. Glass, Jimeng Sun
    http://arxiv.org/abs/2001.08179v2

    • [cs.AI]GLIB: Exploration via Goal-Literal Babbling for Lifted Operator Learning
    Rohan Chitnis, Tom Silver, Joshua Tenenbaum, Leslie Pack Kaelbling, Tomas Lozano-Perez
    http://arxiv.org/abs/2001.08299v1

    • [cs.AI]I Feel I Feel You: A Theory of Mind Experiment in Games
    David Melhart, Georgios N. Yannakakis, Antonios Liapis
    http://arxiv.org/abs/2001.08656v1

    • [cs.AI]Learning Distributional Programs for Relational Autocompletion
    Kumar Nitesh, Kuzelka Ondrej, De Raedt Luc
    http://arxiv.org/abs/2001.08603v1

    • [cs.AI]Model-theoretic Characterizations of Existential Rule Languages
    Heng Zhang, Yan Zhang, Guifei Jiang
    http://arxiv.org/abs/2001.08688v1

    • [cs.AI]Numerical Abstract Persuasion Argumentation for Expressing Concurrent Multi-Agent Negotiations
    Ryuta Arisaka, Takayuki Ito
    http://arxiv.org/abs/2001.08335v1

    • [cs.AI]Proxy Tasks and Subjective Measures Can Be Misleading in Evaluating Explainable AI Systems
    Zana Buçinca, Phoebe Lin, Krzysztof Z. Gajos, Elena L. Glassman
    http://arxiv.org/abs/2001.08298v1

    • [cs.CC]On the computational power and complexity of Spiking Neural Networks
    Johan Kwisthout, Nils Donselaar
    http://arxiv.org/abs/2001.08439v1

    • [cs.CL]A Study of the Tasks and Models in Machine Reading Comprehension
    Chao Wang
    http://arxiv.org/abs/2001.08635v1

    • [cs.CL]Action Recognition and State Change Prediction in a Recipe Understanding Task Using a Lightweight Neural Network Model
    Qing Wan, Yoonsuck Choe
    http://arxiv.org/abs/2001.08665v1

    • [cs.CL]CheckThat! at CLEF 2020: Enabling the Automatic Identification and Verification of Claims in Social Media
    Alberto Barron-Cedeno, Tamer Elsayed, Preslav Nakov, Giovanni Da San Martino, Maram Hasanain, Reem Suwaileh, Fatima Haouari
    http://arxiv.org/abs/2001.08546v1

    • [cs.CL]Coordinated Reasoning for Cross-Lingual Knowledge Graph Alignment
    Kun Xu, Linfeng Song, Yansong Feng, Yan Song, Dong Yu
    http://arxiv.org/abs/2001.08728v1

    • [cs.CL]Multilingual Denoising Pre-training for Neural Machine Translation
    Yinhan Liu, Jiatao Gu, Naman Goyal, Xian Li, Sergey Edunov, Marjan Ghazvininejad, Mike Lewis, Luke Zettlemoyer
    http://arxiv.org/abs/2001.08210v2

    • [cs.CL]Pre-training via Leveraging Assisting Languages and Data Selection for Neural Machine Translation
    Haiyue Song, Raj Dabre, Zhuoyuan Mao, Fei Cheng, Sadao Kurohashi, Eiichiro Sumita
    http://arxiv.org/abs/2001.08353v1

    • [cs.CL]Transition-Based Dependency Parsing using Perceptron Learner
    Rahul Radhakrishnan Iyer, Miguel Ballesteros, Chris Dyer, Robert Frederking
    http://arxiv.org/abs/2001.08279v1

    • [cs.CL]Variational Hierarchical Dialog Autoencoder for Dialogue State Tracking Data Augmentation
    Kang Min Yoo, Hanbit Lee, Franck Dernoncourt, Trung Bui, Walter Chang, Sang-goo Lee
    http://arxiv.org/abs/2001.08604v1

    • [cs.CR]Information set decoding of Lee-metric codes over finite rings
    Violetta Weger, Massimo Battaglioni, Paolo Santini, Franco Chiaraluce, Marco Baldi, Edoardo Persichetti
    http://arxiv.org/abs/2001.08425v1

    • [cs.CR]Nowhere to Hide: Cross-modal Identity Leakage between Biometrics and Devices
    Chris Xiaoxuan Lu, Yang Li, Yuanbo Xiangli, Zhengxiong Li
    http://arxiv.org/abs/2001.08211v1

    • [cs.CR]Sensor-based Continuous Authentication of Smartphones’ Users Using Behavioral Biometrics: A Survey
    Mohammed Abuhamad, Ahmed Abusnaina, DaeHun Nyang, David Mohaisen
    http://arxiv.org/abs/2001.08578v1

    • [cs.CV]A Hypersensitive Breast Cancer Detector
    Stefano Pedemonte, Brent Mombourquette, Alexis Goh, Trevor Tsue, Aaron Long, Sadanand Singh, Thomas Paul Matthews, Meet Shah, Jason Su
    http://arxiv.org/abs/2001.08382v1

    • [cs.CV]A Large Scale Event-based Detection Dataset for Automotive
    Pierre de Tournemire. Davide Nitti, Etienne Perot, Davide Migliore, Amos Sironi
    http://arxiv.org/abs/2001.08499v1

    • [cs.CV]Active Perception with A Monocular Camera for Multiscopic Vision
    Weihao Yuan, Rui Fan, Michael Yu Wang, Qifeng Chen
    http://arxiv.org/abs/2001.08212v1

    • [cs.CV]Adaptation of a deep learning malignancy model from full-field digital mammography to digital breast tomosynthesis
    Sadanand Singh, Thomas Paul Matthews, Meet Shah, Brent Mombourquette, Trevor Tsue, Aaron Long, Ranya Almohsen, Stefano Pedemonte, Jason Su
    http://arxiv.org/abs/2001.08381v1

    • [cs.CV]Audiovisual SlowFast Networks for Video Recognition
    Fanyi Xiao, Yong Jae Lee, Kristen Grauman, Jitendra Malik, Christoph Feichtenhofer
    http://arxiv.org/abs/2001.08740v1

    • [cs.CV]Channel Pruning via Automatic Structure Search
    Mingbao Lin, Rongrong Ji, Yuxin Zhang, Baochang Zhang, Yongjian Wu, Yonghong Tian
    http://arxiv.org/abs/2001.08565v1

    • [cs.CV]Continual Local Replacement for Few-shot Image Recognition
    Canyu Le, Zhonggui Chen, Xihan Wei, Biao Wang, Lei Zhang
    http://arxiv.org/abs/2001.08366v1

    • [cs.CV]Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation
    Hung-Yu Tseng, Hsin-Ying Lee, Jia-Bin Huang, Ming-Hsuan Yang
    http://arxiv.org/abs/2001.08735v1

    • [cs.CV]Deformation-aware Unpaired Image Translation for Pose Estimation on Laboratory Animals
    Siyuan Li, Semih Günel, Mirela Ostrek, Pavan Ramdya, Pascal Fua, Helge Rhodin
    http://arxiv.org/abs/2001.08601v1

    • [cs.CV]Detecting Deficient Coverage in Colonoscopies
    Daniel Freedman, Yochai Blau, Liran Katzir, Amit Aides, Ilan Shimshoni, Danny Veikherman, Tomer Golany, Ariel Gordon, Greg Corrado, Yossi Matias, Ehud Rivlin
    http://arxiv.org/abs/2001.08589v1

    • [cs.CV]Disassembling the Dataset: A Camera Alignment Mechanism for Multiple Tasks in Person Re-identification
    Zijie Zhuang, Longhui Wei, Lingxi Xie, Hengheng Zhang, Tianyu Zhang, Haozhe Wu, Haizhou Ai, Qi Tian
    http://arxiv.org/abs/2001.08680v1

    • [cs.CV]Filter Sketch for Network Pruning
    Mingbao Lin, Rongrong Ji, Shaojie Li, Qixiang Ye, Yonghong Tian, Jianzhuang Liu, Qi Tian
    http://arxiv.org/abs/2001.08514v1

    • [cs.CV]How Much Position Information Do Convolutional Neural Networks Encode?
    Md Amirul Islam, Sen Jia, Neil D. B. Bruce
    http://arxiv.org/abs/2001.08248v1

    • [cs.CV]ImageBERT: Cross-modal Pre-training with Large-scale Weak-supervised Image-Text Data
    Di Qi, Lin Su, Jia Song, Edward Cui, Taroon Bharti, Arun Sacheti
    http://arxiv.org/abs/2001.07966v2

    • [cs.CV]Learning to adapt class-specific features across domains for semantic segmentation
    Mikel Menta, Adriana Romero, Joost van de Weijer
    http://arxiv.org/abs/2001.08311v1

    • [cs.CV]Lipreading using Temporal Convolutional Networks
    Brais Martinez, Pingchuan Ma, Stavros Petridis, Maja Pantic
    http://arxiv.org/abs/2001.08702v1

    • [cs.CV]Observer variation-aware medical image segmentation by combining deep learning and surrogate-assisted genetic algorithms
    Arkadiy Dushatskiy, Adriënne M. Mendrik, Peter A. N. Bosman, Tanja Alderliesten
    http://arxiv.org/abs/2001.08552v1

    • [cs.CV]PENet: Object Detection using Points Estimation in Aerial Images
    Ziyang Tang, Xiang Liu, Guangyu Shen, Baijian Yang
    http://arxiv.org/abs/2001.08247v1

    • [cs.CV]Partially-Shared Variational Auto-encoders for Unsupervised Domain Adaptation with Target Shift
    Ryuhei Takahashi, Atsushi Hashimoto, Motoharu Sonogashira, Masaaki Iiyama
    http://arxiv.org/abs/2001.07895v2

    • [cs.CV]Robust Explanations for Visual Question Answering
    Badri N. Patro, Shivansh Pate, Vinay P. Namboodiri
    http://arxiv.org/abs/2001.08730v1

    • [cs.CV]Semi-DerainGAN: A New Semi-supervised Single Image Deraining Network
    Yanyan Wei, Zhao Zhang, Haijun Zhang, Jie Qin, Mingbo Zhao
    http://arxiv.org/abs/2001.08388v1

    • [cs.CV]Ternary Feature Masks: continual learning without any forgetting
    Marc Masana, Tinne Tuytelaars, Joost van de Weijer
    http://arxiv.org/abs/2001.08714v1

    • [cs.CV]Weakly-Supervised Lesion Segmentation on CT Scans using Co-Segmentation
    Vatsal Agarwal, Youbao Tang, Jing Xiao, Ronald M. Summers
    http://arxiv.org/abs/2001.08590v1

    • [cs.CY]ClassCode: An Interactive Teaching and Learning Environment for Programming Education in Classrooms
    Ryo Suzuki, Jun Kato, Koji Yatani
    http://arxiv.org/abs/2001.08194v1

    • [cs.CY]Online Abuse toward Candidates during the UK General Election 2019: Working Paper
    Genevieve Gorrell, Mehmet E Bakir, Ian Roberts, Mark A Greenwood, Kalina Bontcheva
    http://arxiv.org/abs/2001.08686v1

    • [cs.CY]Quantifying Engagement with Citations on Wikipedia
    Tiziano Piccardi, Miriam Redi, Giovanni Colavizza, Robert West
    http://arxiv.org/abs/2001.08614v1

    • [cs.CY]Understanding the Incel Community on YouTube
    Kostantinos Papadamou, Savvas Zannettou, Jeremy Blackburn, Emiliano De Cristofaro, Gianluca Stringhini, Michael Sirivianos
    http://arxiv.org/abs/2001.08293v1

    • [cs.DC]A Closer Look at Lightweight Graph Reordering
    Priyank Faldu, Jeff Diamond, Boris Grot
    http://arxiv.org/abs/2001.08448v1

    • [cs.DC]CEFIoT: A Fault-Tolerant IoT Architecture for Edge and Cloud
    Asad Javed, Keijo Heljanko, Andrea Buda, Kary Främling
    http://arxiv.org/abs/2001.08433v1

    • [cs.DC]Coded Computing for Boolean Functions
    Chien-Sheng Yang, A. Salman Avestimehr
    http://arxiv.org/abs/2001.08720v1

    • [cs.DC]Communication-Efficient String Sorting
    Timo Bingmann, Peter Sanders, Matthias Schimek
    http://arxiv.org/abs/2001.08516v1

    • [cs.DL]Referencing Source Code Artifacts: a Separate Concern in Software Citation
    Roberto Di Cosmo, Morane Gruenpeter, Stefano Zacchiroli
    http://arxiv.org/abs/2001.08647v1

    • [cs.DS]Bibliography of distributed approximation on structurally sparse graph classes
    Laurent Feuilloley
    http://arxiv.org/abs/2001.08510v1

    • [cs.HC]Facial Feedback for Reinforcement Learning: A Case Study and Offline Analysis Using the TAMER Framework
    Guangliang Li, Hamdi Dibeklioğlu, Shimon Whiteson, Hayley Hung
    http://arxiv.org/abs/2001.08703v1

    • [cs.IR]EventMapper: Detecting Real-World Physical Events Using Corroborative and Probabilistic Sources
    Abhijit Suprem, Calton Pu
    http://arxiv.org/abs/2001.08700v1

    • [cs.IR]Experiments on Manual Thesaurus based Query Expansion for Ad-hoc Monolingual Gujarati Information Retrieval Tasks
    Hardik Joshi, Jyoti Pareek
    http://arxiv.org/abs/2001.08085v1

    • [cs.IR]Navigation-Based Candidate Expansion and Pretrained Language Models for Citation Recommendation
    Rodrigo Nogueira, Zhiying Jiang, Kyunghyun Cho, Jimmy Lin
    http://arxiv.org/abs/2001.08687v1

    • [cs.IT]$O(\log \log n)$ Worst-Case Local Decoding and Update Efficiency for Data Compression
    Shashank Vatedka, Venkat Chandar, Aslan Tchamkerten
    http://arxiv.org/abs/2001.08679v1

    • [cs.IT]A Signal-Space Distance Measure for Nondispersive Optical Fiber
    Reza Rafie Borujeny, Frank R. Kschischang
    http://arxiv.org/abs/2001.08663v1

    • [cs.IT]Communication Efficient Federated Learning over Multiple Access Channels
    Wei-Ting Chang, Ravi Tandon
    http://arxiv.org/abs/2001.08737v1

    • [cs.IT]Convolutional Codes
    Julia Lieb, Raquel Pinto, Joachim Rosenthal
    http://arxiv.org/abs/2001.08281v1

    • [cs.IT]Receive Antenna Selection for Secure Pre-coding Aided Spatial Modulation
    Lin Liu, Guiyang Xia, Jun Zou, Weibin Zhang, Feng Shu, Jiangzhou Wang
    http://arxiv.org/abs/2001.08612v1

    • [cs.IT]The Capacity of Single-Server Weakly-Private Information Retrieval
    Hsuan-Yin Lin, Siddhartha Kumar, Eirik Rosnes, Alexandre Graell i Amat, Eitan Yaakobi
    http://arxiv.org/abs/2001.08727v1

    • [cs.LG]A Deep Learning Approach to Behavior-Based Learner Modeling
    Yuwei Tu, Weiyu Chen, Christopher G. Brinton
    http://arxiv.org/abs/2001.08328v1

    • [cs.LG]Ada-LISTA: Learned Solvers Adaptive to Varying Models
    Aviad Aberdam, Alona Golts, Michael Elad
    http://arxiv.org/abs/2001.08456v1

    • [cs.LG]Applying Recent Innovations from NLP to MOOC Student Course Trajectory Modeling
    Clarence Chen, Zachary Pardos
    http://arxiv.org/abs/2001.08333v1

    • [cs.LG]BLK-REW: A Unified Block-based DNN Pruning Framework using Reweighted Regularization Method
    Xiaolong Ma, Zhengang Li, Yifan Gong, Tianyun Zhang, Wei Niu, Zheng Zhan, Pu Zhao, Jian Tang, Xue Lin, Bin Ren, Yanzhi Wang
    http://arxiv.org/abs/2001.08357v1

    • [cs.LG]Best Arm Identification for Cascading Bandits in the Fixed Confidence Setting
    Zixin Zhong, Wang Chi Cheung, Vincent Y. F. Tan
    http://arxiv.org/abs/2001.08655v1

    • [cs.LG]Compositional properties of emergent languages in deep learning
    Bence Keresztury, Elia Bruni
    http://arxiv.org/abs/2001.08618v1

    • [cs.LG]Data Selection for Federated Learning with Relevant and Irrelevant Data at Clients
    Tiffany Tuor, Shiqiang Wang, Bong Jun Ko, Changchang Liu, Kin K. Leung
    http://arxiv.org/abs/2001.08300v1

    • [cs.LG]Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case
    Neo Wu, Bradley Green, Xue Ben, Shawn O’Banion
    http://arxiv.org/abs/2001.08317v1

    • [cs.LG]Expected Information Maximization: Using the I-Projection for Mixture Density Estimation
    Philipp Becker, Oleg Arenz, Gerhard Neumann
    http://arxiv.org/abs/2001.08682v1

    • [cs.LG]From abstract items to latent spaces to observed data and back: Compositional Variational Auto-Encoder
    Victor Berger, Michèle Sebag
    http://arxiv.org/abs/2001.07910v1

    • [cs.LG]FsNet: Feature Selection Network on High-dimensional Biological Data
    Dinesh Singh, Makoto Yamada
    http://arxiv.org/abs/2001.08322v1

    • [cs.LG]Information Compensation for Deep Conditional Generative Networks
    Zehao Wang, Kaili Wang, Tinne Tuytelaars, Jose Oramas
    http://arxiv.org/abs/2001.08559v1

    • [cs.LG]Intelligent Chest X-ray Worklist Prioritization by CNNs: A Clinical Workflow Simulation
    Ivo M. Baltruschat, Leonhard Steinmeister, Hannes Nickisch, Axel Saalbach, Michael Grass, Gerhard Adam, Harald Ittrich, Tobias Knopp
    http://arxiv.org/abs/2001.08625v1

    • [cs.LG]Intermittent Pulling with Local Compensation for Communication-Efficient Federated Learning
    Haozhao Wang, Zhihao Qu, Song Guo, Xin Gao, Ruixuan Li, Baoliu Ye
    http://arxiv.org/abs/2001.08277v1

    • [cs.LG]Low-Complexity LSTM Training and Inference with FloatSD8 Weight Representation
    Yu-Tung Liu, Tzi-Dar Chiueh
    http://arxiv.org/abs/2001.08450v1

    • [cs.LG]Massif: Interactive Interpretation of Adversarial Attacks on Deep Learning
    Nilaksh Das, Haekyu Park, Zijie J. Wang, Fred Hohman, Robert Firstman, Emily Rogers, Duen Horng Chau
    http://arxiv.org/abs/2001.07769v2

    • [cs.LG]Multi-objective Neural Architecture Search via Non-stationary Policy Gradient
    Zewei Chen, Fengwei Zhou, George Trimponias, Zhenguo Li
    http://arxiv.org/abs/2001.08437v1

    • [cs.LG]RPN: A Residual Pooling Network for Efficient Federated Learning
    Anbu Huang, Yuanyuan Chen, Yang Liu, Tianjian Chen, Qiang Yang
    http://arxiv.org/abs/2001.08600v1

    • [cs.LG]Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures
    Mohamed El Amine Seddik, Cosme Louart, Mohamed Tamaazousti, Romain Couillet
    http://arxiv.org/abs/2001.08370v1

    • [cs.LG]Representation Learning for Medical Data
    Karol Antczak
    http://arxiv.org/abs/2001.08269v1

    • [cs.LG]Scaling Laws for Neural Language Models
    Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B. Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, Dario Amodei
    http://arxiv.org/abs/2001.08361v1

    • [cs.LG]Semi-supervised Grasp Detection by Representation Learning in a Vector Quantized Latent Space
    Mridul Mahajan, Tryambak Bhattacharjee, Arya Krishnan, Priya Shukla, G C Nandi
    http://arxiv.org/abs/2001.08477v1

    • [cs.LG]Stacked Boosters Network Architecture for Short Term Load Forecasting in Buildings
    Tuukka Salmi, Jussi Kiljander, Daniel Pakkala
    http://arxiv.org/abs/2001.08406v1

    • [cs.LG]Structured Compression and Sharing of Representational Space for Continual Learning
    Gobinda Saha, Isha Garg, Aayush Ankit, Kaushik Roy
    http://arxiv.org/abs/2001.08650v1

    • [cs.LG]Towards A Controllable Disentanglement Network
    Zengjie Song, Oluwasanmi Koyejo, Jiangshe Zhang
    http://arxiv.org/abs/2001.08572v1

    • [cs.LG]Towards Automatic Clustering Analysis using Traces of Information Gain: The InfoGuide Method
    Paulo Rocha, Diego Pinheiro, Martin Cadeiras, Carmelo Bastos-Filho
    http://arxiv.org/abs/2001.08677v1

    • [cs.LG]Towards Robust DNNs: An Taylor Expansion-Based Method for Generating Powerful Adversarial Examples
    Ya-guan Qian, Xi-Ming Zhang, Bin Wang, Wei Li, Jian-Hai Chen, Wu-Jie Zhou, Jing-Sheng Lei
    http://arxiv.org/abs/2001.08389v1

    • [cs.LG]Visual Summary of Value-level Feature Attribution in Prediction Classes with Recurrent Neural Networks
    Chuan Wang, Xumeng Wang, Kwan-Liu Ma
    http://arxiv.org/abs/2001.08379v1

    • [cs.NE]DCT-Conv: Coding filters in convolutional networks with Discrete Cosine Transform
    Karol Chęciński, Paweł Wawrzyński
    http://arxiv.org/abs/2001.08517v1

    • [cs.NI]Synchronous Transmissions in Low-Power Wireless: A Survey of Communication Protocols and Network Services
    Marco Zimmerling, Luca Mottola, Silvia Santini
    http://arxiv.org/abs/2001.08557v1

    • [cs.RO]2D-VSR-Sim: an Optimization-friendly Simulator of 2-D Voxel-based Soft Robots
    Eric Medvet, Alberto Bartoli, Andrea De Lorenzo, Stefano Seriani
    http://arxiv.org/abs/2001.08617v1

    • [cs.RO]A Probabilistic Framework for Imitating Human Race Driver Behavior
    Stefan Löckel, Jan Peters, Peter van Vliet
    http://arxiv.org/abs/2001.08255v1

    • [cs.RO]Automatic Differentiation and Continuous Sensitivity Analysis of Rigid Body Dynamics
    David Millard, Eric Heiden, Shubham Agrawal, Gaurav S. Sukhatme
    http://arxiv.org/abs/2001.08539v1

    • [cs.RO]Fast, Compact and Highly Scalable Visual Place Recognition through Sequence-based Matching of Overloaded Representations
    Sourav Garg, Michael Milford
    http://arxiv.org/abs/2001.08434v1

    • [cs.RO]Impact-aware humanoid robot motion generation with a quadratic optimization controller
    Yuquan Wang, Arnaud Tanguy, Pierre Gergondet, Abderrahmane Kheddar
    http://arxiv.org/abs/2001.08454v1

    • [cs.RO]Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement Learning
    Jianyu Chen, Shengbo Eben Li, Masayoshi Tomizuka
    http://arxiv.org/abs/2001.08726v1

    • [cs.RO]Learning Object Placements For Relational Instructions by Hallucinating Scene Representations
    Oier Mees, Alp Emek, Johan Vertens, Wolfram Burgard
    http://arxiv.org/abs/2001.08481v1

    • [cs.RO]Socially intelligent task and motion planning for human-robot interaction
    Andrea Frank, Laurel Riek
    http://arxiv.org/abs/2001.08398v1

    • [cs.RO]Trajectory Planning for Connected and Automated Vehicles: Cruising, Lane Changing, and Platooning
    Xiangguo Liu, Guangchen Zhao, Neda Masoud, Qi Zhu
    http://arxiv.org/abs/2001.08620v1

    • [cs.SD]The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Speech Quality and Testing Framework
    Chandan K. A. Reddy, Ebrahim Beyrami, Harishchandra Dubey, Vishak Gopal, Roger Cheng, Ross Cutler, Sergiy Matusevych, Robert Aichner, Ashkan Aazami, Sebastian Braun, Puneet Rana, Sriram Srinivasan, Johannes Gehrke
    http://arxiv.org/abs/2001.08662v1

    • [cs.SE]Search-Based Software Engineering for Self-Adaptive Systems: One Survey, Five Disappointments and Six Opportunities
    Tao Chen, Miqing Li, Ke Li, Kalyanmoy Deb
    http://arxiv.org/abs/2001.08236v1

    • [cs.SI]Joint Inference on Truth/Rumor and Their Sources in Social Networks
    Shan Qu, Ziqi Zhao, Luoyi Fu, XInbing Wang, Jun Xu
    http://arxiv.org/abs/2001.08472v1

    • [cs.SI]Relational Thematic Clustering with Mutually Preferred Neighbors
    Tiantian He, Lu Bai, Yew-Soon Ong
    http://arxiv.org/abs/2001
    6a6d
    .08412v1
    6a6d
    .08412v1)

    • [cs.SI]The Pushshift Reddit Dataset
    Jason Baumgartner, Savvas Zannettou, Brian Keegan, Megan Squire, Jeremy Blackburn
    http://arxiv.org/abs/2001.08435v1

    • [cs.SI]The Pushshift Telegram Dataset
    Jason Baumgartner, Savvas Zannettou, Megan Squire, Jeremy Blackburn
    http://arxiv.org/abs/2001.08438v1

    • [eess.AS]Improving speaker discrimination of target speech extraction with time-domain SpeakerBeam
    Marc Delcroix, Tsubasa Ochiai, Katerina Zmolikova, Keisuke Kinoshita, Naohiro Tawara, Tomohiro Nakatani, Shoko Araki
    http://arxiv.org/abs/2001.08378v1

    • [eess.AS]On the human evaluation of audio adversarial examples
    Jon Vadillo, Roberto Santana
    http://arxiv.org/abs/2001.08444v1

    • [eess.IV]A One-Shot Learning Framework for Assessment of Fibrillar Collagen from Second Harmonic Generation Images of an Infarcted Myocardium
    Qun Liu, Supratik Mukhopadhyay, Maria Ximena Bastidas Rodriguez, Xing Fu, Sushant Sahu, David Burk, Manas Gartia
    http://arxiv.org/abs/2001.08395v1

    • [eess.IV]A multi-site study of a breast density deep learning model for full-field digital mammography and digital breast tomosynthesis exams
    Thomas P. Matthews, Sadanand Singh, Brent Mombourquette, Jason Su, Meet P. Shah, Stefano Pedemonte, Aaron Long, David Maffit, Jenny Gurney, Rodrigo Morales Hoil, Nikita Ghare, Douglas Smith, Stephen M. Moore, Susan C. Marks, Richard L. Wahl
    http://arxiv.org/abs/2001.08383v1

    • [eess.IV]CNN-CASS: CNN for Classification of Coronary Artery Stenosis Score in MPR Images
    Mariia Dobko, Bohdan Petryshak, Oles Dobosevych
    http://arxiv.org/abs/2001.08593v1

    • [eess.IV]MRI Banding Removal via Adversarial Training
    Aaron Defazio, Tullie Murrell, Michael P. Recht
    http://arxiv.org/abs/2001.08699v1

    • [eess.IV]Segmentation of Retinal Low-Cost Optical Coherence Tomography Images using Deep Learning
    Timo Kepp, Helge Sudkamp, Claus von der Burchard, Hendrik Schenke, Peter Koch, Gereon Hüttmann, Johann Roider, Mattias P. Heinrich, Heinz Handels
    http://arxiv.org/abs/2001.08480v1

    • [eess.IV]Tensor-Based Grading: A Novel Patch-Based Grading Approach for the Analysis of Deformation Fields in Huntington’s Disease
    Kilian Hett, Hans Johnson, Pierrick Coupé, Jane Paulsen, Jeffrey Long, Ipek Oguz
    http://arxiv.org/abs/2001.08651v1

    • [eess.SP]A hemodynamic decomposition model for detecting cognitive load using functional near-infrared spectroscopy
    Marco A. Pinto-Orellana, Diego C. Nascimento, Peyman Mirtaheri, Rune Jonassen, Anis Yazidi, Hugo L. Hammer
    http://arxiv.org/abs/2001.08579v1

    • [eess.SP]Inference over Wireless IoT Links with Importance-Filtered Updates
    Ivana Nikoloska, Josefine Holm, Anders Kalør, Petar Popovski, Nikola Zlatanov
    http://arxiv.org/abs/2001.07857v1

    • [eess.SP]Reconfigurable Intelligent Surface assisted Two-Way Communications: Performance Analysis and Optimization
    Saman Atapattu, Rongfei Fan, Prathapasinghe Dharmawansa, Gongpu Wang, Jamie Evans, Theodoros A. Tsiftsis
    http://arxiv.org/abs/2001.07907v1

    • [eess.SY]Counter-example Guided Learning of Bounds on Environment Behavior
    Yuxiao Chen, Sumanth Dathathri, Tung Phan-Minh, Richard M. Murray
    http://arxiv.org/abs/2001.07233v2

    • [math.OC]Replica Exchange for Non-Convex Optimization
    Jing Dong, Xin T. Tong
    http://arxiv.org/abs/2001.08356v1

    • [math.ST]A precise local limit theorem for the multinomial distribution
    Frédéric Ouimet
    http://arxiv.org/abs/2001.08512v1

    • [math.ST]Geometric Conditions for the Discrepant Posterior Phenomenon and Connections to Simpson’s Paradox
    Yang Chen, Ruobin Gong, Min-ge Xie
    http://arxiv.org/abs/2001.08336v1

    • [q-bio.NC]Towards naturalistic human neuroscience and neuroengineering: behavior mining in long-term video and neural recordings
    Satpreet H. Singh, Steven M. Peterson, Rajesh P. N. Rao, Bingni W. Brunton
    http://arxiv.org/abs/2001.08349v1

    • [q-bio.QM]Deep learning-based prediction of response to HER2-targeted neoadjuvant chemotherapy from pre-treatment dynamic breast MRI: A multi-institutional validation study
    Nathaniel Braman, Mohammed El Adoui, Manasa Vulchi, Paulette Turk, Maryam Etesami, Pingfu Fu, Kaustav Bera, Stylianos Drisis, Vinay Varadan, Donna Plecha, Mohammed Benjelloun, Jame Abraham, Anant Madabhushi
    http://arxiv.org/abs/2001.08570v1

    • [quant-ph]On lower semicontinuity of the quantum conditional mutual information and its corollaries
    M. E. Shirokov
    http://arxiv.org/abs/2001.08691v1

    • [stat.AP]A covariance-enhanced approach to multi-tissue joint eQTL mapping with application to transcriptome-wide association studies
    Aaron J. Molstad, Wei Sun, Li Hsu
    http://arxiv.org/abs/2001.08363v1

    • [stat.AP]Bayesian estimates of transmission line outage rates that consider line dependencies
    Kai Zhou, James R. Cruise, Chris J. Dent, Ian Dobson, Louis Wehenkel, Zhaoyu Wang, Amy L. Wilson
    http://arxiv.org/abs/2001.08681v1

    • [stat.AP]Statistical post-processing of heat index ensemble forecasts: is there a royal road?
    Sándor Baran, Ágnes Baran, Florian Pappenberger, Zied Ben Bouallègue
    http://arxiv.org/abs/2001.08712v1

    • [stat.ME]Maximum Likelihood Estimation of Spatially Varying Coefficient Models for Large Data with an Application to Real Estate Price Prediction
    Jakob A. Dambon, Fabio Sigrist, Reinhard Furrer
    http://arxiv.org/abs/2001.08089v2

    • [stat.ME]On the Hauck-Donner Effect in Wald Tests: Detection, Tipping Points, and Parameter Space Characterization
    Thomas William Yee
    http://arxiv.org/abs/2001.08431v1

    • [stat.ME]Shrinkage with Robustness: Log-Adjusted Priors for Sparse Signals
    Yasuyuki Hamura, Kaoru Irie, Shonosuke Sugasawa
    http://arxiv.org/abs/2001.08465v1

    • [stat.ME]The Reciprocal Bayesian LASSO
    Himel Mallick, Rahim Alhamzawi, Vladimir Svetnik
    http://arxiv.org/abs/2001.08327v1

    • [stat.ML]A Bayesian Long Short-Term Memory Model for Value at Risk and Expected Shortfall Joint Forecasting
    Zhengkun Li, Minh-Ngoc Tran, Chao Wang, Richard Gerlach, Junbin Gao
    http://arxiv.org/abs/2001.08374v1

    • [stat.ML]A Multi-Scale Tensor Network Architecture for Classification and Regression
    Justin Reyes, Miles Stoudenmire
    http://arxiv.org/abs/2001.08286v1

    • [stat.ML]Best Principal Submatrix Selection for the Maximum Entropy Sampling Problem: Scalable Algorithms and Performance Guarantees
    Yongchun Li, Weijun Xie
    http://arxiv.org/abs/2001.08537v1

    • [stat.ML]Linking Bank Clients using Graph Neural Networks Powered by Rich Transactional Data
    Valentina Shumovskaia, Kirill Fedyanin, Ivan Sukharev, Dmitry Berestnev, Maxim Panov
    http://arxiv.org/abs/2001.08427v1

    • [stat.ML]Stratified cross-validation for unbiased and privacy-preserving federated learning
    R. Bey, R. Goussault, M. Benchoufi, R. Porcher
    http://arxiv.org/abs/2001.08090v2

    • [stat.ML]Target-Embedding Autoencoders for Supervised Representation Learning
    Daniel Jarrett, Mihaela van der Schaar
    http://arxiv.org/abs/2001.08345v1