astro-ph.CO - 宇宙学和天体物理学

    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.ET - 新兴技术 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.SI - 社交网络与信息网络 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 math.NA - 数值分析 math.ST - 统计理论 physics.soc-ph - 物理学与社会 q-bio.QM - 定量方法 q-fin.CP -计算金融学 q-fin.RM - 风险管理 q-fin.TR - 贸易与市场微观结构 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

    • [astro-ph.CO]Foreground model recognition through Neural Networks for CMB B-mode observations
    • [cs.AI]An Incremental Explanation of Inference in Hybrid Bayesian Networks for Increasing Model Trustworthiness and Supporting Clinical Decision Making
    • [cs.AI]Dynamic Experience Replay
    • [cs.AI]Knowledge Graphs
    • [cs.CL]A Study on Efficiency, Accuracy and Document Structure for Answer Sentence Selection
    • [cs.CL]An Empirical Accuracy Law for Sequential Machine Translation: the Case of Google Translate
    • [cs.CL]CLUECorpus2020: A Large-scale Chinese Corpus for Pre-training Language Model
    • [cs.CL]Fact Check-Worthiness Detection as Positive Unlabelled Learning
    • [cs.CL]HypoNLI: Exploring the Artificial Patterns of Hypothesis-only Bias in Natural Language Inference
    • [cs.CL]Kleister: A novel task for Information Extraction involving Long Documents with Complex Layout
    • [cs.CL]Multi-Task Learning with Auxiliary Speaker Identification for Conversational Emotion Recognition
    • [cs.CL]Natural Language Processing Advancements By Deep Learning: A Survey
    • [cs.CL]RecipeGPT: Generative Pre-training Based Cooking Recipe Generation and Evaluation System
    • [cs.CL]Zero-Shot Cross-Lingual Transfer with Meta Learning
    • [cs.CR]DANTE: A framework for mining and monitoring darknet traffic
    • [cs.CR]Detection and Recovery of Adversarial Attacks with Injected Attractors
    • [cs.CV]A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation
    • [cs.CV]A Benchmark for LiDAR-based Panoptic Segmentation based on KITTI
    • [cs.CV]AI outperformed every dermatologist: Improved dermoscopic melanoma diagnosis through customizing batch logic and loss function in an optimized Deep CNN architecture
    • [cs.CV]Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation
    • [cs.CV]Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization
    • [cs.CV]Cluster Pruning: An Efficient Filter Pruning Method for Edge AI Vision Applications
    • [cs.CV]Combating noisy labels by agreement: A joint training method with co-regularization
    • [cs.CV]Creating High Resolution Images with a Latent Adversarial Generator
    • [cs.CV]Detecting Attended Visual Targets in Video
    • [cs.CV]Drone Based RGBT Vehicle Detection and Counting: A Challenge
    • [cs.CV]Embedding Expansion: Augmentation in Embedding Space for Deep Metric Learning
    • [cs.CV]End-to-End Trainable One-Stage Parking Slot Detection Integrating Global and Local Information
    • [cs.CV]Exploring Partial Intrinsic and Extrinsic Symmetry in 3D Medical Imaging
    • [cs.CV]Fake Generated Painting Detection via Frequency Analysis
    • [cs.CV]Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep
    • [cs.CV]GANwriting: Content-Conditioned Generation of Styled Handwritten Word Images
    • [cs.CV]Image Generation from Freehand Scene Sketches
    • [cs.CV]Learning View and Target Invariant Visual Servoing for Navigation
    • [cs.CV]MarginDistillation: distillation for margin-based softmax
    • [cs.CV]Multi-object Tracking via End-to-end Tracklet Searching and Ranking
    • [cs.CV]Search Space of Adversarial Perturbations against Image Filters
    • [cs.CV]Self-Supervised Spatio-Temporal Representation Learning Using Variable Playback Speed Prediction
    • [cs.CV]The Impact of Hole Geometry on Relative Robustness of In-Painting Networks: An Empirical Study
    • [cs.CV]Towards Fair Cross-Domain Adaptation via Generative Learning
    • [cs.CV]Who Make Drivers Stop? Towards Driver-centric Risk Assessment: Risk Object Identification via Causal Inference
    • [cs.CY]Demographic Bias in Biometrics: A Survey on an Emerging Challenge
    • [cs.DB]Constant-Delay Enumeration for Nondeterministic Document Spanners
    • [cs.DB]Efficient and Effective Similar Subtrajectory Search with Deep Reinforcement Learning
    • [cs.DB]LAQP: Learning-based Approximate Query Processing
    • [cs.DC]Distributed Asynchronous Union-Find for Scalable Feature Tracking
    • [cs.DC]Moving the California distributed CMS xcache from bare metal into containers using Kubernetes
    • [cs.DC]Ordering Chaos: Memory-Aware Scheduling of Irregula
    7f20
    rly Wired Neural Networks for Edge Devices
    • [cs.DC]Que Sera Consensus: Simple Asynchronous Agreement with Private Coins and Threshold Logical Clocks
    • [cs.DC]Workload Scheduling on heterogeneous Mobile Edge Cloud in 5G networks to Minimize SLA Violation
    • [cs.DL]A Quantitative History of A.I. Research in the United States and China
    • [cs.ET]Deep Learning in Memristive Nanowire Networks
    • [cs.HC]Implementation of a Natural User Interface to Command a Drone
    • [cs.HC]Re-Imagining HCI: New Materialist Philosophy and Figurations as Tool for Design
    • [cs.HC]Towards Effective Human-AI Collaboration in GUI-Based Interactive Task Learning Agents
    • [cs.IR]Hadath: From Social Media Mapping to Multi-Resolution Event-Enriched Maps
    • [cs.IR]Recommender Systems Based on Generative Adversarial Networks: A Problem-Driven Perspective
    • [cs.IT]MEC-enhanced Information Freshness for Safety-critical C-V2X Communications
    • [cs.IT]Optimizing Joint Probabilistic Caching and Channel Access for Clustered {D2D} Networks
    • [cs.IT]Overhead-Aware Design of Reconfigurable Intelligent Surfaces in Smart Radio Environments
    • [cs.IT]Privacy-Aware Time-Series Data Sharing with Deep Reinforcement Learning
    • [cs.IT]Unsupervised Neural Universal Denoiser for Finite-Input General-Output Noisy Channel
    • [cs.IT]WGAN-based Autoencoder Training Over-the-air
    • [cs.LG]Adaptive Prediction Timing for Electronic Health Records
    • [cs.LG]Adversarial Robustness Through Local Lipschitzness
    • [cs.LG]Augmented Transformer Achieves 97% and 85% for Top5 Prediction of Direct and Classical Retro-Synthesis
    • [cs.LG]BERT as a Teacher: Contextual Embeddings for Sequence-Level Reward
    • [cs.LG]Balance Between Efficient and Effective Learning: Dense2Sparse Reward Shaping for Robot Manipulation with Environment Uncertainty
    • [cs.LG]Bandits with adversarial scaling
    • [cs.LG]Bayesian Domain Randomization for Sim-to-Real Transfer
    • [cs.LG]Comparing Rewinding and Fine-tuning in Neural Network Pruning
    • [cs.LG]Cross-GCN: Enhancing Graph Convolutional Network with $k$-Order Feature Interactions
    • [cs.LG]Does label smoothing mitigate label noise?
    • [cs.LG]Factorized Graph Representations for Semi-Supervised Learning from Sparse Data
    • [cs.LG]Fuzzy k-Nearest Neighbors with monotonicity constraints: Moving towards the robustness of monotonic noise
    • [cs.LG]Linear time dynamic programming for the exact path of optimal models selected from a finite set
    • [cs.LG]Neural Kernels Without Tangents
    • [cs.LG]On the Learning Property of Logistic and Softmax Losses for Deep Neural Networks
    • [cs.LG]On the performance of deep learning models for time series classification in streaming
    • [cs.LG]PAC-Bayesian Meta-learning with Implicit Prior
    • [cs.LG]Path Planning Using Probability Tensor Flows
    • [cs.LG]Permute to Train: A New Dimension to Training Deep Neural Networks
    • [cs.LG]Pruning Filters while Training for Efficiently Optimizing Deep Learning Networks
    • [cs.LG]PushNet: Efficient and Adaptive Neural Message Passing
    • [cs.LG]Real-time Federated Evolutionary Neural Architecture Search
    • [cs.LG]Recognition of Smoking Gesture Using Smart Watch Technology
    • [cs.LG]Reduced Dilation-Erosion Perceptron for Binary Classification
    • [cs.LG]SAFE: Scalable Automatic Feature Engineering Framework for Industrial Tasks
    • [cs.LG]SLEIPNIR: Deterministic and Provably Accurate Feature Expansion for Gaussian Process Regression with Derivatives
    • [cs.LG]Semi-supervised Learning Meets Factorization: Learning to Recommend with Chain Graph Model
    • [cs.LG]Stochastic Linear Contextual Bandits with Diverse Contexts
    • [cs.LG]TIME: A Transparent, Interpretable, Model-Adaptive and Explainable Neural Network for Dynamic Physical Processes
    • [cs.LG]Talking-Heads Attention
    • [cs.LG]What went wrong and when? Instance-wise Feature Importance for Time-series Models
    • [cs.LG]mmFall: Fall Detection using 4D MmWave Radar and Variational Recurrent Autoencoder
    • [cs.NE]Adaptive Verifiability-Driven Strategy for Evolutionary Approximation of Arithmetic Circuits
    • [cs.NE]Event-Based Angular Velocity Regression with Spiking Networks
    • [cs.NE]Plasticity-Enhanced Domain-Wall MTJ Neural Networks for Energy-Efficient Online Learning
    • [cs.NE]QED: using Quality-Environment-Diversity to evolve resilient robot swarms
    • [cs.NI]Optimal Sampling Cost in Wireless Networks with Age of Information Constraints
    • [cs.RO]A Geometric Perspective on Visual Imitation Learning
    • [cs.RO]Autonomous Driving at Intersections: A Critical-Turning-Point Approach for Left Turns
    • [cs.RO]Efficient Uncertainty-aware Decision-making for Automated Driving Using Guided Branching
    • [cs.RO]GOMP: Grasp-Optimized Motion Planning for Bin Picking
    • [cs.RO]Learning the sense of touch in simulation: a sim-to-real strategy for vision-based tactile sensing
    • [cs.RO]Learning,Generating and Adapting Wave Gestures for Expressive Human-Robot Interaction
    • [cs.RO]Learning-based distributionally robust motion control with Gaussian processes
    • [cs.RO]PointLoc: Deep Pose Regressor for LiDAR Point Cloud Localization
    • [cs.RO]Safe Planning for Self-Driving Via Adaptive Constrained ILQR
    • [cs.RO]Team O2AS at the World Robot Summit 2018: An Approach to Robotic Kitting and Assembly Tasks using General Purpose Grippers and Tools
    • [cs.RO]Touch the Wind: Simultaneous Airflow, Drag and Interaction Sensing on a Multirotor
    • [cs.RO]UAV Coverage Path Planning under Varying Power Constraints using Deep Reinforcement Learning
    • [cs.SI]AGL: a Scalable System for Industrial-purpose Graph Machine Learning
    • [cs.SI]EPINE: Enhanced Proximity Information Network Embedding
    • [cs.SI]Fragility of spectral clustering for networks with an overlapping structure
    • [cs.SI]Modeling the Popularity of Twitter Hashtags with Master Equations
    • [cs.SI]Properties of Erdős-Rényi Graphs
    • [cs.SI]The Multi-granularity in Graph Revealed by a Generalized Leading Tree
    • [econ.EM]Backward CUSUM for Testing and Monitoring Structural Change
    • [eess.AS]Auto-Tuning Spectral Clustering for Speaker Diarization Using Normalized Maximum Eigengap
    • [eess.AS]Real-time, Universal, and Robust Adversarial Attacks Against Speaker Recognition Systems
    • [eess.IV]Harnessing Multi-View Perspective of Light Fields for Low-Light Imaging
    • [eess.IV]Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised Knee Osteoarthritis Severity Grading from Plain Radiographs
    • [eess.SP]Approximate Message Passing with a Colored Aliasing Model for Variable Density Fourier Sampled Images
    • [eess.SP]Approximating the Hotelling Observer with Autoencoder-Learned Efficient Channels for Binary Signal Detection Tasks
    • [math.NA]Methods to Recover Unknown Processes in Partial Differential Equations Using Data
    • [math.ST]A comparison of maximum likelihood and absolute moments for the estimation of Hurst exponents in a stationary framework
    • [math.ST]A strong law of large numbers for simultaneously testing parameters of Lancaster bivariate distributions
    • [math.ST]Cumulant-free closed-form formulas for some common (dis)similarities between densities of an exponential family
    • [math.ST]II. High Dimensional Estimation under Weak Moment Assumptions: Structured Recovery and Matrix Estimation
    • [math.ST]Logistic regression with total variation regularization
    • [physics.soc-ph]Phase transitions in a decentralized graph-based approach to human language
    • [q-bio.QM]Variation in correlation between prognosis and histologic feature based on biopsy selection
    • [q-fin.CP]Non-stationary neural network for stock return prediction
    • [q-fin.RM]Application of Deep Neural Networks to assess corporate Credit Rating
    • [q-fin.TR]Robust Market Making via Adversarial Reinforcement Learning
    • [quant-ph]QSW_MPI: a framework for parallel simulation of quantum stochastic walks
    • [stat.AP]Bayesian A/B Testing for Business Decisions
    • [stat.AP]Individual Claims Forecasting with Bayesian Mixture Density Networks
    • [stat.AP]Multi-Output Gaussian Processes for Multi-Population Longevity Modeling
    • [stat.ME]A Multi-Way Correlation Coefficient
    • [stat.ME]A new approach in model selection for ordinal target variables
    • [stat.ME]Exploiting disagreement between high-dimensional variable selectors for uncertainty visualization
    • [stat.ME]Graphical modelling and partial characteristics for multitype and multivariate-marked spatio-temporal point processes
    • [stat.ME]Optimally adaptive Bayesian spectral density estimation
    • [stat.ME]Probabilistic
    80d
    performance estimators for computational chemistry methods: Systematic Improvement Probability and Ranking Probability Matrix. I. Theory
    • [stat.ME]Regularized Variational Data Assimilation for Bias Treatment using the Wasserstein Metric
    • [stat.ME]Robust Identification of Gene-Environment Interactions under High-Dimensional Accelerated Failure Time Models
    • [stat.ME]Spherical Principal Curves
    • [stat.ML]Bayesian System ID: Optimal management of parameter, model, and measurement uncertainty
    • [stat.ML]Knot Selection in Sparse Gaussian Processes with a Variational Objective
    • [stat.ML]Nonlinear Time Series Classification Using Bispectrum-based Deep Convolutional Neural Networks
    • [stat.ML]On the Convergence of Adam and Adagrad

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

    • [astro-ph.CO]Foreground model recognition through Neural Networks for CMB B-mode observations
    Farida Farsian, Nicoletta Krachmalnicoff, Carlo Baccigalupi
    http://arxiv.org/abs/2003.02278v1

    • [cs.AI]An Incremental Explanation of Inference in Hybrid Bayesian Networks for Increasing Model Trustworthiness and Supporting Clinical Decision Making
    Evangelia Kyrimi, Somayyeh Mossadegh, Nigel Tai, William Marsh
    http://arxiv.org/abs/2003.02599v1

    • [cs.AI]Dynamic Experience Replay
    Jieliang Luo, Hui Li
    http://arxiv.org/abs/2003.02372v1

    • [cs.AI]Knowledge Graphs
    Aidan Hogan, Eva Blomqvist, Michael Cochez, Claudia d’Amato, Gerard de Melo, Claudio Gutierrez, José Emilio Labra Gayo, Sabrina Kirrane, Sebastian Neumaier, Axel Polleres, Roberto Navigli, Axel-Cyrille Ngonga Ngomo, Sabbir M. Rashid, Anisa Rula, Lukas Schmelzeisen, Juan Sequeda, Steffen Staab, Antoine Zimmermann
    http://arxiv.org/abs/2003.02320v1

    • [cs.CL]A Study on Efficiency, Accuracy and Document Structure for Answer Sentence Selection
    Daniele Bonadiman, Alessandro Moschitti
    http://arxiv.org/abs/2003.02349v1

    • [cs.CL]An Empirical Accuracy Law for Sequential Machine Translation: the Case of Google Translate
    Lucas Nunes Sequeira, Bruno Moreschi, Fabio Gagliardi Cozman, Bernardo Fontes
    http://arxiv.org/abs/2003.02817v1

    • [cs.CL]CLUECorpus2020: A Large-scale Chinese Corpus for Pre-training Language Model
    Liang Xu, Xuanwei Zhang, Qianqian Dong
    http://arxiv.org/abs/2003.01355v2

    • [cs.CL]Fact Check-Worthiness Detection as Positive Unlabelled Learning
    Dustin Wright, Isabelle Augenstein
    http://arxiv.org/abs/2003.02736v1

    • [cs.CL]HypoNLI: Exploring the Artificial Patterns of Hypothesis-only Bias in Natural Language Inference
    Tianyu Liu, Xin Zheng, Baobao Chang, Zhifang Sui
    http://arxiv.org/abs/2003.02756v1

    • [cs.CL]Kleister: A novel task for Information Extraction involving Long Documents with Complex Layout
    Filip Graliński, Tomasz Stanisławek, Anna Wróblewska, Dawid Lipiński, Agnieszka Kaliska, Paulina Rosalska, Bartosz Topolski, Przemysław Biecek
    http://arxiv.org/abs/2003.02356v1

    • [cs.CL]Multi-Task Learning with Auxiliary Speaker Identification for Conversational Emotion Recognition
    Jingye Li, Meishan Zhang, Donghong Ji, Yijiang Liu
    http://arxiv.org/abs/2003.01478v2

    • [cs.CL]Natural Language Processing Advancements By Deep Learning: A Survey
    Amirsina Torfi, Rouzbeh A. Shirvani, Yaser Keneshloo, Nader Tavvaf, Edward A. Fox
    http://arxiv.org/abs/2003.01200v2

    • [cs.CL]RecipeGPT: Generative Pre-training Based Cooking Recipe Generation and Evaluation System
    Helena H. Lee, Ke Shu, Palakorn Achananuparp, Philips Kokoh Prasetyo, Yue Liu, Ee-Peng Lim, Lav R. Varshney
    http://arxiv.org/abs/2003.02498v1

    • [cs.CL]Zero-Shot Cross-Lingual Transfer with Meta Learning
    Farhad Nooralahzadeh, Giannis Bekoulis, Johannes Bjerva, Isabelle Augenstein
    http://arxiv.org/abs/2003.02739v1

    • [cs.CR]DANTE: A framework for mining and monitoring darknet traffic
    Dvir Cohen, Yisroel Mirsky, Yuval Elovici, Rami Puzis, Manuel Kamp, Tobias Martin, Asaf Shabtai
    http://arxiv.org/abs/2003.02575v1

    • [cs.CR]Detection and Recovery of Adversarial Attacks with Injected Attractors
    Jiyi Zhang, Ee-Chien Chang, Hwee Kuan Lee
    http://arxiv.org/abs/2003.02732v1

    • [cs.CV]A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation
    Jian Liang, Yunbo Wang, Dapeng Hu, Ran He, Jiashi Feng
    http://arxiv.org/abs/2003.02541v1

    • [cs.CV]A Benchmark for LiDAR-based Panoptic Segmentation based on KITTI
    Jens Behley, Andres Milioto, Cyrill Stachniss
    http://arxiv.org/abs/2003.02371v1

    • [cs.CV]AI outperformed every dermatologist: Improved dermoscopic melanoma diagnosis through customizing batch logic and loss function in an optimized Deep CNN architecture
    Cong Tri Pham, Mai Chi Luong, Dung Van Hoang, Antoine Doucet
    http://arxiv.org/abs/2003.02597v1

    • [cs.CV]Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation
    Min-Hung Chen, Baopu Li, Yingze Bao, Ghassan AlRegib, Zsolt Kira
    http://arxiv.org/abs/2003.02824v1

    • [cs.CV]Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization
    Saehyung Lee, Hyungyu Lee, Sungroh Yoon
    http://arxiv.org/abs/2003.02484v1

    • [cs.CV]Cluster Pruning: An Efficient Filter Pruning Method for Edge AI Vision Applications
    Chinthaka Gamanayake, Lahiru Jayasinghe, Benny Ng, Chau Yuen
    http://arxiv.org/abs/2003.02449v1

    • [cs.CV]Combating noisy labels by agreement: A joint training method with co-regularization
    Hongxin Wei, Lei Feng, Xiangyu Chen, Bo An
    http://arxiv.org/abs/2003.02752v1

    • [cs.CV]Creating High Resolution Images with a Latent Adversarial Generator
    David Berthelot, Peyman Milanfar, Ian Goodfellow
    http://arxiv.org/abs/2003.02365v1

    • [cs.CV]Detecting Attended Visual Targets in Video
    Eunji Chong, Yongxin Wang, Nataniel Ruiz, James M. Rehg
    http://arxiv.org/abs/2003.02501v1

    • [cs.CV]Drone Based RGBT Vehicle Detection and Counting: A Challenge
    Pengfei Zhu, Yiming Sun, Longyin Wen, Yu Feng, Qinghua Hu
    http://arxiv.org/abs/2003.02437v1

    • [cs.CV]Embedding Expansion: Augmentation in Embedding Space for Deep Metric Learning
    Byungsoo Ko, Geonmo Gu
    http://arxiv.org/abs/2003.02546v1

    • [cs.CV]End-to-End Trainable One-Stage Parking Slot Detection Integrating Global and Local Information
    Jae Kyu Suhr, Ho Gi Jung
    http://arxiv.org/abs/2003.02445v1

    • [cs.CV]Exploring Partial Intrinsic and Extrinsic Symmetry in 3D Medical Imaging
    Javad Fotouhi, Giacomo Taylor, Mathias Unberath, Alex Johnson, Sing Chun Lee, Greg Osgood, Mehran Armand, Nassir Navab
    http://arxiv.org/abs/2003.02294v1

    • [cs.CV]Fake Generated Painting Detection via Frequency Analysis
    Yong Bai, Yuanfang Guo, Jinjie Wei, Lin Lu, Rui Wang, Yunhong Wang
    http://arxiv.org/abs/2003.02467v1

    • [cs.CV]Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep
    Behnood Rasti, Danfeng Hong, Renlong Hang, Pedram Ghamisi, Xudong Kang, Jocelyn Chanussot, Jon Atli Benediktsson
    http://arxiv.org/abs/2003.02822v1

    • [cs.CV]GANwriting: Content-Conditioned Generation of Styled Handwritten Word Images
    Lei Kang, Pau Riba, Yaxing Wang, Marçal Rusiñol, Alicia Fornés, Mauricio Villegas
    http://arxiv.org/abs/2003.02567v1

    • [cs.CV]Image Generation from Freehand Scene Sketches
    Chengying Gao, Qi Liu, Qi Xu, Jianzhuang Liu, Limin Wang, Changqing Zou
    http://arxiv.org/abs/2003.02683v1

    • [cs.CV]Learning View and Target Invariant Visual Servoing for Navigation
    Yimeng Li, Jana Kosecka
    http://arxiv.org/abs/2003.02327v1

    • [cs.CV]MarginDistillation: distillation for margin-based softmax
    David Svitov, Sergey Alyamkin
    http://arxiv.org/abs/2003.02586v1

    • [cs.CV]Multi-object Tracking via End-to-end Tracklet Searching and Ranking
    Tao Hu, Lichao Huang, Han Shen
    http://arxiv.org/abs/2003.02795v1

    • [cs.CV]Search Space of Adversarial Perturbations against Image Filters
    Dang Duy Thang, Toshihiro Matsui
    http://arxiv.org/abs/2003.02750v1

    • [cs.CV]Self-Supervised Spatio-Temporal Representation Learning Using Variable Playback Speed Prediction
    Hyeon Cho, Taehoon Kim, Hyung Jin Chang, Wonjun Hwang
    http://arxiv.org/abs/2003.02692v1

    • [cs.CV]The Impact of Hole Geometry on Relative Robustness of In-Painting Networks: An Empirical Study
    Masood S. Mortazavi, Ning Yan
    http://arxiv.org/abs/2003.02314v1

    • [cs.CV]Towards Fair Cross-Domain Adaptation via Generative Learning
    Tongxin Wang, Zhengming Ding, Wei Shao, Haixu Tang, Kun Huang
    http://arxiv.org/abs/2003.02366v1

    • [cs.CV]Who Make Drivers Stop? Towards Driver-centric Risk Assessment: Risk Object Identification via Causal Inference
    Chengxi Li, Stanley H. Chan, Yi-Ting Chen
    http://arxiv.org/abs/2003.02425v1

    • [cs.CY]Demographic Bias in Biometrics: A Survey on an Emerging Challenge
    P. Drozdowski, C. Rathgeb, A. Dantcheva, N. Damer, C. Busch
    http://arxiv.org/abs/2003.02488v1

    • [cs.DB]Constant-Delay Enumeration for Nondeterministic Document Spanners
    Antoine Amarilli, Pierre Bourhis, Stefan Mengel, Matthias Niewerth
    http://arxiv.org/abs/2003.02576v1

    • [cs.DB]Efficient and Effective Similar Subtrajectory Search with Deep Reinforcement Learning
    Zheng Wang, Cheng Long, Gao Cong, Yiding Liu
    http://arxiv.org/abs/2003.02542v1

    • [cs.DB]LAQP: Learning-based Approximate Query Processing
    Meifan Zhang, Hongzhi Wang
    http://arxiv.org/abs/2003.02446v1

    • [cs.DC]Distributed Asynchronous Union-Find for Scalable Feature Tracking
    Jiayi Xu, Hanqi Guo, Han-Wei Shen, Mukund Raj, Xueqiao Xu, Xueyun Wang, Zhehui Wang, Tom Peterka
    http://arxiv.org/abs/2003.02351v1

    • [cs.DC]Moving the California distributed CMS xcache from bare metal into containers using Kubernetes
    Edgar Fajardo, Matevz Tadel, Justas Balcas, Alja Tadel, Frank Wuerthwein, Diego Davila, Jonathan Guiang, Igor Sfiligoi
    http://arxiv.org/abs/2003.02319v1

    • [cs.DC]Ordering Chaos: Memory-Aware Scheduling of Irregula
    7f20
    rly Wired Neural Networks for Edge Devices
    Byung Hoon Ahn, Jinwon Lee, Jamie Menjay Lin, Hsin-Pai Cheng, Jilei Hou, Hadi Esmaeilzadeh
    http://arxiv.org/abs/2003.02369v1

    • [cs.DC]Que Sera Consensus: Simple Asynchronous Agreement with Private Coins and Threshold Logical Clocks
    Bryan Ford, Philipp Jovanovic, Ewa Syta
    http://arxiv.org/abs/2003.02291v1

    • [cs.DC]Workload Scheduling on heterogeneous Mobile Edge Cloud in 5G networks to Minimize SLA Violation
    Mostafa Hadadian Nejad Yousefi, Seyed Amirmasoud Ghiassi, Boshra Sadat Hashemi, Maziar Goudarzi
    http://arxiv.org/abs/2003.02820v1

    • [cs.DL]A Quantitative History of A.I. Research in the United States and China
    Daniel Ish, Andrew Lohn, Christian Curriden
    http://arxiv.org/abs/2003.02763v1

    • [cs.ET]Deep Learning in Memristive Nanowire Networks
    Jack D. Kendall, Ross D. Pantone, Juan C. Nino
    http://arxiv.org/abs/2003.02642v1

    • [cs.HC]Implementation of a Natural User Interface to Command a Drone
    Brandon Yam-Viramontes, Diego Mercado-Ravell
    http://arxiv.org/abs/2003.02662v1

    • [cs.HC]Re-Imagining HCI: New Materialist Philosophy and Figurations as Tool for Design
    Goda Klumbyte, Claude Draude, Loren Britton
    http://arxiv.org/abs/2003.02312v1

    • [cs.HC]Towards Effective Human-AI Collaboration in GUI-Based Interactive Task Learning Agents
    Toby Jia-Jun Li, Jingya Chen, Tom M. Mitchell, Brad A. Myers
    http://arxiv.org/abs/2003.02622v1

    • [cs.IR]Hadath: From Social Media Mapping to Multi-Resolution Event-Enriched Maps
    Faizan Ur Rehman, Imad Afyouni, Ahmed Lbath, Saleh Basalamah
    http://arxiv.org/abs/2003.02615v1

    • [cs.IR]Recommender Systems Based on Generative Adversarial Networks: A Problem-Driven Perspective
    Min Gao, Junwei Zhang, Junliang Yu, Jundong Li, Junhao Wen, Qingyu Xiong
    http://arxiv.org/abs/2003.02474v1

    • [cs.IT]MEC-enhanced Information Freshness for Safety-critical C-V2X Communications
    Mustafa Emara, Miltiades C. Filippou, Dario Sabella
    http://arxiv.org/abs/2003.02495v1

    • [cs.IT]Optimizing Joint Probabilistic Caching and Channel Access for Clustered {D2D} Networks
    Ramy Amer, M. Majid Butt, Nicola Marchetti
    http://arxiv.org/abs/2003.02676v1

    • [cs.IT]Overhead-Aware Design of Reconfigurable Intelligent Surfaces in Smart Radio Environments
    Alessio Zappone, Marco Di Renzo, Farshad Shams, Xuewen Qian, Merouane Debbah
    http://arxiv.org/abs/2003.02538v1

    • [cs.IT]Privacy-Aware Time-Series Data Sharing with Deep Reinforcement Learning
    Ecenaz Erdemir, Pier Luigi Dragotti, Deniz Gunduz
    http://arxiv.org/abs/2003.02685v1

    • [cs.IT]Unsupervised Neural Universal Denoiser for Finite-Input General-Output Noisy Channel
    Tae-Eon Park, Taesup Moon
    http://arxiv.org/abs/2003.02623v1

    • [cs.IT]WGAN-based Autoencoder Training Over-the-air
    Sebastian Dörner, Marcus Henninger, Sebastian Cammerer, Stephan ten Brink
    http://arxiv.org/abs/2003.02744v1

    • [cs.LG]Adaptive Prediction Timing for Electronic Health Records
    Jacob Deasy, Ari Ercole, Pietro Liò
    http://arxiv.org/abs/2003.02554v1

    • [cs.LG]Adversarial Robustness Through Local Lipschitzness
    Yao-Yuan Yang, Cyrus Rashtchian, Hongyang Zhang, Ruslan Salakhutdinov, Kamalika Chaudhuri
    http://arxiv.org/abs/2003.02460v1

    • [cs.LG]Augmented Transformer Achieves 97% and 85% for Top5 Prediction of Direct and Classical Retro-Synthesis
    Igor V. Tetko, Pavel Karpov, Ruud Van Deursen, Guillaume Godin
    http://arxiv.org/abs/2003.02804v1

    • [cs.LG]BERT as a Teacher: Contextual Embeddings for Sequence-Level Reward
    Florian Schmidt, Thomas Hofmann
    http://arxiv.org/abs/2003.02738v1

    • [cs.LG]Balance Between Efficient and Effective Learning: Dense2Sparse Reward Shaping for Robot Manipulation with Environment Uncertainty
    Yongle Luo, Kun Dong, Lili Zhao, Zhiyong Sun, Chao Zhou, Bo Song
    http://arxiv.org/abs/2003.02740v1

    • [cs.LG]Bandits with adversarial scaling
    Thodoris Lykouris, Vahab Mirrokni, Renato Paes Leme
    http://arxiv.org/abs/2003.02287v1

    • [cs.LG]Bayesian Domain Randomization for Sim-to-Real Transfer
    Fabio Muratore, Christian Eilers, Michael Gienger, Jan Peters
    http://arxiv.org/abs/2003.02471v1

    • [cs.LG]Comparing Rewinding and Fine-tuning in Neural Network Pruning
    Alex Renda, Jonathan Frankle, Michael Carbin
    http://arxiv.org/abs/2003.02389v1

    • [cs.LG]Cross-GCN: Enhancing Graph Convolutional Network with $k$-Order Feature Interactions
    Fuli Feng, Xiangnan He, Hanwang Zhang, Tat-Seng Chua
    http://arxiv.org/abs/2003.02587v1

    • [cs.LG]Does label smoothing mitigate label noise?
    Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar
    http://arxiv.org/abs/2003.02819v1

    • [cs.LG]Factorized Graph Representations for Semi-Supervised Learning from Sparse Data
    Krishna Kumar P., Paul Langton, Wolfgang Gatterbauer
    http://arxiv.org/abs/2003.02829v1

    • [cs.LG]Fuzzy k-Nearest Neighbors with monotonicity constraints: Moving towards the robustness of monotonic noise
    Sergio González, Salvador García, Sheng-Tun Li, Robert John, Francisco Herrera
    http://arxiv.org/abs/2003.02601v1

    • [cs.LG]Linear time dynamic programming for the exact path of optimal models selected from a finite set
    Toby Hocking, Joseph Vargovich
    http://arxiv.org/abs/2003.02808v1

    • [cs.LG]Neural Kernels Without Tangents
    Vaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil, Ludwig Schmidt, Jonathan Ragan-Kelley, Benjamin Recht
    http://arxiv.org/abs/2003.02237v2

    • [cs.LG]On the Learning Property of Logistic and Softmax Losses for Deep Neural Networks
    Xiangrui Li, Xin Li, Deng Pan, Dongxiao Zhu
    http://arxiv.org/abs/2003.02309v1

    • [cs.LG]On the performance of deep learning models for time series classification in streaming
    Pedro Lara-Benítez, Manuel Carranza-García, Francisco Martínez-Álvarez, José C. Riquelme
    http://arxiv.org/abs/2003.02544v1

    • [cs.LG]PAC-Bayesian Meta-learning with Implicit Prior
    Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro
    http://arxiv.org/abs/2003.02455v1

    • [cs.LG]Path Planning Using Probability Tensor Flows
    Francesco A. N. Palmieri, Krishna R. Pattipati, Giovanni Fioretti, Giovanni Di Gennaro, Amedeo Buonanno
    http://arxiv.org/abs/2003.02774v1

    • [cs.LG]Permute to Train: A New Dimension to Training Deep Neural Networks
    Yushi Qiu, Reiji Suda
    http://arxiv.org/abs/2003.02570v1

    • [cs.LG]Pruning Filters while Training for Efficiently Optimizing Deep Learning Networks
    Sourjya Roy, Priyadarshini Panda, Gopalakrishnan Srinivasan, Anand Raghunathan
    http://arxiv.org/abs/2003.02800v1

    • [cs.LG]PushNet: Efficient and Adaptive Neural Message Passing
    Julian Busch, Jiaxing Pi, Thomas Seidl
    http://arxiv.org/abs/2003.02228v2

    • [cs.LG]Real-time Federated Evolutionary Neural Architecture Search
    Hangyu Zhu, Yaochu Jin
    http://arxiv.org/abs/2003.02793v1

    • [cs.LG]Recognition of Smoking Gesture Using Smart Watch Technology
    Casey A. Cole, Bethany Janos, Dien Anshari, James F. Thrasher, Scott Strayer, Homayoun Valafar
    http://arxiv.org/abs/2003.02735v1

    • [cs.LG]Reduced Dilation-Erosion Perceptron for Binary Classification
    Marcos Eduardo Valle
    http://arxiv.org/abs/2003.02306v1

    • [cs.LG]SAFE: Scalable Automatic Feature Engineering Framework for Industrial Tasks
    Qitao Shi, Ya-Lin Zhang, Longfei Li, Xinxing Yang, Meng Li, Jun Zho
    http://arxiv.org/abs/2003.02556v1

    • [cs.LG]SLEIPNIR: Deterministic and Provably Accurate Feature Expansion for Gaussian Process Regression with Derivatives
    Emmanouil Angelis, Philippe Wenk, Bernhard Schölkopf, Stefan Bauer, Andreas Krause
    http://arxiv.org/abs/2003.02658v1

    • [cs.LG]Semi-supervised Learning Meets Factorization: Learning to Recommend with Chain Graph Model
    Chaochao Chen, Kevin C. Chang, Qibing Li, Xiaolin Zheng
    http://arxiv.org/abs/2003.02452v1

    • [cs.LG]Stochastic Linear Contextual Bandits with Diverse Contexts
    Weiqiang Wu, Jing Yang, Cong Shen
    http://arxiv.org/abs/2003.02681v1

    • [cs.LG]TIME: A Transparent, Interpretable, Model-Adaptive and Explainable Neural Network for Dynamic Physical Processes
    Gurpreet Singh, Soumyajit Gupta, Matt Lease, Clint N. Dawson
    http://arxiv.org/abs/2003.02426v1

    • [cs.LG]Talking-Heads Attention
    Noam Shazeer, Zhenzhong Lan, Youlong Cheng, Nan Ding, Le Hou
    http://arxiv.org/abs/2003.02436v1

    • [cs.LG]What went wrong and when? Instance-wise Feature Importance for Time-series Models
    Sana Tonekaboni, Shalmali Joshi, David Duvenaud, Anna Goldenberg
    http://arxiv.org/abs/2003.02821v1

    • [cs.LG]mmFall: Fall Detection using 4D MmWave Radar and Variational Recurrent Autoencoder
    Feng Jin, Arindam Sengupta, Siyang Cao
    http://arxiv.org/abs/2003.02386v1

    • [cs.NE]Adaptive Verifiability-Driven Strategy for Evolutionary Approximation of Arithmetic Circuits
    Milan Ceska, Jiri Matyas, Vojtech Mrazek, Lukas Sekanina, Zdenek Vasicek, Tomas Vojnar
    http://arxiv.org/abs/2003.02491v1

    • [cs.NE]Event-Based Angular Velocity Regression with Spiking Networks
    Mathias Gehrig, Sumit Bam Shrestha, Daniel Mouritzen, Davide Scaramuzza
    http://arxiv.org/abs/2003.02790v1

    • [cs.NE]Plasticity-Enhanced Domain-Wall MTJ Neural Networks for Energy-Efficient Online Learning
    Christopher H. Bennett, T. Patrick Xiao, Can Cui, Naimul Hassan, Otitoaleke G. Akinola, Jean Anne C. Incorvia, Alvaro Velasquez, Joseph S. Friedman, Matthew J. Marinella
    http://arxiv.org/abs/2003.02357v1

    • [cs.NE]QED: using Quality-Environment-Diversity to evolve resilient robot swarms
    David M. Bossens, Danesh Tarapore
    http://arxiv.org/abs/2003.02341v1

    • [cs.NI]Optimal Sampling Cost in Wireless Networks with Age of Information Constraints
    Emmanouil Fountoulakis, Nikolaos Pappas, Marian Codreanu, Anthony Ephremides
    http://arxiv.org/abs/2003.02512v1

    • [cs.RO]A Geometric Perspective on Visual Imitation Learning
    Jun Jin, Laura Petrich, Masood Dehghan, Martin Jagersand
    http://arxiv.org/abs/2003.02768v1

    • [cs.RO]Autonomous Driving at Intersections: A Critical-Turning-Point Approach for Left Turns
    K. Shu, H. Yu, X. Chen, L. Chen, Q. Wang, L. Li, D. Cao
    http://arxiv.org/abs/2003.02409v1

    • [cs.RO]Efficient Uncertainty-aware Decision-making for Automated Driving Using Guided Branching
    Lu Zhang, Wenchao Ding, Jing Chen, Shaojie Shen
    http://arxiv.org/abs/2003.02746v1

    • [cs.RO]GOMP: Grasp-Optimized Motion Planning for Bin Picking
    Jeffrey Ichnowski, Michael Danielczuk, Jingyi Xu, Vishal Satish, Ken Goldberg
    http://arxiv.org/abs/2003.02401v1

    • [cs.RO]Learning the sense of touch in simulation: a sim-to-real strategy for vision-based tactile sensing
    Carmelo Sferrazza, Thomas Bi, Raffaello D’Andrea
    http://arxiv.org/abs/2003.02640v1

    • [cs.RO]Learning,Generating and Adapting Wave Gestures for Expressive Human-Robot Interaction
    Mihalis Panteris, Simon Manschitz, Sylvain Calinon
    http://arxiv.org/abs/2003.02348v1

    • [cs.RO]Learning-based distributionally robust motion control with Gaussian processes
    Astghik Hakobyan, Insoon Yang
    http://arxiv.org/abs/2003.02532v1

    • [cs.RO]PointLoc: Deep Pose Regressor for LiDAR Point Cloud Localization
    Wei Wang, Bing Wang, Peijun Zhao, Changhao Chen, Ronald Clark, Bo Yang, Andrew Markham, Niki Trigoni
    http://arxiv.org/abs/2003.02392v1

    • [cs.RO]Safe Planning for Self-Driving Via Adaptive Constrained ILQR
    Yanjun Pan, Qin Lin, Het Shah, John M. Dolan
    http://arxiv.org/abs/2003.02757v1

    • [cs.RO]Team O2AS at the World Robot Summit 2018: An Approach to Robotic Kitting and Assembly Tasks using General Purpose Grippers and Tools
    Felix von Drigalski, Chisato Nakashima, Yoshiya Shibata, Yoshinori Konishi, Joshua C. Triyonoputro, Kaidi Nie, Damien Petit, Toshio Ueshiba, Ryuichi Takase, Yukiyasu Domae, Taku Yoshioka, Yoshihisa Ijiri, Ixchel G. Ramirez-Alpizar, Weiwei Wan, Kensuke Harada
    http://arxiv.org/abs/2003.02427v1

    • [cs.RO]Touch the Wind: Simultaneous Airflow, Drag and Interaction Sensing on a Multirotor
    Andrea Tagliabue, Aleix Paris, Suhan Kim, Regan Kubicek, Sarah Bergbreiter, Jonathan P. How
    http://arxiv.org/abs/2003.02305v1

    • [cs.RO]UAV Coverage Path Planning under Varying Power Constraints using Deep Reinforcement Learning
    Mirco Theile, Harald Bayerlein, Richard Nai, David Gesbert, Marco Caccamo
    http://arxiv.org/abs/2003.02609v1

    • [cs.SI]AGL: a Scalable System for Industrial-purpose Graph Machine Learning
    Dalong Zhang, Xin Huang, Ziqi Liu, Zhiyang Hu, Xianzheng Song, Zhibang Ge, Zhiqiang Zhang, Lin Wang, Jun Zhou, Yuan Qi
    http://arxiv.org/abs/2003.02454v1

    • [cs.SI]EPINE: Enhanced Proximity Information Network Embedding
    Luoyi Zhang, Ming Xu
    http://arxiv.org/abs/2003.02689v1

    • [cs.SI]Fragility of spectral clustering for networks with an overlapping structure
    Chihiro Noguchi, Tatsuro Kawamoto
    http://arxiv.org/abs/2003.02463v1

    • [cs.SI]Modeling the Popularity of Twitter Hashtags with Master Equations
    Oscar Fontanelli, Ricardo Mansilla
    http://arxiv.org/abs/2003.02672v1

    • [cs.SI]Properties of Erdős-Rényi Graphs
    Hang Chen, Vahan Hurovan, Stephen Kobourov
    http://arxiv.org/abs/2003.02673v1

    • [cs.SI]The Multi-granularity in Graph Revealed by a Generalized Leading Tree
    Shun Fu, Ji Xu
    http://arxiv.org/abs/2003.02708v1

    • [econ.EM]Backward CUSUM for Testing and Monitoring Structural Change
    Sven Otto, Jörg Breitung
    http://arxiv.org/abs/2003.02682v1

    • [eess.AS]Auto-Tuning Spectral Clustering for Speaker Diarization Using Normalized Maximum Eigengap
    Tae Jin Park, Kyu J. Han, Manoj Kumar, Shrikanth Narayanan
    http://arxiv.org/abs/2003.02405v1

    • [eess.AS]Real-time, Universal, and Robust Adversarial Attacks Against Speaker Recognition Systems
    Yi Xie, Cong Shi, Zhuohang Li, Jian Liu, Yingying Chen, Bo Yuan
    http://arxiv.org/abs/2003.02301v1

    • [eess.IV]Harnessing Multi-View Perspective of Light Fields for Low-Light Imaging
    Mohit Lamba, Kranthi Kumar, Kaushik Mitra
    http://arxiv.org/abs/2003.02438v1

    • [eess.IV]Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised Knee Osteoarthritis Severity Grading from Plain Radiographs
    Huy Hoang Nguyen, Simo Saarakkala, Matthew Blaschko, Aleksei Tiulpin
    http://arxiv.org/abs/2003.01944v2

    • [eess.SP]Approximate Message Passing with a Colored Aliasing Model for Variable Density Fourier Sampled Images
    Charles Millard, Aaron T Hess, Boris Mailhé, Jared Tanner
    http://arxiv.org/abs/2003.02701v1

    • [eess.SP]Approximating the Hotelling Observer with Autoencoder-Learned Efficient Channels for Binary Signal Detection Tasks
    Jason L. Granstedt, Weimin Zhou, Mark A. Anastasio
    http://arxiv.org/abs/2003.02321v1

    • [math.NA]Methods to Recover Unknown Processes in Partial Differential Equations Using Data
    Zhen Chen, Kailiang Wu, Dongbin Xiu
    http://arxiv.org/abs/2003.02387v1

    • [math.ST]A comparison of maximum likelihood and absolute moments for the estimation of Hurst exponents in a stationary framework
    Matthieu Garcin
    http://arxiv.org/abs/2003.02566v1

    • [math.ST]A strong law of large numbers for simultaneously testing parameters of Lancaster bivariate distributions
    Xiongzhi Chen
    http://arxiv.org/abs/2003.02805v1

    • [math.ST]Cumulant-free closed-form formulas for some common (dis)similarities between densities of an exponential family
    Frank Nielsen, Richard Nock
    http://arxiv.org/abs/2003.02469v1

    • [math.ST]II. High Dimensional Estimation under Weak Moment Assumptions: Structured Recovery and Matrix Estimation
    Xiaohan Wei
    http://arxiv.org/abs/2003.02468v1

    • [math.ST]Logistic regression with total variation regularization
    Sara van de Geer
    http://arxiv.org/abs/2003.02678v1

    • [physics.soc-ph]Phase transitions in a decentralized graph-based approach to human language
    Javier Vera, Felipe Urbina, Wenceslao Palma
    http://arxiv.org/abs/2003.02639v1

    • [q-bio.QM]Variation in correlation between prognosis and histologic feature based on biopsy selection
    Emily Diller, Jason Parker
    http://arxiv.org/abs/2003.02340v1

    • [q-fin.CP]Non-stationary neural network for stock return prediction
    Steven Y. K. Wong, Jennifer Chan, Lamiae Azizi, Richard Y. D. Xu
    http://arxiv.org/abs/2003.02515v1

    • [q-fin.RM]Application of Deep Neural Networks to assess corporate Credit Rating
    Parisa Golbayani, Dan Wang, Ionut Florescu
    http://arxiv.org/abs/2003.02334v1

    • [q-fin.TR]Robust Market Making via Adversarial Reinforcement Learning
    Thomas Spooner, Rahul Savani
    http://arxiv.org/abs/2003.01820v1

    • [quant-ph]QSW_MPI: a framework for parallel simulation of quantum stochastic walks
    Edric Matwiejew, Jingbo Wang
    http://arxiv.org/abs/2003.02450v1

    • [stat.AP]Bayesian A/B Testing for Business Decisions
    Shafi Kamalbasha, Manuel J. A. Eugster
    http://arxiv.org/abs/2003.02769v1

    • [stat.AP]Individual Claims Forecasting with Bayesian Mixture Density Networks
    Kevin Kuo
    http://arxiv.org/abs/2003.02453v1

    • [stat.AP]Multi-Output Gaussian Processes for Multi-Population Longevity Modeling
    Nhan Huynh, Mike Ludkovski
    http://arxiv.org/abs/2003.02443v1

    • [stat.ME]A Multi-Way Correlation Coefficient
    Benjamin M. Taylor
    http://arxiv.org/abs/2003.02561v1

    • [stat.ME]A new approach in model selection for ordinal target variables
    Elena Ballante, Pierpaolo Uberti, Silvia Figini
    http://arxiv.org/abs/2003.02761v1

    • [stat.ME]Exploiting disagreement between high-dimensional variable selectors for uncertainty visualization
    Christine Yuen, Piotr Fryzlewicz
    http://arxiv.org/abs/2003.02791v1

    • [stat.ME]Graphical modelling and partial characteristics for multitype and multivariate-marked spatio-temporal point processes
    Matthias Eckardt, Jonatan A. González, Jorge Mateu
    http://arxiv.org/abs/2003.02476v1

    • [stat.ME]Optimally adaptive Bayesian spectral density estimation
    Nick James, Max Menzies
    http://arxiv.org/abs/2003.02367v1

    • [stat.ME]Probabilistic
    80d
    performance estimators for computational chemistry methods: Systematic Improvement Probability and Ranking Probability Matrix. I. Theory
    Pascal Pernot, Andreas Savin
    http://arxiv.org/abs/2003.00987v3

    • [stat.ME]Regularized Variational Data Assimilation for Bias Treatment using the Wasserstein Metric
    Sagar K. Tamang, Ardeshir Ebtehaj, Dongmian Zou, Gilad Lerman
    http://arxiv.org/abs/2003.02421v1

    • [stat.ME]Robust Identification of Gene-Environment Interactions under High-Dimensional Accelerated Failure Time Models
    Qingzhao Zhang, Hao Chai, Shuangge Ma
    http://arxiv.org/abs/2003.02580v1

    • [stat.ME]Spherical Principal Curves
    Jang-Hyun Kim, Jongmin Lee, Hee-Seok Oh
    http://arxiv.org/abs/2003.02578v1

    • [stat.ML]Bayesian System ID: Optimal management of parameter, model, and measurement uncertainty
    Nicholas Galioto, Alex Gorodetsky
    http://arxiv.org/abs/2003.02359v1

    • [stat.ML]Knot Selection in Sparse Gaussian Processes with a Variational Objective
    Nathaniel Garton, Jarad Niemi, Alicia Carriquiry
    http://arxiv.org/abs/2003.02729v1

    • [stat.ML]Nonlinear Time Series Classification Using Bispectrum-based Deep Convolutional Neural Networks
    Paul A. Parker, Scott H. Holan, Nalini Ravishanker
    http://arxiv.org/abs/2003.02353v1

    • [stat.ML]On the Convergence of Adam and Adagrad
    Alexandre Défossez, Léon Bottou, Francis Bach, Nicolas Usunier
    http://arxiv.org/abs/2003.02395v1