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.DB - 数据库 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.ET - 新兴技术 cs.GR - 计算机图形学 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 econ.GN - 一般经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.AT - 代数拓扑 math.OC - 优化与控制 math.ST - 统计理论 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]Accelerating Road Sign Ground Truth Construction with Knowledge Graph and Machine Learning
    • [cs.AI]Constrained Risk-Averse Markov Decision Processes
    • [cs.AI]Creativity of Deep Learning: Conceptualization and Assessment
    • [cs.AI]Explaining Predictions of Deep Neural Classifier via Activation Analysis
    • [cs.AI]Learning in two-player games between transparent opponents
    • [cs.AI]Playing Text-Based Games with Common Sense
    • [cs.AI]Understanding Attention: In Minds and Machines
    • [cs.CL]A Benchmark Dataset for Understandable Medical Language Translation
    • [cs.CL]Automated Detection of Cyberbullying Against Women and Immigrants and Cross-domain Adaptability
    • [cs.CL]CUED_speech at TREC 2020 Podcast Summarisation Track
    • [cs.CL]Coarse-to-Fine Entity Representations for Document-level Relation Extraction
    • [cs.CL]DDRel: A New Dataset for Interpersonal Relation Classification in Dyadic Dialogues
    • [cs.CL]Data Processing and Annotation Schemes for FinCausal Shared Task
    • [cs.CL]Delexicalized Paraphrase Generation
    • [cs.CL]Event Guided Denoising for Multilingual Relation Learning
    • [cs.CL]Evolving Character-Level DenseNet Architectures using Genetic Programming
    • [cs.CL]Evolving Character-level Convolutional Neural Networks for Text Classification
    • [cs.CL]Few-Shot Event Detection with Prototypical Amortized Conditional Random Field
    • [cs.CL]Financial Document Causality Detection Shared Task (FinCausal 2020)
    • [cs.CL]Fine-tuning BERT for Low-Resource Natural Language Understanding via Active Learning
    • [cs.CL]FinnSentiment — A Finnish Social Media Corpus for Sentiment Polarity Annotation
    • [cs.CL]Pre-trained language models as knowledge bases for Automotive Complaint Analysis
    • [cs.CL]Ve’rdd. Narrowing the Gap between Paper Dictionaries, Low-Resource NLP and Community Involvement
    • [cs.CR]TrollHunter [Evader]: Automated Detection [Evasion] of TwitterTrolls During the COVID-19 Pandemic
    • [cs.CR]TrollHunter2020: Real-Time Detection of TrollingNarratives on Twitter During the 2020 US Elections
    • [cs.CR]Unleashing the Tiger: Inference Attacks on Split Learning
    • [cs.CV]A Note on Data Biases in Generative Models
    • [cs.CV]A high performance approach to detecting small targets in long range low quality infrared videos
    • [cs.CV]An Empirical Method to Quantify the Peripheral Performance Degradation in Deep Networks
    • [cs.CV]AuthNet: A Deep Learning based Authentication Mechanism using Temporal Facial Feature Movements
    • [cs.CV]Boosting offline handwritten text recognition in historical documents with few labeled lines
    • [cs.CV]Compositionally Generalizable 3D Structure Prediction
    • [cs.CV]Crop Classification under Varying Cloud Cover with Neural Ordinary Differential Equations
    • [cs.CV]Deep Learning for Wrist Fracture Detection: Are We There Yet?
    • [cs.CV]Detecting 32 Pedestrian Attributes for Autonomous Vehicles
    • [cs.CV]Effective Label Propagation for Discriminative Semi-Supervised Domain Adaptation
    • [cs.CV]F2Net: Learning to Focus on the Foreground for Unsupervised Video Object Segmentation
    • [cs.CV]Few-shot Image Generation with Elastic Weight Consolidation
    • [cs.CV]Generator Pyramid for High-Resolution Image Inpainting
    • [cs.CV]Global Context Aware RCNN for Object Detection
    • [cs.CV]Hierarchical Semantic Aggregation for Contrastive Representation Learning
    • [cs.CV]How Many Annotators Do We Need? — A Study on the Influence of Inter-Observer Variability on the Reliability of Automatic Mitotic Figure Assessment
    • [cs.CV]ID-Reveal: Identity-aware DeepFake Video Detection
    • [cs.CV]Is It a Plausible Colour? UCapsNet for Image Colourisation
    • [cs.CV]Isometric Multi-Shape Matching
    • [cs.CV]Learning Equivariant Representations
    • [cs.CV]Learning to Fuse Asymmetric Feature Maps in Siamese Trackers
    • [cs.CV]Multi-Scale 2D Temporal Adjacent Networks for Moment Localization with Natural Language
    • [cs.CV]Optical Wavelength Guided Self-Supervised Feature Learning For Galaxy Cluster Richness Estimate
    • [cs.CV]PeR-ViS: Person Retrieval in Video Surveillance using Semantic Description
    • [cs.CV]Photoacoustic Image Reconstruction Beyond Supervised to Compensate Limit-view and Remove Artifacts
    • [cs.CV]Practical No-box Adversarial Attacks against DNNs
    • [cs.CV]Prediction of Lane Number Using Results From Lane Detection
    • [cs.CV]Rethinking movie genre classification with fine grained semantic clustering
    • [cs.CV]SAFFIRE: System for Autonomous Feature Filtering and Intelligent ROI Estimation
    • [cs.CV]SMPLy Benchmarking 3D Human Pose Estimation in the Wild
    • [cs.CV]Self-Supervised VQA: Answering Visual Questions using Images and Captions
    • [cs.CV]Self-supervised Learning of Pixel-wise Anatomical Embeddings in Radiological Images
    • [cs.CV]Spatial-Temporal Alignment Network for Action Recognition and Detection
    • [cs.CV]Super-Selfish: Self-Supervised Learning onImages with PyTorch
    • [cs.CV]Towards Good Practices of U-Net for Traffic Forecasting
    • [cs.CV]Understanding Guided Image Captioning Performance across Domains
    • [cs.CY]Adaptivity and Personalization Application Scenarios in eParticipation
    • [cs.CY]Birdspotter: A Tool for Analyzing and Labeling Twitter Users
    • [cs.CY]Spatio-Temporal Analysis of On Demand Transit: A Case Study of Belleville, Canada
    • [cs.CY]The Treachery of Images in the Digital Sovereignty Debate
    • [cs.DB]Computational Complexity of Three Central Problems in Itemset Mining
    • [cs.DC]Energy Balanced Two-level Clustering for Large-Scale Wireless Sensor Networks based on the Gravitational Search Algorithm
    • [cs.DL]Ten Simple Rules for making a vocabulary FAIR
    • [cs.DS]Distributed domination on graph classes with bounded expansion
    • [cs.ET]A Single-Cycle MLP Classifier Using Analog MRAM-based Neurons and Synapses
    • [cs.GR]Multiscale Mesh Deformation Component Analysis with Attention-based Autoencoders
    • [cs.IR]FAST: A Fairness Assured Service Recommendation Strategy Considering Service Capacity Constraint
    • [cs.IR]Linear Regression Evaluation of Search Engine Automatic Search Performance Based on Hadoop and R
    • [cs.IR]Research Progress of News Recommendation Methods
    • [cs.IT]Joint Channel Estimation and Data Decoding using SVM-based Receivers
    • [cs.IT]Massive MIMO with Dense Arrays and 1-bit Data Converters
    • [cs.IT]Reconfigurable Intelligent Surface Aided Secure Transmission Exploiting Statistical CSI of Eavesdropper
    • [cs.LG]A Variant of Gradient Descent Algorithm Based on Gradient Averaging
    • [cs.LG]A novel multi-classifier information fusion based on Dempster-Shafer theory: application to vibration-based fault detection
    • [cs.LG]Advocating for Multiple Defense Strategies against Adversarial Examples
    • [cs.LG]Application of deep learning to large scale riverine flow velocity estimation
    • [cs.LG]Batch Group Normalization
    • [cs.LG]Bayesian Active Learning for Wearable Stress and Affect Detection
    • [cs.LG]Benchmarking Energy-Conserving Neural Networks for Learning Dynamics from Data
    • [cs.LG]Challenging common interpretability assumptions in feature attribution explanations
    • [cs.LG]Community detection using fast low-cardinality semidefinite programming
    • [cs.LG]Concept-based model explanations for Electronic Health Records
    • [cs.LG]DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation
    • [cs.LG]Deep Learning for Medical Anomaly Detection — A Survey
    • [cs.LG]Deep Learning for Road Traffic Forecasting: Does it Make a Difference?
    • [cs.LG]Demonstration-efficient Inverse Reinforcement Learning in Procedurally Generated Environments
    • [cs.LG]Detecting Trojaned DNNs Using Counterfactual Attributions
    • [cs.LG]Divide and Learn: A Divide and Conquer Approach for Predict+Optimize
    • [cs.LG]ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare
    • [cs.LG]Effect of the initial configuration of weights on the training and function of artificial neural networks
    • [cs.LG]Efficient semidefinite-programming-based inference for binary and multi-class MRFs
    • [cs.LG]Federated Learning with Heterogeneous Labels and Models for Mobile Activity Monitoring
    • [cs.LG]Kernel-convoluted Deep Neural Networks with Data Augmentation
    • [cs.LG]Logic Synthesis Meets Machine Learning:Trading Exactness for Generalization
    • [cs.LG]MLPerf Mobile Inference Benchmark: Why Mobile AI Benchmarking Is Hard and What to Do About It
    • [cs.LG]Mitigating Bias in Federated Learning
    • [cs.LG]Model-Agnostic Learning to Meta-Learn
    • [cs.LG]Multimodal Privacy-preserving Mood Prediction from Mobile Data: A Preliminary Study
    • [cs.LG]Neural Dynamic Policies for End-to-End Sensorimotor Learning
    • [cs.LG]Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning
    • [cs.LG]Non-Asymptotic Analysis of Excess Risk via Empirical Risk Landscape
    • [cs.LG]Offline Meta-level Model-based Reinforcement Learning Approach for Cold-Start Recommendation
    • [cs.LG]On Detecting Data Pollution Attacks On Recommender Systems Using Sequential GANs
    • [cs.LG]Optimising Design Verification Using Machine Learning: An Open Source Solution
    • [cs.LG]Planning from Pixels using Inverse Dynamics Models
    • [cs.LG]Proximal Policy Optimization Smoothed Algorithm
    • [cs.LG]Relational Pretrained Transformers towards Democratizing Data Preparation [Vision]
    • [cs.LG]Representation Based Complexity Measures for Predicting Generalization in Deep Learning
    • [cs.LG]Rethinking supervised learning: insights from biological learning and from calling it by its name
    • [cs.LG]Towards Natural Robustness Against Adversarial Examples
    • [cs.LG]Universal Approximation Property of Neural Ordinary Differential Equations
    • [cs.LG]Unsupervised Adversarially-Robust Representation Learning on Graphs
    • [cs.LG]Unsupervised embedding of trajectories captures the latent structure of mobility
    • [cs.RO]A data-set of piercing needle through deformable objects for Deep Learning from Demonstrations
    • [cs.RO]Autonomous Navigation with Mobile Robots using Deep Learning and the Robot Operating System
    • [cs.RO]Decentralized Multi-target Tracking with Multiple Quadrotors using a PHD Filter
    • [cs.RO]DeepSym: Deep Symbol Generation and Rule Learning from Unsupervised Continuous Robot Interaction for Planning
    • [cs.RO]LAMP: Learning a Motion Policy to Repeatedly Navigate in an Uncertain Environment
    • [cs.RO]P3-LOAM: PPP/LiDAR Loosely Coupled SLAM with Accurate Covariance Estimation and Robust RAIM in Urban Canyon Environment
    • [cs.RO]Pose-Based Servo Control with Soft Tactile Sensing
    • [cs.RO]Spatial Language Understanding for Object Search in Partially Observed Cityscale Environments
    • [cs.SD]Predicting Emotions Perceived from Sounds
    • [cs.SE]A Comparison of Natural Language Understanding Platforms for Chatbots in Software Engineering
    • [cs.SI]A Review of Latent Space Models for Social Networks
    • [cs.SI]Addressing machine learning concept drift reveals declining vaccine sentiment during the COVID-19 pandemic
    • [cs.SI]Learning Node Representations from Noisy Graph Structures
    • [cs.SI]Spread Mechanism and Influence Measurement of Online Rumors during COVID-19 Epidemic in China
    • [econ.EM]A Canonical Representation of Block Matrices with Applications to Covariance and Correlation Matrices
    • [econ.EM]A New Parametrization of Correlation Matrices
    • [econ.GN]Biased Programmers? Or Biased Data? A Field Experiment in Operationalizing AI Ethics
    • [econ.GN]The Managerial Effects of Algorithmic Fairness Activism
    • [eess.AS]A Correspondence Variational Autoencoder for Unsupervised Acoustic Word Embeddings
    • [eess.IV]Offset Curves Loss for Imbalanced Problem in Medical Segmentation
    • [eess.IV]Statistical inference of the inter-sample Dice distribution for discriminative CNN brain lesion segmentation models
    • [eess.IV]Ultrasound Scatterer Density Classification Using Convolutional Neural Networks by Exploiting Patch Statistics
    • [eess.IV]XraySyn: Realistic View Synthesis From a Single Radiograph Through CT Priors
    • [eess.SP]Deep Interference Mitigation and Denoising of Real-World FMCW Radar Signals
    • [math.AT]Hierarchical Clustering and Zeroth Persistent Homology
    • [math.OC]Generalized Proximal Methods for Pose Graph Optimization
    • [math.ST]Approximations of conditional probability density functions in Lebesgue spaces via mixture of experts models
    • [math.ST]Information Complexity Criterion for Model Selection in Robust Regression Using A New Robust Penalty Term
    • [math.ST]Ordinal pattern dependence as a multivariate dependence measure
    • [stat.AP]A latent variable approach to account for correlated inputs in global sensitivity analysis with cases from pharmacological systems modelling
    • [stat.AP]Efficient Social Distancing for COVID-19: An Integration of Economic Health and Public Health
    • [stat.CO]Penalised t-walk MCMC
    • [stat.ME]Bayesian hierarchical space-time models to improve multispecies assessment by combining observations from disparate fish surveys
    • [stat.ME]Derandomizing Knockoffs
    • [stat.ME]Joint Model for Survival and Multivariate Sparse Functional Data with Application to a Study of Alzheimer’s Disease
    • [stat.ME]Latent function-on-scalar regression models for observed sequences of binary data: a restricted likelihood approach
    • [stat.ME]Optimal Bayesian hierarchical model to accelerate the development of tissue-agnostic drugs and basket trials
    • [stat.ML]Non-monotone risk functions for learning
    • [stat.ML]When does gradient descent with logistic loss find interpolating two-layer networks?

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    • [cs.AI]Accelerating Road Sign Ground Truth Construction with Knowledge Graph and Machine Learning
    Ji Eun Kim, Cory Henson, Kevin Huang, Tuan A. Tran, Wan-Yi Lin
    http://arxiv.org/abs/2012.02672v1

    • [cs.AI]Constrained Risk-Averse Markov Decision Processes
    Mohamadreza Ahmadi, Ugo Rosolia, Michel D. Ingham, Richard M. Murray, Aaron D. Ames
    http://arxiv.org/abs/2012.02423v1

    • [cs.AI]Creativity of Deep Learning: Conceptualization and Assessment
    Johannes Schneider, Marcus Basalla
    http://arxiv.org/abs/2012.02282v1

    • [cs.AI]Explaining Predictions of Deep Neural Classifier via Activation Analysis
    Martin Stano, Wanda Benesova, Lukas Samuel Martak
    http://arxiv.org/abs/2012.02248v1

    • [cs.AI]Learning in two-player games between transparent opponents
    Adrian Hutter
    http://arxiv.org/abs/2012.02671v1

    • [cs.AI]Playing Text-Based Games with Common Sense
    Sahith Dambekodi, Spencer Frazier, Prithviraj Ammanabrolu, Mark O. Riedl
    http://arxiv.org/abs/2012.02757v1

    • [cs.AI]Understanding Attention: In Minds and Machines
    Shriraj P. Sawant, Shruti Singh
    http://arxiv.org/abs/2012.02659v1

    • [cs.CL]A Benchmark Dataset for Understandable Medical Language Translation
    Junyu Luo, Zifei Zheng, Hanzhong Ye, Muchao Ye, Yaqing Wang, Quanzeng You, Cao Xiao, Fenglong Ma
    http://arxiv.org/abs/2012.02420v1

    • [cs.CL]Automated Detection of Cyberbullying Against Women and Immigrants and Cross-domain Adaptability
    Thushari Atapattu, Mahen Herath, Georgia Zhang, Katrina Falkner
    http://arxiv.org/abs/2012.02565v1

    • [cs.CL]CUED_speech at TREC 2020 Podcast Summarisation Track
    Potsawee Manakul, Mark Gales
    http://arxiv.org/abs/2012.02535v1

    • [cs.CL]Coarse-to-Fine Entity Representations for Document-level Relation Extraction
    Damai Dai, Jing Ren, Shuang Zeng, Baobao Chang, Zhifang Sui
    http://arxiv.org/abs/2012.02507v1

    • [cs.CL]DDRel: A New Dataset for Interpersonal Relation Classification in Dyadic Dialogues
    Qi Jia, Hongru Huang, Kenny Q. Zhu
    http://arxiv.org/abs/2012.02553v1

    • [cs.CL]Data Processing and Annotation Schemes for FinCausal Shared Task
    Dominique Mariko, Estelle Labidurie, Yagmur Ozturk, Hanna Abi Akl, Hugues de Mazancourt
    http://arxiv.org/abs/2012.02498v1

    • [cs.CL]Delexicalized Paraphrase Generation
    Boya Yu, Konstantine Arkoudas, Wael Hamza
    http://arxiv.org/abs/2012.02763v1

    • [cs.CL]Event Guided Denoising for Multilingual Relation Learning
    Amith Ananthram, Emily Allaway, Kathleen McKeown
    http://arxiv.org/abs/2012.02721v1

    • [cs.CL]Evolving Character-Level DenseNet Architectures using Genetic Programming
    Trevor Londt, Xiaoying Gao, Peter Andreae
    http://arxiv.org/abs/2012.02327v1

    • [cs.CL]Evolving Character-level Convolutional Neural Networks for Text Classification
    Trevor Londt, Xiaoying Gao, Bing Xue, Peter Andreae
    http://arxiv.org/abs/2012.02223v1

    • [cs.CL]Few-Shot Event Detection with Prototypical Amortized Conditional Random Field
    Xin Cong, Shiyao Cui, Bowen Yu, Tingwen Liu, Yubin Wang, Bin Wang
    http://arxiv.org/abs/2012.02353v1

    • [cs.CL]Financial Document Causality Detection Shared Task (FinCausal 2020)
    Dominique Mariko, Hanna Abi Akl, Estelle Labidurie, Stéphane Durfort, Hugues de Mazancourt, Mahmoud El-Haj
    http://arxiv.org/abs/2012.02505v1

    • [cs.CL]Fine-tuning BERT for Low-Resource Natural Language Understanding via Active Learning
    Daniel Grießhaber, Johannes Maucher, Ngoc Thang Vu
    http://arxiv.org/abs/2012.02462v1

    • [cs.CL]FinnSentiment — A Finnish Social Media Corpus for Sentiment Polarity Annotation
    Krister Lindén, Tommi Jauhiainen, Sam Hardwick
    http://arxiv.org/abs/2012.02613v1

    • [cs.CL]Pre-trained language models as knowledge bases for Automotive Complaint Analysis
    V. D. Viellieber, M. Aßenmacher
    http://arxiv.org/abs/2012.02558v1

    • [cs.CL]Ve’rdd. Narrowing the Gap between Paper Dictionaries, Low-Resource NLP and Community Involvement
    Khalid Alnajjar, Mika Hämäläinen, Jack Rueter, Niko Partanen
    http://arxiv.org/abs/2012.02578v1

    • [cs.CR]TrollHunter [Evader]: Automated Detection [Evasion] of TwitterTrolls During the COVID-19 Pandemic
    Peter Jachim, Filipo Sharevski, Paige Treebridge
    http://arxiv.org/abs/2012.02586v1

    • [cs.CR]TrollHunter2020: Real-Time Detection of TrollingNarratives on Twitter During the 2020 US Elections
    Peter Jachim, Filipo Sharevski, Emma Pieroni
    http://arxiv.org/abs/2012.02606v1

    • [cs.CR]Unleashing the Tiger: Inference Attacks on Split Learning
    Dario Pasquini, Giuseppe Ateniese, Massimo Bernaschi
    http://arxiv.org/abs/2012.02670v1

    • [cs.CV]A Note on Data Biases in Generative Models
    Patrick Esser, Robin Rombach, Björn Ommer
    http://arxiv.org/abs/2012.02516v1

    • [cs.CV]A high performance approach to detecting small targets in long range low quality infrared videos
    Chiman Kwan, Bence Budavari
    http://arxiv.org/abs/2012.02579v1

    • [cs.CV]An Empirical Method to Quantify the Peripheral Performance Degradation in Deep Networks
    Calden Wloka, John K. Tsotsos
    http://arxiv.org/abs/2012.02749v1

    • [cs.CV]AuthNet: A Deep Learning based Authentication Mechanism using Temporal Facial Feature Movements
    Mohit Raghavendra, Pravan Omprakash, B R Mukesh, Sowmya Kamath
    http://arxiv.org/abs/2012.02515v1

    • [cs.CV]Boosting offline handwritten text recognition in historical documents with few labeled lines
    José Carlos Aradillas, Juan José Murillo-Fuentes, Pablo M. Olmos
    http://arxiv.org/abs/2012.02544v1

    • [cs.CV]Compositionally Generalizable 3D Structure Prediction
    Songfang Han, Jiayuan Gu, Kaichun Mo, Li Yi, Siyu Hu, Xuejin Chen, Hao Su
    http://arxiv.org/abs/2012.02493v1

    • [cs.CV]Crop Classification under Varying Cloud Cover with Neural Ordinary Differential Equations
    Nando Metzger, Mehmet Ozgur Turkoglu, Stefano D’Aronco, Jan Dirk Wegner, Konrad Schindler
    http://arxiv.org/abs/2012.02542v1

    • [cs.CV]Deep Learning for Wrist Fracture Detection: Are We There Yet?
    Abu Mohammed Raisuddin, Elias Vaattovaara, Mika Nevalainen, Marko Nikki, Elina Järvenpää, Kaisa Makkonen, Pekka Pinola, Tuula Palsio, Arttu Niemensivu, Osmo Tervonen, Aleksei Tiulpin
    http://arxiv.org/abs/2012.02577v1

    • [cs.CV]Detecting 32 Pedestrian Attributes for Autonomous Vehicles
    Taylor Mordan, Matthieu Cord, Patrick Pérez, Alexandre Alahi
    http://arxiv.org/abs/2012.02647v1

    • [cs.CV]Effective Label Propagation for Discriminative Semi-Supervised Domain Adaptation
    Zhiyong Huang, Kekai Sheng, Weiming Dong, Xing Mei, Chongyang Ma, Feiyue Huang, Dengwen Zhou, Changsheng Xu
    http://arxiv.org/abs/2012.02621v1

    • [cs.CV]F2Net: Learning to Focus on the Foreground for Unsupervised Video Object Segmentation
    Daizong Liu, Dongdong Yu, Changhu Wang, Pan Zhou
    http://arxiv.org/abs/2012.02534v1

    • [cs.CV]Few-shot Image Generation with Elastic Weight Consolidation
    Yijun Li, Richard Zhang, Jingwan Lu, Eli Shechtman
    http://arxiv.org/abs/2012.02780v1

    • [cs.CV]Generator Pyramid for High-Resolution Image Inpainting
    Leilei Cao, Tong Yang, Yixu Wang, Bo Yan, Yandong Guo
    http://arxiv.org/abs/2012.02381v1

    • [cs.CV]Global Context Aware RCNN for Object Detection
    Wenchao Zhang, Chong Fu, Haoyu Xie, Mai Zhu, Ming Tie, Junxin Chen
    http://arxiv.org/abs/2012.02637v1

    • [cs.CV]Hierarchical Semantic Aggregation for Contrastive Representation Learning
    Haohang Xu, Xiaopeng Zhang, Hao Li, Lingxi Xie, Hongkai Xiong, Qi Tian
    http://arxiv.org/abs/2012.02733v1

    • [cs.CV]How Many Annotators Do We Need? — A Study on the Influence of Inter-Observer Variability on the Reliability of Automatic Mitotic Figure Assessment
    Frauke Wilm, Christof A. Bertram, Christian Marzahl, Alexander Bartel, Taryn A. Donovan, Charles-Antoine Assenmacher, Kathrin Becker, Mark Bennett, Sarah Corner, Brieuc Cossic, Daniela Denk, Martina Dettwiler, Beatriz Garcia Gonzalez, Corinne Gurtner, Annika Lehmbecker, Sophie Merz, Stephanie Plog, Anja Schmidt, Rebecca C. Smedley, Marco Tecilla, Tuddow Thaiwong, Katharina Breininger, Matti Kiupel, Andreas Maier, Robert Klopfleisch, Marc Aubreville
    http://arxiv.org/abs/2012.02495v1

    • [cs.CV]ID-Reveal: Identity-aware DeepFake Video Detection
    Davide Cozzolino, Andreas Rössler, Justus Thies, Matthias Nießner, Luisa Verdoliva
    http://arxiv.org/abs/2012.02512v1

    • [cs.CV]Is It a Plausible Colour? UCapsNet for Image Colourisation
    Rita Pucci, Christian Micheloni, Gian Luca Foresti, Niki Martinel
    http://arxiv.org/abs/2012.02478v1

    • [cs.CV]Isometric Multi-Shape Matching
    Maolin Gao, Zorah Lähner, Johan Thunberg, Daniel Cremers, Florian Bernard
    http://arxiv.org/abs/2012.02689v1

    • [cs.CV]Learning Equivariant Representations
    Carlos Esteves
    http://arxiv.org/abs/2012.02771v1

    • [cs.CV]Learning to Fuse Asymmetric Feature Maps in Siamese Trackers
    Wencheng Han, Xingping Dong, Fahad Shahbaz Khan, Ling Shao, Jianbing Shen
    http://arxiv.org/abs/2012.02776v1

    • [cs.CV]Multi-Scale 2D Temporal Adjacent Networks for Moment Localization with Natural Language
    Songyang Zhang, Houwen Peng, Jianlong Fu, Yijuan Lu, Jiebo Luo
    http://arxiv.org/abs/2012.02646v1

    • [cs.CV]Optical Wavelength Guided Self-Supervised Feature Learning For Galaxy Cluster Richness Estimate
    Gongbo Liang, Yuanyuan Su, Sheng-Chieh Lin, Yu Zhang, Yuanyuan Zhang, Nathan Jacobs
    http://arxiv.org/abs/2012.02368v1

    • [cs.CV]PeR-ViS: Person Retrieval in Video Surveillance using Semantic Description
    Parshwa Shah, Arpit Garg, Vandit Gajjar
    http://arxiv.org/abs/2012.02408v1

    • [cs.CV]Photoacoustic Image Reconstruction Beyond Supervised to Compensate Limit-view and Remove Artifacts
    Hengrong Lan, Changchun Yang, Feng Gao, Fei Gao
    http://arxiv.org/abs/2012.02472v1

    • [cs.CV]Practical No-box Adversarial Attacks against DNNs
    Qizhang Li, Yiwen Guo, Hao Chen
    http://arxiv.org/abs/2012.02525v1

    • [cs.CV]Prediction of Lane Number Using Results From Lane Detection
    Panumate Chetprayoon, Fumihiko Takahashi, Yusuke Uchida
    http://arxiv.org/abs/2012.02604v1

    • [cs.CV]Rethinking movie genre classification with fine grained semantic clustering
    Edward Fish, Dr Andrew Gilbert, Jon Weinbren
    http://arxiv.org/abs/2012.02639v1

    • [cs.CV]SAFFIRE: System for Autonomous Feature Filtering and Intelligent ROI Estimation
    Marco Boschi, Luigi Di Stefano, Martino Alessandrini
    http://arxiv.org/abs/2012.02502v1

    • [cs.CV]SMPLy Benchmarking 3D Human Pose Estimation in the Wild
    Vincent Leroy, Philippe Weinzaepfel, Romain Brégier, Hadrien Combaluzier, Grégory Rogez
    http://arxiv.org/abs/2012.02743v1

    • [cs.CV]Self-Supervised VQA: Answering Visual Questions using Images and Captions
    Pratyay Banerjee, Tejas Gokhale, Yezhou Yang, Chitta Baral
    http://arxiv.org/abs/2012.02356v1

    • [cs.CV]Self-supervised Learning of Pixel-wise Anatomical Embeddings in Radiological Images
    Ke Yan, Jinzheng Cai, Dakai Jin, Shun Miao, Adam P. Harrison, Dazhou Guo, Youbao Tang, Jing Xiao, Jingjing Lu, Le Lu
    http://arxiv.org/abs/2012.02383v1

    • [cs.CV]Spatial-Temporal Alignment Network for Action Recognition and Detection
    Junwei Liang, Liangliang Cao, Xuehan Xiong, Ting Yu, Alexander Hauptmann
    http://arxiv.org/abs/2012.02426v1

    • [cs.CV]Super-Selfish: Self-Supervised Learning onImages with PyTorch
    Nicolas Wagner, Anirban Mukhopadhyay
    http://arxiv.org/abs/2012.02706v1

    • [cs.CV]Towards Good Practices of U-Net for Traffic Forecasting
    Jingwei Xu, Jianjin Zhang, Zhiyu Yao, Yunbo Wang
    http://arxiv.org/abs/2012.02598v1

    • [cs.CV]Understanding Guided Image Captioning Performance across Domains
    Edwin G. Ng, Bo Pang, Piyush Sharma, Radu Soricut
    http://arxiv.org/abs/2012.02339v1

    • [cs.CY]Adaptivity and Personalization Application Scenarios in eParticipation
    Babis Magoutas, Gregoris Mentzas
    http://arxiv.org/abs/2012.02571v1

    • [cs.CY]Birdspotter: A Tool for Analyzing and Labeling Twitter Users
    Rohit Ram, Quyu Kong, Marian-Andrei Rizoiu
    http://arxiv.org/abs/2012.02370v1

    • [cs.CY]Spatio-Temporal Analysis of On Demand Transit: A Case Study of Belleville, Canada
    Irum Sanaullah, Nael Alsaleh, Shadi Djavadian, Bilal Farooq
    http://arxiv.org/abs/2012.02600v1

    • [cs.CY]The Treachery of Images in the Digital Sovereignty Debate
    Jukka Ruohonen
    http://arxiv.org/abs/2012.02724v1

    • [cs.DB]Computational Complexity of Three Central Problems in Itemset Mining
    Christian Bessiere, Mohamed-Bachir Belaid, Nadjib Lazaar
    http://arxiv.org/abs/2012.02619v1

    • [cs.DC]Energy Balanced Two-level Clustering for Large-Scale Wireless Sensor Networks based on the Gravitational Search Algorithm
    Basilis Mamalis, Marios Perlitis
    http://arxiv.org/abs/2012.02536v1

    • [cs.DL]Ten Simple Rules for making a vocabulary FAIR
    Simon J D Cox, Alejandra N Gonzalez-Beltran, Barbara Magagna, Maria-Cristina Marinescu
    http://arxiv.org/abs/2012.02325v1

    • [cs.DS]Distributed domination on graph classes with bounded expansion
    Simeon Kublenz, Sebastian Siebertz, Alexandre Vigny
    http://arxiv.org/abs/2012.02701v1

    • [cs.ET]A Single-Cycle MLP Classifier Using Analog MRAM-based Neurons and Synapses
    Ramtin Zand
    http://arxiv.org/abs/2012.02695v1

    • [cs.GR]Multiscale Mesh Deformation Component Analysis with Attention-based Autoencoders
    Jie Yang, Lin Gao, Qingyang Tan, Yihua Huang, Shihong Xia, Yu-Kun Lai
    http://arxiv.org/abs/2012.02459v1

    • [cs.IR]FAST: A Fairness Assured Service Recommendation Strategy Considering Service Capacity Constraint
    Yao Wu, Jian Cao, Guandong Xu
    http://arxiv.org/abs/2012.02292v1

    • [cs.IR]Linear Regression Evaluation of Search Engine Automatic Search Performance Based on Hadoop and R
    Hong Xiong
    http://arxiv.org/abs/2012.02629v1

    • [cs.IR]Research Progress of News Recommendation Methods
    Jing Qin
    http://arxiv.org/abs/2012.02360v1

    • [cs.IT]Joint Channel Estimation and Data Decoding using SVM-based Receivers
    Sami Akın, Maxim Penner, Jürgen Peissig
    http://arxiv.org/abs/2012.02523v1

    • [cs.IT]Massive MIMO with Dense Arrays and 1-bit Data Converters
    Amine Mezghani, Faouzi Bellili, Robert W. Heath, Jr
    http://arxiv.org/abs/2012.02680v1

    • [cs.IT]Reconfigurable Intelligent Surface Aided Secure Transmission Exploiting Statistical CSI of Eavesdropper
    Cen Liu, Chang Tian, Peixi Liu
    http://arxiv.org/abs/2012.02466v1

    • [cs.LG]A Variant of Gradient Descent Algorithm Based on Gradient Averaging
    Saugata Purkayastha, Sukannya Purkayastha
    http://arxiv.org/abs/2012.02387v1

    • [cs.LG]A novel multi-classifier information fusion based on Dempster-Shafer theory: application to vibration-based fault detection
    Vahid Yaghoubi, Liangliang Cheng, Wim Van Paepegem, Mathias Kersemans
    http://arxiv.org/abs/2012.02481v1

    • [cs.LG]Advocating for Multiple Defense Strategies against Adversarial Examples
    Alexandre Araujo, Laurent Meunier, Rafael Pinot, Benjamin Negrevergne
    http://arxiv.org/abs/2012.02632v1

    • [cs.LG]Application of deep learning to large scale riverine flow velocity estimation
    Mojtaba Forghani, Yizhou Qian, Jonghyun Lee, Matthew W. Farthing, Tyler Hesser, Peter K. Kitanidis, Eric F. Darve
    http://arxiv.org/abs/2012.02620v1

    • [cs.LG]Batch Group Normalization
    Xiao-Yun Zhou, Jiacheng Sun, Nanyang Ye, Xu Lan, Qijun Luo, Bo-Lin Lai, Pedro Esperanca, Guang-Zhong Yang, Zhenguo Li
    http://arxiv.org/abs/2012.02782v1

    • [cs.LG]Bayesian Active Learning for Wearable Stress and Affect Detection
    Abhijith Ragav, Gautham Krishna Gudur
    http://arxiv.org/abs/2012.02702v1

    • [cs.LG]Benchmarking Energy-Conserving Neural Networks for Learning Dynamics from Data
    Yaofeng Desmond Zhong, Biswadip Dey, Amit Chakraborty
    http://arxiv.org/abs/2012.02334v1

    • [cs.LG]Challenging common interpretability assumptions in feature attribution explanations
    Jonathan Dinu, Jeffrey Bigham, J. Zico Kolter
    http://arxiv.org/abs/2012.02748v1

    • [cs.LG]Community detection using fast low-cardinality semidefinite programming
    Po-Wei Wang, J. Zico Kolter
    http://arxiv.org/abs/2012.02676v1

    • [cs.LG]Concept-based model explanations for Electronic Health Records
    Sebastien Baur, Shaobo Hou, Eric Loreaux, Diana Mincu, Anne Mottram, Ivan Protsyuk, Nenad Tomasev, Martin G Seneviratne, Alan Karthikesanlingam, Jessica Schrouff
    http://arxiv.org/abs/2012.02308v1

    • [cs.LG]DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation
    Jungeun Kim, Kookjin Lee, Dongeun Lee, Sheo Yon Jin, Noseong Park
    http://arxiv.org/abs/2012.02681v1

    • [cs.LG]Deep Learning for Medical Anomaly Detection — A Survey
    Tharindu Fernando, Harshala Gammulle, Simon Denman, Sridha Sridharan, Clinton Fookes
    http://arxiv.org/abs/2012.02364v1

    • [cs.LG]Deep Learning for Road Traffic Forecasting: Does it Make a Difference?
    Eric L. Manibardo, Ibai Laña, Javier Del Ser
    http://arxiv.org/abs/2012.02260v1

    • [cs.LG]Demonstration-efficient Inverse Reinforcement Learning in Procedurally Generated Environments
    Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov
    http://arxiv.org/abs/2012.02527v1

    • [cs.LG]Detecting Trojaned DNNs Using Counterfactual Attributions
    Karan Sikka, Indranil Sur, Susmit Jha, Anirban Roy, Ajay Divakaran
    http://arxiv.org/abs/2012.02275v1

    • [cs.LG]Divide and Learn: A Divide and Conquer Approach for Predict+Optimize
    Ali Ugur Guler, Emir Demirovic, Jeffrey Chan, James Bailey, Christopher Leckie, Peter J. Stuckey
    http://arxiv.org/abs/2012.02342v1

    • [cs.LG]ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare
    Ali Burak Ünal, Mete Akgün, Nico Pfeifer
    http://arxiv.org/abs/2012.02688v1

    • [cs.LG]Effect of the initial configuration of weights on the training and function of artificial neural networks
    R. J. Jesus, M. L. Antunes, R. A. da Costa, S. N. Dorogovtsev, J. F. F. Mendes, R. L. Aguiar
    http://arxiv.org/abs/2012.02550v1

    • [cs.LG]Efficient semidefinite-programming-based inference for binary and multi-class MRFs
    Chirag Pabbaraju, Po-Wei Wang, J. Zico Kolter
    http://arxiv.org/abs/2012.02661v1

    • [cs.LG]Federated Learning with Heterogeneous Labels and Models for Mobile Activity Monitoring
    Gautham Krishna Gudur, Satheesh K. Perepu
    http://arxiv.org/abs/2012.02539v1

    • [cs.LG]Kernel-convoluted Deep Neural Networks with Data Augmentation
    Minjin Kim, Young-geun Kim, Dongha Kim, Yongdai Kim, Myunghee Cho Paik
    http://arxiv.org/abs/2012.02521v1

    • [cs.LG]Logic Synthesis Meets Machine Learning:Trading Exactness for Generalization
    Shubham Rai, Walter Lau Neto, Yukio Miyasaka, Xinpei Zhang, Mingfei Yu, Qingyang Yi Masahiro Fujita, Guilherme B. Manske, Matheus F. Pontes, Leomar S. da Rosa Junior, Marilton S. de Aguiar, Paulo F. Butzen, Po-Chun Chien, Yu-Shan Huang, Hoa-Ren Wang, Jie-Hong R. Jiang, Jiaqi Gu, Zheng Zhao, Zixuan Jiang, David Z. Pan, Brunno A. de Abreu, Isac de Souza Campos, Augusto Berndt, Cristina Meinhardt, Jonata T. Carvalho, Mateus Grellert, Sergio Bampi, Aditya Lohana, Akash Kumar, Wei Zeng, Azadeh Davoodi, Rasit O. Topaloglu, Yuan Zhou, Jordan Dotzel, Yichi Zhang, Hanyu Wang, Zhiru Zhang, Valerio Tenace, Pierre-Emmanuel Gaillardon, Alan Mishchenko, Satrajit Chatterjee
    http://arxiv.org/abs/2012.02530v1

    • [cs.LG]MLPerf Mobile Inference Benchmark: Why Mobile AI Benchmarking Is Hard and What to Do About It
    Vijay Janapa Reddi, David Kanter, Peter Mattson, Jared Duke, Thai Nguyen, Ramesh Chukka, Kenneth Shiring, Koan-Sin Tan, Mark Charlebois, William Chou, Mostafa El-Khamy, Jungwook Hong, Michael Buch, Cindy Trinh, Thomas Atta-fosu, Fatih Cakir, Masoud Charkhabi, Xiaodong Chen, Jimmy Chiang, Dave Dexter, Woncheol Heo, Guenther Schmuelling, Maryam Shabani, Dylan Zika
    http://arxiv.org/abs/2012.02328v1

    • [cs.LG]Mitigating Bias in Federated Learning
    Annie Abay, Yi Zhou, Nathalie Baracaldo, Shashank Rajamoni, Ebube Chuba, Heiko Ludwig
    http://arxiv.org/abs/2012.02447v1

    • [cs.LG]Model-Agnostic Learning to Meta-Learn
    Arnout Devos, Yatin Dandi
    http://arxiv.org/abs/2012.02684v1

    • [cs.LG]Multimodal Privacy-preserving Mood Prediction from Mobile Data: A Preliminary Study
    Terrance Liu, Paul Pu Liang, Michal Muszynski, Ryo Ishii, David Brent, Randy Auerbach, Nicholas Allen, Louis-Philippe Morency
    http://arxiv.org/abs/2012.02359v1

    • [cs.LG]Neural Dynamic Policies for End-to-End Sensorimotor Learning
    Shikhar Bahl, Mustafa Mukadam, Abhinav Gupta, Deepak Pathak
    http://arxiv.org/abs/2012.02788v1

    • [cs.LG]Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning
    Woosuk Kwon, Gyeong-In Yu, Eunji Jeong, Byung-Gon Chun
    http://arxiv.org/abs/2012.02732v1

    • [cs.LG]Non-Asymptotic Analysis of Excess Risk via Empirical Risk Landscape
    Mingyang Yi, Ruoyu Wang, Zhi-Ming Ma
    http://arxiv.org/abs/2012.02456v1

    • [cs.LG]Offline Meta-level Model-based Reinforcement Learning Approach for Cold-Start Recommendation
    Yanan Wang, Yong Ge, Li Li, Rui Chen, Tong Xu
    http://arxiv.org/abs/2012.02476v1

    • [cs.LG]On Detecting Data Pollution Attacks On Recommender Systems Using Sequential GANs
    Behzad Shahrasbi, Venugopal Mani, Apoorv Reddy Arrabothu, Deepthi Sharma, Kannan Achan, Sushant Kumar
    http://arxiv.org/abs/2012.02509v1

    • [cs.LG]Optimising Design Verification Using Machine Learning: An Open Source Solution
    B. Samhita Varambally, Naman Sehgal
    http://arxiv.org/abs/2012.02453v1

    • [cs.LG]Planning from Pixels using Inverse Dynamics Models
    Keiran Paster, Sheila A. McIlraith, Jimmy Ba
    http://arxiv.org/abs/2012.02419v1

    • [cs.LG]Proximal Policy Optimization Smoothed Algorithm
    Wangshu Zhu, Andre Rosendo
    http://arxiv.org/abs/2012.02439v1

    • [cs.LG]Relational Pretrained Transformers towards Democratizing Data Preparation [Vision]**
    Nan Tang, Ju Fan, Fangyi Li, Jianhong Tu, Xiaoyong Du, Guoliang Li, Sam Madden, Mourad Ouzzani
    http://arxiv.org/abs/2012.02469v1

    • [cs.LG]Representation Based Complexity Measures for Predicting Generalization in Deep Learning
    Parth Natekar, Manik Sharma
    http://arxiv.org/abs/2012.02775v1

    • [cs.LG]Rethinking supervised learning: insights from biological learning and from calling it by its name
    Alex Hernandez-Garcia
    http://arxiv.org/abs/2012.02526v1

    • [cs.LG]Towards Natural Robustness Against Adversarial Examples
    Haoyu Chu, Shikui Wei, Yao Zhao
    http://arxiv.org/abs/2012.02452v1

    • [cs.LG]Universal Approximation Property of Neural Ordinary Differential Equations
    Takeshi Teshima, Koichi Tojo, Masahiro Ikeda, Isao Ishikawa, Kenta Oono
    http://arxiv.org/abs/2012.02414v1

    • [cs.LG]Unsupervised Adversarially-Robust Representation Learning on Graphs
    Jiarong Xu, Junru Chen, Yang Yang, Yizhou Sun, Chunping Wang, Jiangang Lu
    http://arxiv.org/abs/2012.02486v1

    • [cs.LG]Unsupervised embedding of trajectories captures the latent structure of mobility
    Dakota Murray, Jisung Yoon, Sadamori Kojaku, Rodrigo Costas, Woo-Sung Jung, Staša Milojević, Yong-Yeol Ahn
    http://arxiv.org/abs/2012.02785v1

    • [cs.RO]A data-set of piercing needle through deformable objects for Deep Learning from Demonstrations
    Hamidreza Hashempour, Kiyanoush Nazari, Fangxun Zhong, Amir Ghalamzan E.
    http://arxiv.org/abs/2012.02458v1

    • [cs.RO]Autonomous Navigation with Mobile Robots using Deep Learning and the Robot Operating System
    Anh Nguyen, Quang D. Tran
    http://arxiv.org/abs/2012.02417v1

    • [cs.RO]Decentralized Multi-target Tracking with Multiple Quadrotors using a PHD Filter
    Aniket Shirsat, Spring Berman
    http://arxiv.org/abs/2012.02340v1

    • [cs.RO]DeepSym: Deep Symbol Generation and Rule Learning from Unsupervised Continuous Robot Interaction for Planning
    Alper Ahmetoglu, M. Yunus Seker, Aysu Sayin, Serkan Bugur, Justus Piater, Erhan Oztop, Emre Ugur
    http://arxiv.org/abs/2012.02532v1

    • [cs.RO]LAMP: Learning a Motion Policy to Repeatedly Navigate in an Uncertain Environment
    Florence Tsang, Tristan Walker, Ryan A. MacDonald, Armin Sadeghi, Stephen L. Smith
    http://arxiv.org/abs/2012.02271v1

    • [cs.RO]P3-LOAM: PPP/LiDAR Loosely Coupled SLAM with Accurate Covariance Estimation and Robust RAIM in Urban Canyon Environment
    Tao Li, Ling Pei, Yan Xiang, Qi Wu, Songpengcheng Xia, Lihao Tao, Wenxian Yu
    http://arxiv.org/abs/2012.02399v1

    • [cs.RO]Pose-Based Servo Control with Soft Tactile Sensing
    Nathan F. Lepora, John Lloyd
    http://arxiv.org/abs/2012.02504v1

    • [cs.RO]Spatial Language Understanding for Object Search in Partially Observed Cityscale Environments
    Kaiyu Zheng, Deniz Bayazit, Rebecca Mathew, Ellie Pavlick, Stefanie Tellex
    http://arxiv.org/abs/2012.02705v1

    • [cs.SD]Predicting Emotions Perceived from Sounds
    Faranak Abri, Luis Felipe Gutiérrez, Akbar Siami Namin, David R. W. Sears, Keith S. Jones
    http://arxiv.org/abs/2012.02643v1

    • [cs.SE]A Comparison of Natural Language Understanding Platforms for Chatbots in Software Engineering
    Ahmad Abdellatif, Khaled Badran, Diego Elias Costa, Emad Shihab
    http://arxiv.org/abs/2012.02640v1

    • [cs.SI]A Review of Latent Space Models for Social Networks
    Juan Sosa, Lina Buitrago
    http://arxiv.org/abs/2012.02307v1

    • [cs.SI]Addressing machine learning concept drift reveals declining vaccine sentiment during the COVID-19 pandemic
    Martin Müller, Marcel Salathé
    http://arxiv.org/abs/2012.02197v1

    • [cs.SI]Learning Node Representations from Noisy Graph Structures
    Junshan Wang, Ziyao Li, Qingqing Long, Weiyu Zhang, Guojie Song, Chuan Shi
    http://arxiv.org/abs/2012.02434v1

    • [cs.SI]Spread Mechanism and Influence Measurement of Online Rumors during COVID-19 Epidemic in China
    Yiou Lin, Hang Lei, Yu Deng
    http://arxiv.org/abs/2012.02446v1

    • [econ.EM]A Canonical Representation of Block Matrices with Applications to Covariance and Correlation Matrices
    Ilya Archakov, Peter Reinhard Hansen
    http://arxiv.org/abs/2012.02698v1

    • [econ.EM]A New Parametrization of Correlation Matrices
    Ilya Archakov, Peter Reinhard Hansen
    http://arxiv.org/abs/2012.02395v1

    • [econ.GN]Biased Programmers? Or Biased Data? A Field Experiment in Operationalizing AI Ethics
    Bo Cowgill, Fabrizio Dell’Acqua, Samuel Deng, Daniel Hsu, Nakul Verma, Augustin Chaintreau
    http://arxiv.org/abs/2012.02394v1

    • [econ.GN]The Managerial Effects of Algorithmic Fairness Activism
    Bo Cowgill, Fabrizio Dell’Acqua, Sandra Matz
    http://arxiv.org/abs/2012.02393v1

    • [eess.AS]A Correspondence Variational Autoencoder for Unsupervised Acoustic Word Embeddings
    Puyuan Peng, Herman Kamper, Karen Livescu
    http://arxiv.org/abs/2012.02221v1

    • [eess.IV]Offset Curves Loss for Imbalanced Problem in Medical Segmentation
    Ngan Le, Trung Le, Kashu Yamazaki, Toan Duc Bui, Khoa Luu, Marios Savides
    http://arxiv.org/abs/2012.02463v1

    • [eess.IV]Statistical inference of the inter-sample Dice distribution for discriminative CNN brain lesion segmentation models
    Kevin Raina
    http://arxiv.org/abs/2012.02755v1

    • [eess.IV]Ultrasound Scatterer Density Classification Using Convolutional Neural Networks by Exploiting Patch Statistics
    Ali K. Z. Tehrani, Mina Amiri, Ivan M. Rosado-Mendez, Timothy J. Hall, Hassan Rivaz
    http://arxiv.org/abs/2012.02738v1

    • [eess.IV]XraySyn: Realistic View Synthesis From a Single Radiograph Through CT Priors
    Cheng Peng, Haofu Liao, Gina Wong, Jiebo Luo, Shaohua Kevin Zhou, Rama Chellappa
    http://arxiv.org/abs/2012.02407v1

    • [eess.SP]Deep Interference Mitigation and Denoising of Real-World FMCW Radar Signals
    Johanna Rock, Mate Toth, Paul Meissner, Franz Pernkopf
    http://arxiv.org/abs/2012.02529v1

    • [math.AT]Hierarchical Clustering and Zeroth Persistent Homology
    İsmail Güzel, Atabey Kaygun
    http://arxiv.org/abs/2012.02655v1

    • [math.OC]Generalized Proximal Methods for Pose Graph Optimization
    Taosha Fan, Todd Murphey
    http://arxiv.org/abs/2012.02709v1

    • [math.ST]Approximations of conditional probability density functions in Lebesgue spaces via mixture of experts models
    Hien Duy Nguyen, TrungTin Nguyen, Faicel Chamroukhi, Geoffrey McLachlan
    http://arxiv.org/abs/2012.02385v1

    • [math.ST]Information Complexity Criterion for Model Selection in Robust Regression Using A New Robust Penalty Term
    Esra Pamukçu, Mehmet Niyazi Çankaya
    http://arxiv.org/abs/2012.02468v1

    • [math.ST]Ordinal pattern dependence as a multivariate dependence measure
    Annika Betken, Herold Dehling, Ines Münker, Alexander Schnurr
    http://arxiv.org/abs/2012.02445v1

    • [stat.AP]A latent variable approach to account for correlated inputs in global sensitivity analysis with cases from pharmacological systems modelling
    Nicola Melillo, Adam S. Darwich
    http://arxiv.org/abs/2012.02500v1

    • [stat.AP]Efficient Social Distancing for COVID-19: An Integration of Economic Health and Public Health
    Kexin Chen, Chi Seng Pun, Hoi Ying Wong
    http://arxiv.org/abs/2012.02397v1

    • [stat.CO]Penalised t-walk MCMC
    Felipe J Medina-Aguayo, J Andrés Christen
    http://arxiv.org/abs/2012.02293v1

    • [stat.ME]Bayesian hierarchical space-time models to improve multispecies assessment by combining observations from disparate fish surveys
    Chibuzor C. Nnanatu, Murray S. A. Thompson, Michael A. Spence, Elena Couce, Jeroen van der Kooij, Christopher P. Lynam
    http://arxiv.org/abs/2012.02196v1

    • [stat.ME]Derandomizing Knockoffs
    Zhimei Ren, Yuting Wei, Emmanuel Candès
    http://arxiv.org/abs/2012.02717v1

    • [stat.ME]Joint Model for Survival and Multivariate Sparse Functional Data with Application to a Study of Alzheimer’s Disease
    Cai Li, Luo Xiao, Sheng Luo
    http://arxiv.org/abs/2012.02302v1

    • [stat.ME]Latent function-on-scalar regression models for observed sequences of binary data: a restricted likelihood approach
    Fatemeh Asgari, Mohammad Hossein Alamatsaz, Valeria Vitelli, Saeed Hayati
    http://arxiv.org/abs/2012.02635v1

    • [stat.ME]Optimal Bayesian hierarchical model to accelerate the development of tissue-agnostic drugs and basket trials
    Liyun Jiang, Lei Nie, Fangrong Yan, Ying Yuan
    http://arxiv.org/abs/2012.02378v1

    • [stat.ML]Non-monotone risk functions for learning
    Matthew J. Holland
    http://arxiv.org/abs/2012.02424v1

    • [stat.ML]When does gradient descent with logistic loss find interpolating two-layer networks?
    Niladri S. Chatterji, Philip M. Long, Peter L. Bartlett
    http://arxiv.org/abs/2012.02409v1