cs.AI - 人工智能 cs.CE - 计算工程、 金融和科学 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.DS - 数据结构与算法 cs.ET - 新兴技术 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.MA - 多代理系统 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.OH - 其他CS cs.RO - 机器人学 cs.SD - 声音处理 econ.EM - 计量经济学 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.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 physics.geo-ph - 地球物理学 q-bio.QM - 定量方法 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]AliMe KBQA: Question Answering over Structured Knowledge for E-commerce Customer Service
    • [cs.AI]CLOSURE: Assessing Systematic Generalization of CLEVR Models
    • [cs.AI]Learning Improvement Heuristics for Solving the Travelling Salesman Problem
    • [cs.CE]Robust Data-driven Profile-based Pricing Schemes
    • [cs.CL]Automatic Spanish Translation of the SQuAD Dataset for Multilingual Question Answering
    • [cs.CL]Extending Machine Language Models toward Human-Level Language Understanding
    • [cs.CL]Improving Interpretability of Word Embeddings by Generating Definition and Usage
    • [cs.CL]Personalized Patent Claim Generation and Measurement
    • [cs.CL]Text as Environment: A Deep Reinforcement Learning Text Readability Assessment Model
    • [cs.CR]HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning
    • [cs.CV]Automated Analysis of Femoral Artery Calcification Using Machine Learning Techniques
    • [cs.CV]CCCNet: An Attention Based Deep Learning Framework for Categorized Crowd Counting
    • [cs.CV]CineFilter: Unsupervised Filtering for Real Time Autonomous Camera Systems
    • [cs.CV]Deep Structured Implicit Functions
    • [cs.CV]Discriminative Dimension Reduction based on Mutual Information
    • [cs.CV]Estimating 3D Camera Pose from 2D Pedestrian Trajectories
    • [cs.CV]GPRInvNet: Deep Learning-Based Ground Penetrating Radar Data Inversion for Tunnel Lining
    • [cs.CV]Hue-Net: Intensity-based Image-to-Image Translation with Differentiable Histogram Loss Functions
    • [cs.CV]Human Motion Anticipation with Symbolic Label
    • [cs.CV]Improved Activity Forecasting for Generating Trajectories
    • [cs.CV]IoU-aware Single-stage Object Detector for Accurate Localization
    • [cs.CV]LatticeNet: Fast Point Cloud Segmentation Using Permutohedral Lattices
    • [cs.CV]Local Context Normalization: Revisiting Local Normalization
    • [cs.CV]MAGSAC++, a fast, reliable and accurate robust estimator
    • [cs.CV]Meaning guided video captioning
    • [cs.CV]Neural Voice Puppetry: Audio-driven Facial Reenactment
    • [cs.CV]Object Recognition with Human in the Loop Intelligent Frameworks
    • [cs.CV]One Framework to Register Them All: PointNet Encoding for Point Cloud Alignment
    • [cs.CV]Online Deep Reinforcement Learning for Autonomous UAV Navigation and Exploration of Outdoor Environments
    • [cs.CV]Photosequencing of Motion Blur using Short and Long Exposures
    • [cs.CV]Robust Gabor Networks
    • [cs.CV]Semantic segmentation of trajectories with improved agent models for pedestrian behavior analysis
    • [cs.CV]Simultaneous Detection and Removal of Dynamic Objects in Multi-view Images
    • [cs.CV]The Benefits of Close-Domain Fine-Tuning for Table Detection in Document Images
    • [cs.CV]Totally Deep Support Vector Machines
    • [cs.CV]Unified Generative Adversarial Networks for Controllable Image-to-Image Translation
    • [cs.CV]VIBE: Video Inference for Human Body Pose and Shape Estimation
    • [cs.CV]Variational Coupling Revisited: Simpler Models, Theoretical Connections, and Novel Applications
    • [cs.CV]Vectorizing World Buildings: Planar Graph Reconstruction by Primitive Detection and Relationship Classification
    • [cs.CV]Zooming into Face Forensics: A Pixel-level Analysis
    • [cs.CV]deepsing: Generating Sentiment-aware Visual Stories using Cross-modal Music Translation
    • [cs.CY]Calculate the carbon footprint of your IT assets with EcoDiag, an EcoInfo service
    • [cs.CY]Content Generation for Workforce Training
    • [cs.CY]Taking Ethics, Fairness, and Bias Seriously in Machine Learning for Disaster Risk Management
    • [cs.DC]EPIC: An Energy-Efficient, High-Performance GPGPU Computing Research Infrastructure
    • [cs.DC]From Hashgraph to a Family of Atomic Broadcast Algorithms
    • [cs.DC]Towards Auction-Based Function Placement in Serverless Fog Platforms
    • [cs.DS]Graph Sparsification for Derandomizing Massively Parallel Computation with Low Space
    • [cs.ET]A recipe for creating ideal hybrid memristive-CMOS neuromorphic computing systems
    • [cs.IR]SetRank: Learning a Permutation-Invariant Ranking Model for Information Retrieval
    • [cs.IT]An Integral Representation of the Logarithmic Function with Applications in Information Theory
    • [cs.IT]Fundamental Limits of Lossless Data Compression with Side Information
    • [cs.IT]Minimizing Age of Information with Power Constraints: Opportunistic Scheduling in Multi-State Time-Varying Networks
    • [cs.IT]On depth spectra of constacyclic codes over finite commutative chain rings
    • [cs.IT]Optimal Transmission Policies for Energy Harvesting Age of Information Systems with Battery Recovery
    • [cs.IT]Optimization of Integer-Forcing Precoding for Multi-User MIMO Downlink
    • [cs.IT]The Metagenomic Binning Problem: Clustering Markov Sequences
    • [cs.LG]An Efficient Explorative Sampling Considering the Generative Boundaries of Deep Generative Neural Networks
    • [cs.LG]Automatic Layout Generation with Applications in Machine Learning Engine Evaluation
    • [cs.LG]Bayesian Hyperparameter Optimization with BoTorch, GPyTorch and Ax
    • [cs.LG]Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution Detection
    • [cs.LG]Coloring graph neural networks for node disambiguation
    • [cs.LG]Deep One-bit Compressive Autoencoding
    • [cs.LG]Efficient Per-Example Gradient Computations in Convolutional Neural Networks
    • [cs.LG]Enabling Machine Learning Across Heterogeneous Sensor Networks with Graph Autoencoders
    • [cs.LG]Game Design for Eliciting Distinguishable Behavior
    • [cs.LG]Grid Search, Random Search, Genetic Algorithm: A Big Comparison for NAS
    • [cs.LG]Is Feature Diversity Necessary in Neural Network Initialization?
    • [cs.LG]Large-scale Kernel Methods and Applications to Lifelong Robot Learning
    • [cs.LG]Learning To Reach Goals Without Reinforcement Learning
    • [cs.LG]Linear Mode Connectivity and the Lottery Ticket Hypothesis
    • [cs.LG]On the relationship between multitask neural networks and multitask Gaussian Processes
    • [cs.LG]Provably Efficient Exploration in Policy Optimization
    • [cs.LG]REFINED (REpresentation of Features as Images with NEighborhood Dependencies): A novel feature representation for Convolutional Neural Networks
    • [cs.LG]Representation of Federated Learning via Worst-Case Robust Optimization Theory
    • [cs.LG]Speech-driven facial animation using polynomial fusion of features
    • [cs.LG]Sublinear Optimal Policy Value Estimation in Contextual Bandits
    • [cs.LG]Sublinear Time Numerical Linear Algebra for Structured Matrices
    • [cs.LG]Tensor Completion for Weakly-dependent Data on Graph for Metro Passenger Flow Prediction
    • [cs.LG]The PlayStation Reinforcement Learning Environment (PSXLE)
    • [cs.LG]The Use of Deep Learning for Symbolic Integration: A Review of (Lample and Charton, 2019)
    • [cs.LG]Towards Expressive Priors for Bayesian Neural Networks: Poisson Process Radial Basis Function Networks
    • [cs.LG]Towards a Robust Classifier: An MDL-Based Method for Generating Adversarial Examples
    • [cs.LG]Tracing the Propagation Path: A Flow Perspective of Representation Learning on Graphs
    • [cs.LG]What it Thinks is Important is Important: Robustness Transfers through Input Gradients
    • [cs.LO]Formal Verification of Debates in Argumentation Theory
    • [cs.MA]Biases for Emergent Communication in Multi-agent Reinforcement Learning
    • [cs.MA]Multi-Agent Task Allocation in Complementary Teams: A Hunter and Gatherer Approach
    • [cs.NE]STEERAGE: Synthesis of Neural Networks Using Architecture Search and Grow-and-Prune Methods
    • [cs.NE]Sequential vs. Integrated Algorithm Selection and Configuration: A Case Study for the Modular CMA-ES
    • [cs.NI]Peek Inside the Closed World: Evaluating Autoencoder-Based Detection of DDoS to Cloud
    • [cs.OH]The Use of Machine Learning and Big Five Personality Taxonomy to Predict Construction Workers’ Safety Behaviour
    • [cs.RO]0-Step Capturability, Motion Decomposition and Global Feedback Control of the 3D Variable Height-Inverted Pendulum
    • [cs.RO]A Billion Ways to Grasp: An Evaluation of Grasp Sampling Schemes on a Dense, Physics-based Grasp Data Set
    • [cs.RO]Graph Neural Networks for Decentralized Multi-Robot Path Planning
    • [cs.RO]Parareal with a Learned Coarse Model for Robotic Manipulation
    • [cs.SD]Encoding Musical Style with Transformer Autoencoders
    • [econ.EM]A Regularized Factor-augmented Vector Autoregressive Model
    • [eess.AS]Leveraging End-to-End Speech Recognition with Neural Architecture Search
    • [eess.AS]Measuring Mother-Infant Emotions By Audio Sensing
    • [eess.AS]On Neural Phone Recognition of Mixed-Source ECoG Signals
    • [eess.AS]Singing Synthesis: with a little help from my attention
    • [eess.IV]A Saliency Dataset of Head and Eye Movements for Augmented Reality
    • [eess.IV]An Approach to Super-Resolution of Sentinel-2 Images Based on Generative Adversarial Networks
    • [eess.IV]CARP: Compression through Adaptive Recursive Partitioning for Multi-dimensional Images
    • [eess.IV]Coronary Artery Plaque Characterization from CCTA Scans using Deep Learning and Radiomics
    • [eess.IV]EM-based approach to 3D reconstruction from single-waveform multispectral Lidar data
    • [eess.IV]IterNet: Retinal Image Segmentation Utilizing Structural Redundancy in Vessel Networks
    • [eess.IV]Learned Variable-Rate Image Compression with Residual Divisive Normalization
    • [eess.IV]SegTHOR: Segmentation of Thoracic Organs at Risk in CT images
    • [eess.IV]Understanding Important Features of Deep Learning Models for Transmission Electron Microscopy Image Segmentation
    • [eess.SP]Graph Theory and Metro Traffic Modelling
    • [eess.SP]Terahertz Communications (TeraCom): Challenges and Impact on 6G Wireless Systems
    • [eess.SY]Fundamental Entropic Laws and $\mathcal{L}_p$ Limitations of Feedback Systems: Implications for Machine-Learning-in-the-Loop Control
    • [eess.SY]Gaussian Conditionally Markov Sequences: Dynamic Models and Representations of Reciprocal and Other Classes
    • [math.NA]A numerical study of the pollution error and DPG adaptivity for long waveguide simulations
    • [math.OC]Control-Tutored Reinforcement Learning
    • [math.OC]Parallel Restarted SPIDER — Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity
    • [math.ST]Combining e-values and p-values
    • [math.ST]Diffusion based Gaussian process regression via heat kernel reconstruction
    • [math.ST]Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence
    • [math.ST]Graph quilting: graphical model selection from partially observed covariances
    • [math.ST]Scale invariant proper scoring rules Scale dependence: Why the average CRPS often is inappropriate for ranking probabilistic forecasts
    • [math.ST]Variable Selection Consistency of Gaussian Process Regression
    • [physics.geo-ph]Unsupervised classification of acoustic emissions from catalogs and fault time-to-failure prediction
    • [q-bio.QM]Pathway Activity Analysis and Metabolite Annotation for Untargeted Metabolomics using Probabilistic Modeling
    • [quant-ph]Bell Diagonal and Werner state generation: entanglement, non-locality, steering and discord on the IBM quantum computer
    • [quant-ph]Integration and Evaluation of Quantum Accelerators for Data-Driven User Functions
    • [stat.AP]A Hierarchical Modelling Framework for Correcting Delayed Reporting in Spatio-Temporal Disease Surveillance Data
    • [stat.AP]A low-rank semiparametric Bayesian spatial model for estimating extreme Red Sea surface temperature hotspots
    • [stat.AP]A state-space model for dynamic functional connectivity
    • [stat.CO]Exploratory data analysis for large-scale multiple testing problems and its application in gene expression studies
    • [stat.ME]Diagnosing model misspecification and performing generalized Bayes’ updates via probabilistic classifiers
    • [stat.ME]Identifying and Responding to Outlier Demand in Revenue Management
    • [stat.ME]Parametric mode regression for bounded data
    • [stat.ME]Sensitivity analysis for bias due to a misclassfied confounding variable in marginal structural models
    • [stat.ME]Testing Independence under Biased Sampling
    • [stat.ML]Adaptive Reticulum
    • [stat.ML]Measuring the Reliability of Reinforcement Learning Algorithms
    • [stat.ML]Near-optimal Oracle-efficient Algorithms for Stationary and Non-Stationary Stochastic Linear Bandits
    • [stat.ML]Normalizing Constant Estimation with Gaussianized Bridge Sampling

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

    • [cs.AI]AliMe KBQA: Question Answering over Structured Knowledge for E-commerce Customer Service
    Feng-Lin Li, Weijia Chen, Qi Huang, Yikun Guo
    http://arxiv.org/abs/1912.05728v1

    • [cs.AI]CLOSURE: Assessing Systematic Generalization of CLEVR Models
    Dzmitry Bahdanau, Harm de Vries, Timothy J. O’Donnell, Shikhar Murty, Philippe Beaudoin, Yoshua Bengio, Aaron Courville
    http://arxiv.org/abs/1912.05783v1

    • [cs.AI]Learning Improvement Heuristics for Solving the Travelling Salesman Problem
    Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang, Andrew Lim
    http://arxiv.org/abs/1912.05784v1

    • [cs.CE]Robust Data-driven Profile-based Pricing Schemes
    Jingshi Cui, Haoxiang Wang, Chenye Wu, Yang Yu
    http://arxiv.org/abs/1912.05731v1

    • [cs.CL]Automatic Spanish Translation of the SQuAD Dataset for Multilingual Question Answering
    Casimiro Pio Carrino, Marta R. Costa-jussà, José A. R. Fonollosa
    http://arxiv.org/abs/1912.05200v2

    • [cs.CL]Extending Machine Language Models toward Human-Level Language Understanding
    James L. McClelland, Felix Hill, Maja Rudolph, Jason Baldridge, Hinrich Schütze
    http://arxiv.org/abs/1912.05877v1

    • [cs.CL]Improving Interpretability of Word Embeddings by Generating Definition and Usage
    Haitong Zhang, Yongping Du, Jiaxin Sun, Qingxiao Li
    http://arxiv.org/abs/1912.05898v1

    • [cs.CL]Personalized Patent Claim Generation and Measurement
    Jieh-Sheng Lee
    http://arxiv.org/abs/1912.03502v2

    • [cs.CL]Text as Environment: A Deep Reinforcement Learning Text Readability Assessment Model
    Hamid Mohammadi, Seyed Hossein Khasteh
    http://arxiv.org/abs/1912.05957v1

    • [cs.CR]HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning
    Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, Heiko Ludwig
    http://arxiv.org/abs/1912.05897v1

    • [cs.CV]Automated Analysis of Femoral Artery Calcification Using Machine Learning Techniques
    Liang Zhao, Brendan Odigwe, Susan Lessner, Daniel G. Clair, Firas Mussa, Homayoun Valafar
    http://arxiv.org/abs/1912.06010v1

    • [cs.CV]CCCNet: An Attention Based Deep Learning Framework for Categorized Crowd Counting
    Sarkar Snigdha Sarathi Das, Syed Md. Mukit Rashid, Mohammed Eunus Ali
    http://arxiv.org/abs/1912.05765v1

    • [cs.CV]CineFilter: Unsupervised Filtering for Real Time Autonomous Camera Systems
    Sudheer Achary, Syed Ashar Javed, Nikita Shravan, K L Bhanu Moorthy, Vineet Gandhi, Anoop Namboodiri
    http://arxiv.org/abs/1912.05636v1

    • [cs.CV]Deep Structured Implicit Functions
    Kyle Genova, Forrester Cole, Avneesh Sud, Aaron Sarna, Thomas Funkhouser
    http://arxiv.org/abs/1912.06126v1

    • [cs.CV]Discriminative Dimension Reduction based on Mutual Information
    Orod Razeghi, Guoping Qiu
    http://arxiv.org/abs/1912.05631v1

    • [cs.CV]Estimating 3D Camera Pose from 2D Pedestrian Trajectories
    Yan Xu, Vivek Roy, Kris Kitani
    http://arxiv.org/abs/1912.05758v1

    • [cs.CV]GPRInvNet: Deep Learning-Based Ground Penetrating Radar Data Inversion for Tunnel Lining
    Bin Liu, Yuxiao Ren, Hanchi Liu, Hui Xu, Zhengfang Wang, Anthony G. Cohn, Peng Jiang
    http://arxiv.org/abs/1912.05759v1

    • [cs.CV]Hue-Net: Intensity-based Image-to-Image Translation with Differentiable Histogram Loss Functions
    Mor Avi-Aharon, Assaf Arbelle, Tammy Riklin Raviv
    http://arxiv.org/abs/1912.06044v1

    • [cs.CV]Human Motion Anticipation with Symbolic Label
    Julian Tanke, Juergen Gall
    http://arxiv.org/abs/1912.06079v1

    • [cs.CV]Improved Activity Forecasting for Generating Trajectories
    Daisuke Ogawa, Toru Tamaki, Tsubasa Hirakawa, Bisser Raytchev, Kazufumi Kaneda, Ken Yoda
    http://arxiv.org/abs/1912.05729v1

    • [cs.CV]IoU-aware Single-stage Object Detector for Accurate Localization
    Shengkai Wu, Xiaoping Li, Xinggang Wang
    http://arxiv.org/abs/1912.05992v1

    • [cs.CV]LatticeNet: Fast Point Cloud Segmentation Using Permutohedral Lattices
    Radu Alexandru Rosu, Peer Schütt, Jan Quenzel, Sven Behnke
    http://arxiv.org/abs/1912.05905v1

    • [cs.CV]Local Context Normalization: Revisiting Local Normalization
    Anthony Ortiz, Caleb Robinson, Mahmudulla Hassan, Dan Morris, Olac Fuentes, Christopher Kiekintveld, Nebojsa Jojic
    http://arxiv.org/abs/1912.05845v1

    • [cs.CV]MAGSAC++, a fast, reliable and accurate robust estimator
    Daniel Barath, Jana Noskova, Maksym Ivashechkin, Jiri Matas
    http://arxiv.org/abs/1912.05909v1

    • [cs.CV]Meaning guided video captioning
    Rushi J. Babariya, Toru Tamaki
    http://arxiv.org/abs/1912.05730v1

    • [cs.CV]Neural Voice Puppetry: Audio-driven Facial Reenactment
    Justus Thies, Mohamed Elgharib, Ayush Tewari, Christian Theobalt, Matthias Nießner
    http://arxiv.org/abs/1912.05566v1

    • [cs.CV]Object Recognition with Human in the Loop Intelligent Frameworks
    Orod Razeghi, Guoping Qiu
    http://arxiv.org/abs/1912.05575v1

    • [cs.CV]One Framework to Register Them All: PointNet Encoding for Point Cloud Alignment
    Vinit Sarode, Xueqian Li, Hunter Goforth, Yasuhiro Aoki, Animesh Dhagat, Rangaprasad Arun Srivatsan, Simon Lucey, Howie Choset
    http://arxiv.org/abs/1912.05766v1

    • [cs.CV]Online Deep Reinforcement Learning for Autonomous UAV Navigation and Exploration of Outdoor Environments
    Bruna G. Maciel-Pearson, Letizia Marchegiani, Samet Akcay, Amir Atapour-Abarghouei, James Garforth, Toby P. Breckon
    http://arxiv.org/abs/1912.05684v1

    • [cs.CV]Photosequencing of Motion Blur using Short and Long Exposures
    Vijay Rengarajan, Shuo Zhao, Ruiwen Zhen, John Glotzbach, Hamid Sheikh, Aswin C. Sankaranarayanan
    http://arxiv.org/abs/1912.06102v1

    • [cs.CV]Robust Gabor Networks
    Juan C. Pérez, Motasem Alfarra, Guillaume Jeanneret, Adel Bibi, Ali Thabet, Bernard Ghanem, Pablo Arbeláez
    http://arxiv.org/abs/1912.05661v1

    • [cs.CV]Semantic segmentation of trajectories with improved agent models for pedestrian behavior analysis
    Toru Tamaki, Daisuke Ogawa, Bisser Raytchev, Kazufumi Kaneda
    http://arxiv.org/abs/1912.05727v1

    • [cs.CV]Simultaneous Detection and Removal of Dynamic Objects in Multi-view Images
    Gagan Kanojia, Shanmuganathan Raman
    http://arxiv.org/abs/1912.05591v1

    • [cs.CV]The Benefits of Close-Domain Fine-Tuning for Table Detection in Document Images
    Ángela Casado-García, César Domínguez, Jónathan Heras, Eloy Mata, Vico Pascual
    http://arxiv.org/abs/1912.05846v1

    • [cs.CV]Totally Deep Support Vector Machines
    Hichem Sahbi
    http://arxiv.org/abs/1912.05864v1

    • [cs.CV]Unified Generative Adversarial Networks for Controllable Image-to-Image Translation
    Hao Tang, Hong Liu, Nicu Sebe
    http://arxiv.org/abs/1912.06112v1

    • [cs.CV]VIBE: Video Inference for Human Body Pose and Shape Estimation
    Muhammed Kocabas, Nikos Athanasiou, Michael J. Black
    http://arxiv.org/abs/1912.05656v1

    • [cs.CV]Variational Coupling Revisited: Simpler Models, Theoretical Connections, and Novel Applications
    Aaron Wewior, Joachim Weickert
    http://arxiv.org/abs/1912.05888v1

    • [cs.CV]Vectorizing World Buildings: Planar Graph Reconstruction by Primitive Detection and Relationship Classification
    Nelson Nauata, Yasutaka Furukawa
    http://arxiv.org/abs/1912.05135v2

    • [cs.CV]Zooming into Face Forensics: A Pixel-level Analysis
    Jia Li, Tong Shen, Wei Zhang, Hui Ren, Dan Zeng, Tao Mei
    http://arxiv.org/abs/1912.05790v1

    • [cs.CV]deepsing: Generating Sentiment-aware Visual Stories using Cross-modal Music Translation
    Nikolaos Passalis, Stavros Doropoulos
    http://arxiv.org/abs/1912.05654v1

    • [cs.CY]Calculate the carbon footprint of your IT assets with EcoDiag, an EcoInfo service
    Béatrice Montbroussous, Jonathan Schaeffer, Gabriel Moreau, Francoise Berthoud, Gabrielle Feltin
    http://arxiv.org/abs/1912.06038v1

    • [cs.CY]Content Generation for Workforce Training
    Holly Rushmeier, Kapil Chalil Madathil, Jessica Hodgins, Beth Mynatt, Tony Derose, Blair Macintyre, other workshop participants
    http://arxiv.org/abs/1912.05606v1

    • [cs.CY]Taking Ethics, Fairness, and Bias Seriously in Machine Learning for Disaster Risk Management
    Robert Soden, Dennis Wagenaar, Dave Luo, Annegien Tjieesen
    http://arxiv.org/abs/1912.05538v1

    • [cs.DC]EPIC: An Energy-Efficient, High-Performance GPGPU Computing Research Infrastructure
    Magnus Själander, Magnus Jahre, Gunnar Tufte, Nico Reissmann
    http://arxiv.org/abs/1912.05848v1

    • [cs.DC]From Hashgraph to a Family of Atomic Broadcast Algorithms
    Trafim Lasy
    http://arxiv.org/abs/1912.05895v1

    • [cs.DC]Towards Auction-Based Function Placement in Serverless Fog Platforms
    David Bermbach, Setareh Maghsudi, Jonathan Hasenburg, Tobias Pfandzelter
    http://arxiv.org/abs/1912.06096v1

    • [cs.DS]Graph Sparsification for Derandomizing Massively Parallel Computation with Low Space
    Artur Czumaj, Peter Davies, Merav Parter
    http://arxiv.org/abs/1912.05390v2

    • [cs.ET]A recipe for creating ideal hybrid memristive-CMOS neuromorphic computing systems
    Elisabetta Chicca, Giacomo Indiveri
    http://arxiv.org/abs/1912.05637v1

    • [cs.IR]SetRank: Learning a Permutation-Invariant Ranking Model for Information Retrieval
    Liang Pang, Jun Xu, Qingyao Ai, Yanyan Lan, Xueqi Cheng, Jirong Wen
    http://arxiv.org/abs/1912.05891v1

    • [cs.IT]An Integral Representation of the Logarithmic Function with Applications in Information Theory
    Neri Merhav, Igal Sason
    http://arxiv.org/abs/1912.05812v1

    • [cs.IT]Fundamental Limits of Lossless Data Compression with Side Information
    Lampros Gavalakis, Ioannis Kontoyiannis
    http://arxiv.org/abs/1912.05734v1

    • [cs.IT]Minimizing Age of Information with Power Constraints: Opportunistic Scheduling in Multi-State Time-Varying Networks
    Haoyue Tang, Jintao Wang, Linqi Song, Jian Song
    http://arxiv.org/abs/1912.05947v1

    • [cs.IT]On depth spectra of constacyclic codes over finite commutative chain rings
    Anuradha Sharma, Tania Sidana
    http://arxiv.org/abs/1912.05815v1

    • [cs.IT]Optimal Transmission Policies for Energy Harvesting Age of Information Systems with Battery Recovery
    Caglar Tunc, Shivendra Panwar
    http://arxiv.org/abs/1912.06119v1

    • [cs.IT]Optimization of Integer-Forcing Precoding for Multi-User MIMO Downlink
    Ricardo Bohaczuk Venturelli, Danilo Silva
    http://arxiv.org/abs/1912.05609v1

    • [cs.IT]The Metagenomic Binning Problem: Clustering Markov Sequences
    G. Greenberg, I. Shomorony
    http://arxiv.org/abs/1912.05741v1

    • [cs.LG]An Efficient Explorative Sampling Considering the Generative Boundaries of Deep Generative Neural Networks
    Giyoung Jeon, Haedong Jeong, Jaesik Choi
    http://arxiv.org/abs/1912.05827v1

    • [cs.LG]Automatic Layout Generation with Applications in Machine Learning Engine Evaluation
    Haoyu Yang, Wen Chen, Piyush Pathak, Frank Gennari, Ya-Chieh Lai, Bei Yu
    http://arxiv.org/abs/1912.05796v1

    • [cs.LG]Bayesian Hyperparameter Optimization with BoTorch, GPyTorch and Ax
    Daniel T. Chang
    http://arxiv.org/abs/1912.05686v1

    • [cs.LG]Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution Detection
    Erik Daxberger, José Miguel Hernández-Lobato
    http://arxiv.org/abs/1912.05651v1

    • [cs.LG]Coloring graph neural networks for node disambiguation
    George Dasoulas, Ludovic Dos Santos, Kevin Scaman, Aladin Virmaux
    http://arxiv.org/abs/1912.06058v1

    • [cs.LG]Deep One-bit Compressive Autoencoding
    Shahin Khobahi, Arindam Bose, Mojtaba Soltanalian
    http://arxiv.org/abs/1912.05539v1

    • [cs.LG]Efficient Per-Example Gradient Computations in Convolutional Neural Networks
    Gaspar Rochette, Andre Manoel, Eric W. Tramel
    http://arxiv.org/abs/1912.06015v1

    • [cs.LG]Enabling Machine Learning Across Heterogeneous Sensor Networks with Graph Autoencoders
    Johan Medrano, Fuchun Joseph Lin
    http://arxiv.org/abs/1912.05879v1

    • [cs.LG]Game Design for Eliciting Distinguishable Behavior
    Fan Yang, Liu Leqi, Yifan Wu, Zachary C. Lipton, Pradeep Ravikumar, William W. Cohen, Tom Mitchell
    http://arxiv.org/abs/1912.06074v1

    • [cs.LG]Grid Search, Random Search, Genetic Algorithm: A Big Comparison for NAS
    Petro Liashchynskyi, Pavlo Liashchynskyi
    http://arxiv.org/abs/1912.06059v1

    • [cs.LG]Is Feature Diversity Necessary in Neural Network Initialization?
    Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry
    http://arxiv.org/abs/1912.05137v2

    • [cs.LG]Large-scale Kernel Methods and Applications to Lifelong Robot Learning
    Raffaello Camoriano
    http://arxiv.org/abs/1912.05629v1

    • [cs.LG]Learning To Reach Goals Without Reinforcement Learning
    Dibya Ghosh, Abhishek Gupta, Justin Fu, Ashwin Reddy, Coline Devine, Benjamin Eysenbach, Sergey Levine
    http://arxiv.org/abs/1912.06088v1

    • [cs.LG]Linear Mode Connectivity and the Lottery Ticket Hypothesis
    Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin
    http://arxiv.org/abs/1912.05671v1

    • [cs.LG]On the relationship between multitask neural networks and multitask Gaussian Processes
    Karthikeyan K, Shubham Kumar Bharti, Piyush Rai
    http://arxiv.org/abs/1912.05723v1

    • [cs.LG]Provably Efficient Exploration in Policy Optimization
    Qi Cai, Zhuoran Yang, Chi Jin, Zhaoran Wang
    http://arxiv.org/abs/1912.05830v1

    • [cs.LG]REFINED (REpresentation of Features as Images with NEighborhood Dependencies): A novel feature representation for Convolutional Neural Networks
    Omid Bazgir, Ruibo Zhang, Saugato Rahman Dhruba, Raziur Rahman, Souparno Ghosh, Ranadip Pal
    http://arxiv.org/abs/1912.05687v1

    • [cs.LG]Representation of Federated Learning via Worst-Case Robust Optimization Theory
    Saeedeh Parsaeefard, Iman Tabrizian, Alberto Leon Garcia
    http://arxiv.org/abs/1912.05571v1

    • [cs.LG]Speech-driven facial animation using polynomial fusion of features
    Triantafyllos Kefalas, Konstantinos Vougioukas, Yannis Panagakis, Stavros Petridis, Jean Kossaifi, Maja Pantic
    http://arxiv.org/abs/1912.05833v1

    • [cs.LG]Sublinear Optimal Policy Value Estimation in Contextual Bandits
    Weihao Kong, Gregory Valiant, Emma Brunskill
    http://arxiv.org/abs/1912.06111v1

    • [cs.LG]Sublinear Time Numerical Linear Algebra for Structured Matrices
    Xiaofei Shi, David P. Woodruff
    http://arxiv.org/abs/1912.06060v1

    • [cs.LG]Tensor Completion for Weakly-dependent Data on Graph for Metro Passenger Flow Prediction
    Ziyue Li, Nurettin Dorukhan Sergin, Hao Yan, Chen Zhang, Fugee Tsung
    http://arxiv.org/abs/1912.05693v1

    • [cs.LG]The PlayStation Reinforcement Learning Environment (PSXLE)
    Carlos Purves, Cătălina Cangea, Petar Veličković
    http://arxiv.org/abs/1912.06101v1

    • [cs.LG]The Use of Deep Learning for Symbolic Integration: A Review of (Lample and Charton, 2019)
    Ernest Davis
    http://arxiv.org/abs/1912.05752v1

    • [cs.LG]Towards Expressive Priors for Bayesian Neural Networks: Poisson Process Radial Basis Function Networks
    Beau Coker, Melanie F. Pradier, Finale Doshi-Velez
    http://arxiv.org/abs/1912.05779v1

    • [cs.LG]Towards a Robust Classifier: An MDL-Based Method for Generating Adversarial Examples
    Behzad Asadi, Vijay Varadharajan
    http://arxiv.org/abs/1912.05945v1

    • [cs.LG]Tracing the Propagation Path: A Flow Perspective of Representation Learning on Graphs
    Menghan Wang, Kun Zhang, Gulin Li, Keping Yang, Luo Si
    http://arxiv.org/abs/1912.05977v1

    • [cs.LG]What it Thinks is Important is Important: Robustness Transfers through Input Gradients
    Alvin Chan, Yi Tay, Yew-Soon Ong
    http://arxiv.org/abs/1912.05699v1

    • [cs.LO]Formal Verification of Debates in Argumentation Theory
    Ria Jha, Francesco Belardinelli, Francesca Toni
    http://arxiv.org/abs/1912.05828v1

    • [cs.MA]Biases for Emergent Communication in Multi-agent Reinforcement Learning
    Tom Eccles, Yoram Bachrach, Guy Lever, Angeliki Lazaridou, Thore Graepel
    http://arxiv.org/abs/1912.05676v1

    • [cs.MA]Multi-Agent Task Allocation in Complementary Teams: A Hunter and Gatherer Approach
    Mehdi Dadvar, Saeed Moazami, Harley R. Myler, Hassan Zargarzadeh
    http://arxiv.org/abs/1912.05748v1

    • [cs.NE]STEERAGE: Synthesis of Neural Networks Using Architecture Search and Grow-and-Prune Methods
    Shayan Hassantabar, Xiaoliang Dai, Niraj K. Jha
    http://arxiv.org/abs/1912.05831v1

    • [cs.NE]Sequential vs. Integrated Algorithm Selection and Configuration: A Case Study for the Modular CMA-ES
    Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
    http://arxiv.org/abs/1912.05899v1

    • [cs.NI]Peek Inside the Closed World: Evaluating Autoencoder-Based Detection of DDoS to Cloud
    Hang Guo, Xun Fan, Anh Cao, Geoff Outhred, John Heidemann
    http://arxiv.org/abs/1912.05590v1

    • [cs.OH]The Use of Machine Learning and Big Five Personality Taxonomy to Predict Construction Workers’ Safety Behaviour
    Yifan Gao, Vicente A. Gonzalez, Tak Wing Yiu, Guillermo Cabrera-Guerrerod
    http://arxiv.org/abs/1912.05944v1

    • [cs.RO]0-Step Capturability, Motion Decomposition and Global Feedback Control of the 3D Variable Height-Inverted Pendulum
    Gabriel Garcia, Robert Griffin, Jerry Pratt
    http://arxiv.org/abs/1912.06078v1

    • [cs.RO]A Billion Ways to Grasp: An Evaluation of Grasp Sampling Schemes on a Dense, Physics-based Grasp Data Set
    Clemens Eppner, Arsalan Mousavian, Dieter Fox
    http://arxiv.org/abs/1912.05604v1

    • [cs.RO]Graph Neural Networks for Decentralized Multi-Robot Path Planning
    Qingbiao Li, Fernando Gama, Alejandro Ribeiro, Amanda Prorok
    http://arxiv.org/abs/1912.06095v1

    • [cs.RO]Parareal with a Learned Coarse Model for Robotic Manipulation
    Wisdom Agboh, Oliver Grainger, Daniel Ruprecht, Mehmet Dogar
    http://arxiv.org/abs/1912.05958v1

    • [cs.SD]Encoding Musical Style with Transformer Autoencoders
    Kristy Choi, Curtis Hawthorne, Ian Simon, Monica Dinculescu, Jesse Engel
    http://arxiv.org/abs/1912.05537v1

    • [econ.EM]A Regularized Factor-augmented Vector Autoregressive Model
    Maurizio Daniele, Julie Schnaitmann
    http://arxiv.org/abs/1912.06049v1

    • [eess.AS]Leveraging End-to-End Speech Recognition with Neural Architecture Search
    Ahmed Baruwa, Mojeed Abisiga, Ibrahim Gbadegesin, Afeez Fakunle
    http://arxiv.org/abs/1912.05946v1

    • [eess.AS]Measuring Mother-Infant Emotions By Audio Sensing
    Xuewen Yao, Dong He, Tiancheng Jing, Kaya de Barbaro
    http://arxiv.org/abs/1912.05920v1

    • [eess.AS]On Neural Phone Recognition of Mixed-Source ECoG Signals
    Ahmed Hussen Abdelaziz, Shuo-Yiin Chang, Nelson Morgan, Erik Edwards, Dorothea Kolossa, Dan Ellis, David A. Moses, Edward F. Chang
    http://arxiv.org/abs/1912.05869v1

    • [eess.AS]Singing Synthesis: with a little help from my attention
    Orazio Angelini, Alexis Moinet, Kayoko Yanagisawa, Thomas Drugman
    http://arxiv.org/abs/1912.05881v1

    • [eess.IV]A Saliency Dataset of Head and Eye Movements for Augmented Reality
    Yucheng Zhu, Dandan Zhu, Yiwei Yang, Huiyu Duan, Qiangqiang Zhou, Xiongkuo Min, Jiantao Zhou, Guangtao Zhai, Xiaokang Yang
    http://arxiv.org/abs/1912.05971v1

    • [eess.IV]An Approach to Super-Resolution of Sentinel-2 Images Based on Generative Adversarial Networks
    Kexin Zhang, Gencer Sumbul, Begüm Demir
    http://arxiv.org/abs/1912.06013v1

    • [eess.IV]CARP: Compression through Adaptive Recursive Partitioning for Multi-dimensional Images
    Rongjie Liu, Meng Li, Li Ma
    http://arxiv.org/abs/1912.05622v1

    • [eess.IV]Coronary Artery Plaque Characterization from CCTA Scans using Deep Learning and Radiomics
    Felix Denzinger, Michael Wels, Nishant Ravikumar, Katharina Breininger, Anika Reidelshöfer, Joachim Eckert, Michael Sühling, Axel Schmermund, Andreas Maier
    http://arxiv.org/abs/1912.06075v1

    • [eess.IV]EM-based approach to 3D reconstruction from single-waveform multispectral Lidar data
    Quentin Legros, Sylvain Meignen, Stephen McLaughlin, Yoann Altmann
    http://arxiv.org/abs/1912.06092v1

    • [eess.IV]IterNet: Retinal Image Segmentation Utilizing Structural Redundancy in Vessel Networks
    Liangzhi Li, Manisha Verma, Yuta Nakashima, Hajime Nagahara, Ryo Kawasaki
    http://arxiv.org/abs/1912.05763v1

    • [eess.IV]Learned Variable-Rate Image Compression with Residual Divisive Normalization
    Mohammad Akbari, Jie Liang, Jingning Han, Chengjie Tu
    http://arxiv.org/abs/1912.05688v1

    • [eess.IV]SegTHOR: Segmentation of Thoracic Organs at Risk in CT images
    Z. Lambert, C. Petitjean, B. Dubray, S. Ruan
    http://arxiv.org/abs/1912.05950v1

    • [eess.IV]Understanding Important Features of Deep Learning Models for Transmission Electron Microscopy Image Segmentation
    James P. Horwath, Dmitri N. Zakharov, Remi Megret, Eric A. Stach
    http://arxiv.org/abs/1912.06077v1

    • [eess.SP]Graph Theory and Metro Traffic Modelling
    Bruno Scalzo Dees, Anthony G. Constantinides, Danilo P. Mandic
    http://arxiv.org/abs/1912.05964v1

    • [eess.SP]Terahertz Communications (TeraCom): Challenges and Impact on 6G Wireless Systems
    Chong Han, Yongzhi Wu, Zhi Chen, Xudong Wang
    http://arxiv.org/abs/1912.06040v1

    • [eess.SY]Fundamental Entropic Laws and $\mathcal{L}_p$ Limitations of Feedback Systems: Implications for Machine-Learning-in-the-Loop Control
    Song Fang, Quanyan Zhu
    http://arxiv.org/abs/1912.05541v1

    • [eess.SY]Gaussian Conditionally Markov Sequences: Dynamic Models and Representations of Reciprocal and Other Classes
    Reza Rezaie, X. Rong Li
    http://arxiv.org/abs/1912.05739v1

    • [math.NA]A numerical study of the pollution error and DPG adaptivity for long waveguide simulations
    Stefan Henneking, Leszek Demkowicz
    http://arxiv.org/abs/1912.05716v1

    • [math.OC]Control-Tutored Reinforcement Learning
    Francesco De Lellis, Fabrizia Auletta, Giovanni Russo, Piero De Lellis, Mario di Bernardo
    http://arxiv.org/abs/1912.06085v1

    • [math.OC]Parallel Restarted SPIDER — Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity
    Pranay Sharma, Prashant Khanduri, Saikiran Bulusu, Ketan Rajawat, Pramod K. Varshney
    http://arxiv.org/abs/1912.06036v1

    • [math.ST]Combining e-values and p-values
    Vladimir Vovk, Ruodu Wang
    http://arxiv.org/abs/1912.06116v1

    • [math.ST]Diffusion based Gaussian process regression via heat kernel reconstruction
    David B Dunson, Hau-Tieng Wu, Nan Wu
    http://arxiv.org/abs/1912.05680v1

    • [math.ST]Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence
    Badr-Eddine Chérief-Abdellatif, Pierre Alquier
    http://arxiv.org/abs/1912.05737v1

    • [math.ST]Graph quilting: graphical model selection from partially observed covariances
    Giuseppe Vinci, Gautam Dasarathy, Genevera I. Allen
    http://arxiv.org/abs/1912.05573v1

    • [math.ST]Scale invariant proper scoring rules Scale dependence: Why the average CRPS often is inappropriate for ranking probabilistic forecasts
    David Bolin, Jonas Wallin
    http://arxiv.org/abs/1912.05642v1

    • [math.ST]Variable Selection Consistency of Gaussian Process Regression
    Sheng Jiang, Surya T. Tokdar
    http://arxiv.org/abs/1912.05738v1

    • [physics.geo-ph]Unsupervised classification of acoustic emissions from catalogs and fault time-to-failure prediction
    Hope Jasperson, Chas Bolton, Paul Johnson, Chris Marone, Maarten V. de Hoop
    http://arxiv.org/abs/1912.06087v1

    • [q-bio.QM]Pathway Activity Analysis and Metabolite Annotation for Untargeted Metabolomics using Probabilistic Modeling
    Ramtin Hosseini, Neda Hassanpour, Li-Ping Liu, Soha Hassoun
    http://arxiv.org/abs/1912.05753v1

    • [quant-ph]Bell Diagonal and Werner state generation: entanglement, non-locality, steering and discord on the IBM quantum computer
    Elias Riedel Gårding, Nicolas Schwaller, Su Yeon Chang, Samuel Bosch, Willy Robert Laborde, Javier Naya Hernandez, Chun Lam Chan, Frédéric Gessler, Xinyu Si, Marc-André Dupertuis, Nicolas Macris
    http://arxiv.org/abs/1912.06105v1

    • [quant-ph]Integration and Evaluation of Quantum Accelerators for Data-Driven User Functions
    Thomas Hubregtsen, Christoph Segler, Josef Pichlmeier, Aritra Sarkar, Thomas Gabor, Koen Bertels
    http://arxiv.org/abs/1912.06032v1

    • [stat.AP]A Hierarchical Modelling Framework for Correcting Delayed Reporting in Spatio-Temporal Disease Surveillance Data
    Oliver Stoner, Theo Economou
    http://arxiv.org/abs/1912.05965v1

    • [stat.AP]A low-rank semiparametric Bayesian spatial model for estimating extreme Red Sea surface temperature hotspots
    Arnab Hazra, Raphaël Huser
    http://arxiv.org/abs/1912.05657v1

    • [stat.AP]A state-space model for dynamic functional connectivity
    Sourish Chakravarty, Zachary D. Threlkeld, Yelena G. Bodien, Brian L. Edlow, Emery N. Brown
    http://arxiv.org/abs/1912.05595v1

    • [stat.CO]Exploratory data analysis for large-scale multiple testing problems and its application in gene expression studies
    Paramita Chakraborty, Chong Ma, John Grego, James Lynch
    http://arxiv.org/abs/1912.06030v1

    • [stat.ME]Diagnosing model misspecification and performing generalized Bayes’ updates via probabilistic classifiers
    Owen Thomas, Jukka Corander
    http://arxiv.org/abs/1912.05810v1

    • [stat.ME]Identifying and Responding to Outlier Demand in Revenue Management
    Nicola Rennie, Catherine Cleophas, Adam Sykulski, Florian Dost
    http://arxiv.org/abs/1912.05974v1

    • [stat.ME]Parametric mode regression for bounded data
    Haiming Zhou, Xianzheng Huang
    http://arxiv.org/abs/1912.05588v1

    • [stat.ME]Sensitivity analysis for bias due to a misclassfied confounding variable in marginal structural models
    Linda Nab, Rolf H. H. Groenwold, Maarten van Smeden, Ruth H. Keogh
    http://arxiv.org/abs/1912.05800v1

    • [stat.ME]Testing Independence under Biased Sampling
    Yaniv Tenzer, Micha Mandel, Or Zuk
    http://arxiv.org/abs/1912.05769v1

    • [stat.ML]Adaptive Reticulum
    Giuseppe Nuti, Lluís Antoni Jiménez Rugama, Kaspar Thommen
    http://arxiv.org/abs/1912.05901v1

    • [stat.ML]Measuring the Reliability of Reinforcement Learning Algorithms
    Stephanie C. Y. Chan, Sam Fishman, John Canny, Anoop Korattikara, Sergio Guadarrama
    http://arxiv.org/abs/1912.05663v1

    • [stat.ML]Near-optimal Oracle-efficient Algorithms for Stationary and Non-Stationary Stochastic Linear Bandits
    Baekjin Kim, Ambuj Tewari
    http://arxiv.org/abs/1912.05695v1

    • [stat.ML]Normalizing Constant Estimation with Gaussianized Bridge Sampling
    He Jia, Uroš Seljak
    http://arxiv.org/abs/1912.06073v1