cs.AI - 人工智能

    cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DC - 分布式、并行与集群计算 cs.DL - 数字图书馆 cs.DM - 离散数学 cs.HC - 人机接口 cs.IT - 信息论 cs.LG - 自动学习 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.RO - 机器人学 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.GN - 一般经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SY - 系统和控制 math.NA - 数值分析 math.ST - 统计理论 physics.med-ph - 医学物理学 physics.soc-ph - 物理学与社会 q-bio.PE - 人口与发展 q-bio.QM - 定量方法 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]Modeling Rare Interactions in Time Series Data Through Qualitative Change: Application to Outcome Prediction in Intensive Care Units
    • [cs.AI]Value Driven Representation for Human-in-the-Loop Reinforcement Learning
    • [cs.CL]A Set of Recommendations for Assessing Human-Machine Parity in Language Translation
    • [cs.CL]Aligned Cross Entropy for Non-Autoregressive Machine Translation
    • [cs.CL]Analyzing autoencoder-based acoustic word embeddings
    • [cs.CL]Directions in Abusive Language Training Data: Garbage In, Garbage Out
    • [cs.CL]Keyphrase Rubric Relationship Classification in Complex Assignments
    • [cs.CL]Learning synchronous context-free grammars with multiple specialised non-terminals for hierarchical phrase-based translation
    • [cs.CL]MZET: Memory Augmented Zero-Shot Fine-grained Named Entity Typing
    • [cs.CL]R3: A Reading Comprehension Benchmark Requiring Reasoning Processes
    • [cs.CL]XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation
    • [cs.CR]Efficient UAV Physical Layer Security based on Deep Learning and Artificial Noise
    • [cs.CR]Preserving Statistical Privacy in Distributed Optimization
    • [cs.CV]A Fast Fully Octave Convolutional Neural Network for Document Image Segmentation
    • [cs.CV]BosphorusSign22k Sign Language Recognition Dataset
    • [cs.CV]Cell Segmentation and Tracking using Distance Transform Predictions and Movement Estimation with Graph-Based Matching
    • [cs.CV]Context Prior for Scene Segmentation
    • [cs.CV]Context-Aware Multi-Task Learning for Traffic Scene Recognition in Autonomous Vehicles
    • [cs.CV]DFNet: Discriminative feature extraction and integration network for salient object detection
    • [cs.CV]Deep Learning based detection of Acute Aortic Syndrome in contrast CT images
    • [cs.CV]Deep Learning for Image Search and Retrieval in Large Remote Sensing Archives
    • [cs.CV]Deep White-Balance Editing
    • [cs.CV]Demographic Bias: A Challenge for Fingervein Recognition Systems?
    • [cs.CV]Disassembling Object Representations without Labels
    • [cs.CV]Effective Fusion of Deep Multitasking Representations for Robust Visual Tracking
    • [cs.CV]Exploring the ability of CNNs to generalise to previously unseen scales over wide scale ranges
    • [cs.CV]FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret
    • [cs.CV]From Paris to Berlin: Discovering Fashion Style Influences Around the World
    • [cs.CV]Generative PointNet: Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification
    • [cs.CV]Gradient Centralization: A New Optimization Technique for Deep Neural Networks
    • [cs.CV]Guided Variational Autoencoder for Disentanglement Learning
    • [cs.CV]HandVoxNet: Deep Voxel-Based Network for 3D Hand Shape and Pose Estimation from a Single Depth Map
    • [cs.CV]Interpreting Medical Image Classifiers by Optimization Based Counterfactual Impact Analysis
    • [cs.CV]Intrinsic Point Cloud Interpolation via Dual Latent Space Navigation
    • [cs.CV]Knowing What, Where and When to Look: Efficient Video Action Modeling with Attention
    • [cs.CV]Learning Pose-invariant 3D Object Reconstruction from Single-view Images
    • [cs.CV]LiDAR-based Online 3D Video Object Detection with Graph-based Message Passing and Spatiotemporal Transformer Attention
    • [cs.CV]Near-chip Dynamic Vision Filtering for Low-Bandwidth Pedestrian Detection
    • [cs.CV]Novel View Synthesis of Dynamic Scenes with Globally Coherent Depths from a Monocular Camera
    • [cs.CV]PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation
    • [cs.CV]Quantifying Data Augmentation for LiDAR based 3D Object Detection
    • [cs.CV]RANSAC-Flow: generic two-stage image alignment
    • [cs.CV]S2DNet: Learning Accurate Correspondences for Sparse-to-Dense Feature Matching
    • [cs.CV]Self-Paced Deep Regression Forests with Consideration on Underrepresented Samples
    • [cs.CV]Sequential Learning for Domain Generalization
    • [cs.CV]Sparse Concept Coded Tetrolet Transform for Unconstrained Odia Character Recognition
    • [cs.CV]TEA: Temporal Excitation and Aggregation for Action Recognition
    • [cs.CV]Towards Better Generalization: Joint Depth-Pose Learning without PoseNet
    • [cs.CV]Two-Stream AMTnet for Action Detection
    • [cs.CY]Application of Intelligent Multi Agent Based Systems For E-Healthcare Security
    • [cs.CY]Mobile social media usage and academic performance
    • [cs.CY]Portable Health Screening Device of Respiratory Infections
    • [cs.DC]Assessing Impact of Data Partitioning for Approximate Memory in C/C++ Code
    • [cs.DC]High Bandwidth Memory on FPGAs: A Data Analytics Perspective
    • [cs.DC]Localized Mobile Agent Framework for data processing on Internet of Things
    • [cs.DC]On the Search Efficiency of Parallel Lévy Walks on $\mathbf{Z}^2$
    • [cs.DC]Trustless parallel local search for effective distributed algorithm discovery
    • [cs.DC]User-Space Emulation Framework for Domain-Specific SoC Design
    • [cs.DL]Mapping Three Decades of Intellectual Change in Academia
    • [cs.DM]A Note on Double Pooling Tests
    • [cs.HC]Towards Designer Modeling through Design Style Clustering
    • [cs.IT]A Quadratic Form Approach to Construction A of Lattices over Cyclic Algebras
    • [cs.IT]Binary Golay Spreading Sequences and Reed-Muller Codes for Uplink Grant-Free NOMA
    • [cs.IT]Downlink Extrapolation for FDD Multiple Antenna Systems Through Neural Network Using Extracted Uplink Path Gains
    • [cs.IT]Error Detection and Correction in Communication Networks
    • [cs.IT]On Delay-limited Average Rate of HARQ-based Predictor Antenna Systems
    • [cs.IT]Power Allocation in HARQ-based Predictor Antenna Systems
    • [cs.IT]The Courtade-Kumar Most Informative Boolean Function Conjecture and a Symmetrized Li-Médard Conjecture are Equivalent
    • [cs.LG]A Deep Ensemble Multi-Agent Reinforcement Learning Approach for Air Traffic Control
    • [cs.LG]Attribute2vec: Deep Network Embedding Through Multi-Filtering GCN
    • [cs.LG]Epitomic Variational Graph Autoencoder
    • [cs.LG]From Local SGD to Local Fixed Point Methods for Federated Learning
    • [cs.LG]Hawkes Process Multi-armed Bandits for Disaster Search and Rescue
    • [cs.LG]Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip
    • [cs.LG]Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning
    • [cs.LG]M2pht: Mixed Models with Preferences and Hybrid Transitions for Next-Basket Recommendation
    • [cs.LG]Multi-agent Reinforcement Learning for Networked System Control
    • [cs.LG]Neural Architecture Generator Optimization
    • [cs.LG]On-Device Transfer Learning for Personalising Psychological Stress Modelling using a Convolutional Neural Network
    • [cs.LG]Orthogonal Inductive Matrix Completion
    • [cs.LG]Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
    • [cs.LG]Unpack Local Model Interpretation for GBDT
    • [cs.LG]Weighted Random Search for Hyperparameter Optimization
    • [cs.MA]Distributed Hypothesis Testing and Social Learning in Finite Time with a Finite Amount of Communication
    • [cs.NE]Benchmarking Deep Spiking Neural Networks on Neuromorphic Hardware
    • [cs.NE]Does Comma Selection Help To Cope With Local Optima
    • [cs.NE]The data-driven physical-based equations discovery using evolutionary approach
    • [cs.NE]Under the Hood of Neural Networks: Characterizing Learned Representations by Functional Neuron Populations and Network Ablations
    • [cs.NI]On the Path to High Precise IP Geolocation: A Self-Optimizing Model
    • [cs.NI]RACE: Reinforced Cooperative Autonomous Vehicle Collision AvoidancE
    • [cs.RO]Characterization of Multiple 3D LiDARs for Localization and Mapping using Normal Distributions Transform
    • [cs.RO]Extraction and Assessment of Naturalistic Human Driving Trajectories from Infrastructure Camera and Radar Sensors
    • [cs.RO]Series Elastic Force Control for Soft Robotic Fluid Actuators
    • [cs.RO]VGPN: Voice-Guided Pointing Robot Navigation for Humans
    • [cs.SE]Using Large-Scale Anomaly Detection on Code to Improve Kotlin Compiler
    • [cs.SI]How mobility patterns drive disease spread: A case study using public transit passenger card travel data
    • [cs.SI]Identifying highly influential travellers for spreading disease on a public transport system
    • [cs.SI]Motif-Based Spectral Clustering of Weighted Directed Networks
    • [econ.GN]Predicting Labor Shortages from Labor Demand and LaborSupply Data: A Machine Learning Approach
    • [eess.AS]AI4COVID-19: AI Enabled Preliminary Diagnosis for COVID-19 from Cough Samples via an App
    • [eess.AS]Neural i-vectors
    • [eess.AS]Towards Relevance and Sequence Modeling in Language Recognition
    • [eess.IV]Cell Segmentation by Combining Marker-Controlled Watershed and Deep Learning
    • [eess.IV]Crossover-Net: Leveraging the Vertical-Horizontal Crossover Relation for Robust Segmentation
    • [eess.IV]Deep Transfer Learning for Texture Classification in Colorectal Cancer Histology
    • [eess.IV]Detection of Perineural Invasion in Prostate Needle Biopsies with Deep Neural Networks
    • [eess.IV]Quantification of Tomographic Patterns associated with COVID-19 from Chest CT
    • [eess.IV]Retinopathy of Prematurity Stage Diagnosis Using Object Segmentation and Convolutional Neural Networks
    • [eess.IV]STAN-CT: Standardizing CT Image using Generative Adversarial Network
    • [eess.SY]Data-Driven Transient Stability Boundary Generation for Online Security Monitoring
    • [eess.SY]Event-Triggered Distributed Inference
    • [eess.SY]FeederGAN: Synthetic Feeder Generation via Deep Graph Adversarial Nets
    • [eess.SY]Reinforcement Learning for Mixed-Integer Problems Based on MPC
    • [math.NA]Resampling with neural networks for stochastic parameterization in multiscale systems
    • [math.ST]Relaxing the Gaussian assumption in Shrinkage and SURE in high dimension
    • [physics.med-ph]Predicting the risk of pancreatic cancer with a CT-based ensemble AI algorithm
    • [physics.soc-ph]Bridging the gap between graphs and networks
    • [physics.soc-ph]Generating Similarity Map in COVID-19 Transmission Dynamics with Topological Autoencoder
    • [physics.soc-ph]Layer entanglement in multiplex, temporal multiplex, and coupled multilayer networks
    • [physics.soc-ph]The Wigner’s Semicircle Law of Weighted Random Networks
    • [q-bio.PE]Analysis of the COVID-19 pandemic by SIR model and machine learning technics for forecasting
    • [q-bio.QM]Predicting rice blast disease: machine learning versus process based models
    • [stat.AP]COVID-19: Should We Test Everyone?
    • [stat.AP]Estimation of daily streamflow from multiple donor catchments with Graphical Lasso
    • [stat.CO]Hierarchical Bayesian Nearest Neighbor Co-Kriging Gaussian Process Models; An Application to Intersatellite Calibration
    • [stat.ME]A sequential design for extreme quantiles estimation under binary sampling
    • [stat.ME]Composite mixture of log-linear models for categorical data
    • [stat.ME]General Identification of Dynamic Treatment Regimes Under Interference
    • [stat.ME]Generalized inverse-Gaussian frailty models with application to TARGET neuroblastoma data
    • [stat.ME]Penalized composite likelihood for colored graphical Gaussian models
    • [stat.ME]Robust Parametric Inference for Finite Markov Chains
    • [stat.ME]Uniform Inference in High-Dimensional Generalized Additive Models
    • [stat.ML]A rigorous method to compare interpretability of rule-based algorithms
    • [stat.ML]Distributed Primal-Dual Optimization for Online Multi-Task Learning
    • [stat.ML]Faster Gaussian Processes via Deep Embeddings
    • [stat.ML]IVFS: Simple and Efficient Feature Selection for High Dimensional Topology Preservation
    • [stat.ML]Neural Conditional Event Time Models
    • [stat.ML]Predicting the outputs of finite networks trained with noisy gradients
    • [stat.ML]TRAMP: Compositional Inference with TRee Approximate Message Passing

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

    • [cs.AI]Modeling Rare Interactions in Time Series Data Through Qualitative Change: Application to Outcome Prediction in Intensive Care Units
    Zina Ibrahim, Honghan Wu, Richard Dobson
    http://arxiv.org/abs/2004.01431v1

    • [cs.AI]Value Driven Representation for Human-in-the-Loop Reinforcement Learning
    Ramtin Keramati, Emma Brunskill
    http://arxiv.org/abs/2004.01223v1

    • [cs.CL]A Set of Recommendations for Assessing Human-Machine Parity in Language Translation
    Samuel Läubli, Sheila Castilho, Graham Neubig, Rico Sennrich, Qinlan Shen, Antonio Toral
    http://arxiv.org/abs/2004.01694v1

    • [cs.CL]Aligned Cross Entropy for Non-Autoregressive Machine Translation
    Marjan Ghazvininejad, Vladimir Karpukhin, Luke Zettlemoyer, Omer Levy
    http://arxiv.org/abs/2004.01655v1

    • [cs.CL]Analyzing autoencoder-based acoustic word embeddings
    Yevgen Matusevych, Herman Kamper, Sharon Goldwater
    http://arxiv.org/abs/2004.01647v1

    • [cs.CL]Directions in Abusive Language Training Data: Garbage In, Garbage Out
    Bertie Vidgen, Leon Derczynski
    http://arxiv.org/abs/2004.01670v1

    • [cs.CL]Keyphrase Rubric Relationship Classification in Complex Assignments
    Manikandan Ravikiran
    http://arxiv.org/abs/2004.01549v1

    • [cs.CL]Learning synchronous context-free grammars with multiple specialised non-terminals for hierarchical phrase-based translation
    Felipe Sánchez-Martínez, Juan Antonio Pérez-Ortiz, Rafael C. Carrasco
    http://arxiv.org/abs/2004.01422v1

    • [cs.CL]MZET: Memory Augmented Zero-Shot Fine-grained Named Entity Typing
    Tao Zhang, Congying Xia, Chun-Ta Lu, Philip Yu
    http://arxiv.org/abs/2004.01267v1

    • [cs.CL]R3: A Reading Comprehension Benchmark Requiring Reasoning Processes
    Ran Wang, Kun Tao, Dingjie Song, Zhilong Zhang, Xiao Ma, Xi’ao Su, Xinyu Dai
    http://arxiv.org/abs/2004.01251v1

    • [cs.CL]XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation
    Yaobo Liang, Nan Duan, Yeyun Gong, Ning Wu, Fenfei Guo, Weizhen Qi, Ming Gong, Linjun Shou, Daxin Jiang, Guihong Cao, Xiaodong Fan, Bruce Zhang, Rahul Agrawal, Edward Cui, Sining Wei, Taroon Bharti, Jiun-Hung Chen, Winnie Wu, Shuguang Liu, Fan Yang, Ming Zhou
    http://arxiv.org/abs/2004.01401v1

    • [cs.CR]Efficient UAV Physical Layer Security based on Deep Learning and Artificial Noise
    Behrooz Khadem, Salar Mohebalizadeh
    http://arxiv.org/abs/2004.01343v1

    • [cs.CR]Preserving Statistical Privacy in Distributed Optimization
    Nirupam Gupta, Shripad Gade, Nikhil Chopra, Nitin H. Vaidya
    http://arxiv.org/abs/2004.01312v1

    • [cs.CV]A Fast Fully Octave Convolutional Neural Network for Document Image Segmentation
    Ricardo Batista das Neves Junior, Luiz Felipe Verçosa, David Macêdo, Byron Leite Dantas Bezerra, Cleber Zanchettin
    http://arxiv.org/abs/2004.01317v1

    • [cs.CV]BosphorusSign22k Sign Language Recognition Dataset
    Oğulcan Özdemir, Ahmet Alp Kındıroğlu, Necati Cihan Camgöz, Lale Akarun
    http://arxiv.org/abs/2004.01283v1

    • [cs.CV]Cell Segmentation and Tracking using Distance Transform Predictions and Movement Estimation with Graph-Based Matching
    Tim Scherr, Katharina Löffler, Moritz Böhland, Ralf Mikut
    http://arxiv.org/abs/2004.01486v1

    • [cs.CV]Context Prior for Scene Segmentation
    Changqian Yu, Jingbo Wang, Changxin Gao, Gang Yu, Chunhua Shen, Nong Sang
    http://arxiv.org/abs/2004.01547v1

    • [cs.CV]Context-Aware Multi-Task Learning for Traffic Scene Recognition in Autonomous Vehicles
    Younkwan Lee, Jihyo Jeon, Jongmin Yu, Moongu Jeon
    http://arxiv.org/abs/2004.01351v1

    • [cs.CV]DFNet: Discriminative feature extraction and integration network for salient object detection
    Mehrdad Noori, Sina Mohammadi, Sina Ghofrani Majelan, Ali Bahri, Mohammad Havaei
    http://arxiv.org/abs/2004.01573v1

    • [cs.CV]Deep Learning based detection of Acute Aortic Syndrome in contrast CT images
    Manikanta Srikar Yellapragada, Yiting Xie, Benedikt Graf, David Richmond, Arun Krishnan, Arkadiusz Sitek
    http://arxiv.org/abs/2004.01648v1

    • [cs.CV]Deep Learning for Image Search and Retrieval in Large Remote Sensing Archives
    Gencer Sumbul, Jian Kang, Begüm Demir
    http://arxiv.org/abs/2004.01613v1

    • [cs.CV]Deep White-Balance Editing
    Mahmoud Afifi, Michael S. Brown
    http://arxiv.org/abs/2004.01354v1

    • [cs.CV]Demographic Bias: A Challenge for Fingervein Recognition Systems?
    P. Drozdowski, B. Prommegger, G. Wimmer, R. Schraml, C. Rathgeb, A. Uhl, C. Busch
    http://arxiv.org/abs/2004.01418v1

    • [cs.CV]Disassembling Object Representations without Labels
    Zunlei Feng, Xinchao Wang, Yongming He, Yike Yuan, Xin Gao, Mingli Song
    http://arxiv.org/abs/2004.01426v1

    • [cs.CV]Effective Fusion of Deep Multitasking Representations for Robust Visual Tracking
    Seyed Mojtaba Marvasti-Zadeh, Hossein Ghanei-Yakhdan, Shohreh Kasaei, Kamal Nasrollahi, Thomas B. Moeslund
    http://arxiv.org/abs/2004.01382v1

    • [cs.CV]Exploring the ability of CNNs to generalise to previously unseen scales over wide scale ranges
    Ylva Jansson, Tony Lindeberg
    http://arxiv.org/abs/2004.01536v1

    • [cs.CV]FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret
    Vishnu Suresh Lokhande, Aditya Kumar Akash, Sathya N. Ravi, Vikas Singh
    http://arxiv.org/abs/2004.01355v1

    • [cs.CV]From Paris to Berlin: Discovering Fashion Style Influences Around the World
    Ziad Al-Halah, Kristen Grauman
    http://arxiv.org/abs/2004.01316v1

    • [cs.CV]Generative PointNet: Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification
    Jianwen Xie, Yifei Xu, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu
    http://arxiv.org/abs/2004.01301v1

    • [cs.CV]Gradient Centralization: A New Optimization Technique for Deep Neural Networks
    Hongwei Yong, Jianqiang Huang, Xiansheng Hua, Lei Zhang
    http://arxiv.org/abs/2004.01461v1

    • [cs.CV]Guided Variational Autoencoder for Disentanglement Learning
    Zheng Ding, Yifan Xu, Weijian Xu, Gaurav Parmar, Yang Yang, Max Welling, Zhuowen Tu
    http://arxiv.org/abs/2004.01255v1

    • [cs.CV]HandVoxNet: Deep Voxel-Based Network for 3D Hand Shape and Pose Estimation from a Single Depth Map
    Jameel Malik, Ibrahim Abdelaziz, Ahmed Elhayek, Soshi Shimada, Sk Aziz Ali, Vladislav Golyanik, Christian Theobalt, Didier Stricker
    http://arxiv.org/abs/2004.01588v1

    • [cs.CV]Interpreting Medical Image Classifiers by Optimization Based Counterfactual Impact Analysis
    David Major, Dimitrios Lenis, Maria Wimmer, Gert Sluiter, Astrid Berg, Katja Bühler
    http://arxiv.org/abs/2004.01610v1

    • [cs.CV]Intrinsic Point Cloud Interpolation via Dual Latent Space Navigation
    Marie-Julie Rakotosaona, Maks Ovsjanikov
    http://arxiv.org/abs/2004.01661v1

    • [cs.CV]Knowing What, Where and When to Look: Efficient Video Action Modeling with Attention
    Juan-Manuel Perez-Rua, Brais Martinez, Xiatian Zhu, Antoine Toisoul, Victor Escorcia, Tao Xiang
    http://arxiv.org/abs/2004.01278v1

    • [cs.CV]Learning Pose-invariant 3D Object Reconstruction from Single-view Images
    Bo Peng, Wei Wang, Jing Dong, Tieniu Tan
    http://arxiv.org/abs/2004.01347v1

    • [cs.CV]LiDAR-based Online 3D Video Object Detection with Graph-based Message Passing and Spatiotemporal Transformer Attention
    Junbo Yin, Jianbing Shen, Chenye Guan, Dingfu Zhou, Ruigang Yang
    http://arxiv.org/abs/2004.01389v1

    • [cs.CV]Near-chip Dynamic Vision Filtering for Low-Bandwidth Pedestrian Detection
    Anthony Bisulco, Fernando Cladera Ojeda, Volkan Isler, Daniel D. Lee
    http://arxiv.org/abs/2004.01689v1

    • [cs.CV]Novel View Synthesis of Dynamic Scenes with Globally Coherent Depths from a Monocular Camera
    Jae Shin Yoon, Kihwan Kim, Orazio Gallo, Hyun Soo Park, Jan Kautz
    http://arxiv.org/abs/2004.01294v1

    • [cs.CV]PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation
    Li Jiang, Hengshuang Zhao, Shaoshuai Shi, Shu Liu, Chi-Wing Fu, Jiaya Jia
    http://arxiv.org/abs/2004.01658v1

    • [cs.CV]Quantifying Data Augmentation for LiDAR based 3D Object Detection
    Martin Hahner, Dengxin Dai, Alexander Liniger, Luc Van Gool
    http://arxiv.org/abs/2004.01643v1

    • [cs.CV]RANSAC-Flow: generic two-stage image alignment
    Xi Shen, François Darmon, Alexei A. Efros, Mathieu Aubry
    http://arxiv.org/abs/2004.01526v1

    • [cs.CV]S2DNet: Learning Accurate Correspondences for Sparse-to-Dense Feature Matching
    Hugo Germain, Guillaume Bourmaud, Vincent Lepetit
    http://arxiv.org/abs/2004.01673v1

    • [cs.CV]Self-Paced Deep Regression Forests with Consideration on Underrepresented Samples
    Lili Pan, Shijie Ai, Yazhou Ren, Zenglin Xu
    http://arxiv.org/abs/2004.01459v1

    • [cs.CV]Sequential Learning for Domain Generalization
    Da Li, Yongxin Yang, Yi-Zhe Song, Timothy Hospedales
    http://arxiv.org/abs/2004.01377v1

    • [cs.CV]Sparse Concept Coded Tetrolet Transform for Unconstrained Odia Character Recognition
    Kalyan S Dash, N B Puhan, G Panda
    http://arxiv.org/abs/2004.01551v1

    • [cs.CV]TEA: Temporal Excitation and Aggregation for Action Recognition
    Yan Li, Bin Ji, Xintian Shi, Jianguo Zhang, Bin Kang, Limin Wang
    http://arxiv.org/abs/2004.01398v1

    • [cs.CV]Towards Better Generalization: Joint Depth-Pose Learning without PoseNet
    Wang Zhao, Shaohui Liu, Yezhi Shu, Yong-Jin Liu
    http://arxiv.org/abs/2004.01314v1

    • [cs.CV]Two-Stream AMTnet for Action Detection
    Suman Saha, Gurkirt Singh, Fabio Cuzzolin
    http://arxiv.org/abs/2004.01494v1

    • [cs.CY]Application of Intelligent Multi Agent Based Systems For E-Healthcare Security
    Faizal Khan, Omar Reyad
    http://arxiv.org/abs/2004.01256v1

    • [cs.CY]Mobile social media usage and academic performance
    Fausto Giunchiglia, Mattia Zeni, Elisa Gobbi, Enrico Bignotti, Ivano Bison
    http://arxiv.org/abs/2004.01392v1

    • [cs.CY]Portable Health Screening Device of Respiratory Infections
    Zheng Jiang, Menghan Hu, Guangtao Zhai
    http://arxiv.org/abs/2004.01479v1

    • [cs.DC]Assessing Impact of Data Partitioning for Approximate Memory in C/C++ Code
    Soramichi Akiyama
    http://arxiv.org/abs/2004.01637v1

    • [cs.DC]High Bandwidth Memory on FPGAs: A Data Analytics Perspective
    Kaan Kara, Christoph Hagleitner, Dionysios Diamantopoulos, Dimitris Syrivelis, Gustavo Alonso
    http://arxiv.org/abs/2004.01635v1

    • [cs.DC]Localized Mobile Agent Framework for data processing on Internet of Things
    J. Mahalakshmi, P. Venkata Krishna
    http://arxiv.org/abs/2004.01477v1

    • [cs.DC]On the Search Efficiency of Parallel Lévy Walks on $\mathbf{Z}^2$
    Andrea Clementi, Francesco d’Amore, George Giakkoupis, Emanuele Natale
    http://arxiv.org/abs/2004.01562v1

    • [cs.DC]Trustless parallel local search for effective distributed algorithm discovery
    Zvezdin Besarabov, Todor Kolev
    http://arxiv.org/abs/2004.01521v1

    • [cs.DC]User-Space Emulation Framework for Domain-Specific SoC Design
    Joshua Mack, Nirmal Kumbhare, Anish NK, Umit Y. Ogras, Ali Akoglu
    http://arxiv.org/abs/2004.01636v1

    • [cs.DL]Mapping Three Decades of Intellectual Change in Academia
    Daniel Rammage, Christopher Manning, Daniel A. McFarland
    http://arxiv.org/abs/2004.01291v1

    • [cs.DM]A Note on Double Pooling Tests
    Andrei Z. Broder, Ravi Kumar
    http://arxiv.org/abs/2004.01684v1

    • [cs.HC]Towards Designer Modeling through Design Style Clustering
    Alberto Alvarez, Jose Font, Julian Togelius
    http://arxiv.org/abs/2004.01697v1

    • [cs.IT]A Quadratic Form Approach to Construction A of Lattices over Cyclic Algebras
    Grégory Berhuy, Frédérique Oggier
    http://arxiv.org/abs/2004.01641v1

    • [cs.IT]Binary Golay Spreading Sequences and Reed-Muller Codes for Uplink Grant-Free NOMA
    Nam Yul Yu
    http://arxiv.org/abs/2004.01446v1

    • [cs.IT]Downlink Extrapolation for FDD Multiple Antenna Systems Through Neural Network Using Extracted Uplink Path Gains
    Hyuckjin Choi, Junil Choi
    http://arxiv.org/abs/2004.01361v1

    • [cs.IT]Error Detection and Correction in Communication Networks
    Chong Shangguan, Itzhak Tamo
    http://arxiv.org/abs/2004.01654v1

    • [cs.IT]On Delay-limited Average Rate of HARQ-based Predictor Antenna Systems
    Hao Guo, Behrooz Makki, Mohamed-Slim Alouini, Tommy Svensson
    http://arxiv.org/abs/2004.01423v1

    • [cs.IT]Power Allocation in HARQ-based Predictor Antenna Systems
    Hao Guo, Behrooz Makki, Mohamed-Slim Alouini, Tommy Svensson
    http://arxiv.org/abs/2004.01421v1

    • [cs.IT]The Courtade-Kumar Most Informative Boolean Function Conjecture and a Symmetrized Li-Médard Conjecture are Equivalent
    Leighton Pate Barnes, Ayfer Özgür
    http://arxiv.org/abs/2004.01277v1

    • [cs.LG]A Deep Ensemble Multi-Agent Reinforcement Learning Approach for Air Traffic Control
    Supriyo Ghosh, Sean Laguna, Shiau Hong Lim, Laura Wynter, Hasan Poonawala
    http://arxiv.org/abs/2004.01387v1

    • [cs.LG]Attribute2vec: Deep Network Embedding Through Multi-Filtering GCN
    Tingyi Wanyan, Chenwei Zhang, Ariful Azad, Xiaomin Liang, Daifeng Li, Ying Ding
    http://arxiv.org/abs/2004.01375v1

    • [cs.LG]Epitomic Variational Graph Autoencoder
    Rayyan Ahmad Khan, Martin Kleinsteuber
    http://arxiv.org/abs/2004.01468v1

    • [cs.LG]From Local SGD to Local Fixed Point Methods for Federated Learning
    Grigory Malinovsky, Dmitry Kovalev, Elnur Gasanov, Laurent Condat, Peter Richtarik
    http://arxiv.org/abs/2004.01442v1

    • [cs.LG]Hawkes Process Multi-armed Bandits for Disaster Search and Rescue
    Wen-Hao Chiang, George Mohler
    http://arxiv.org/abs/2004.01580v1

    • [cs.LG]Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip
    Yuxuan Song, Minkai Xu, Lantao Yu, Hao Zhou, Shuo Shao, Yong Yu
    http://arxiv.org/abs/2004.01454v1

    • [cs.LG]Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning
    Paulo R. de O. da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay
    http://arxiv.org/abs/2004.01608v1

    • [cs.LG]M2pht: Mixed Models with Preferences and Hybrid Transitions for Next-Basket Recommendation
    Bo Peng, Zhiyun Ren, Srinivasan Parthasarathy, Xia Ning
    http://arxiv.org/abs/2004.01646v1

    • [cs.LG]Multi-agent Reinforcement Learning for Networked System Control
    Tianshu Chu, Sandeep Chinchali, Sachin Katti
    http://arxiv.org/abs/2004.01339v1

    • [cs.LG]Neural Architecture Generator Optimization
    Binxin Ru, Pedro Esperanca, Fabio Carlucci
    http://arxiv.org/abs/2004.01395v1

    • [cs.LG]On-Device Transfer Learning for Personalising Psychological Stress Modelling using a Convolutional Neural Network
    Kieran Woodward, Eiman Kanjo, David J. Brown, T. M. McGinnity
    http://arxiv.org/abs/2004.01603v1

    • [cs.LG]Orthogonal Inductive Matrix Completion
    Antoine Ledent, Rodrigo Alves, Marius Kloft
    http://arxiv.org/abs/2004.01653v1

    • [cs.LG]Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
    Vijil Chenthamarakshan, Payel Das, Inkit Padhi, Hendrik Strobelt, Kar Wai Lim, Ben Hoover, Samuel C. Hoffman, Aleksandra Mojsilovic
    http://arxiv.org/abs/2004.01215v1

    • [cs.LG]Unpack Local Model Interpretation for GBDT
    Wenjing Fang, Jun Zhou, Xiaolong Li, Kenny Q. Zhu
    http://arxiv.org/abs/2004.01358v1

    • [cs.LG]Weighted Random Search for Hyperparameter Optimization
    Adrian-Catalin Florea, Razvan Andonie
    http://arxiv.org/abs/2004.01628v1

    • [cs.MA]Distributed Hypothesis Testing and Social Learning in Finite Time with a Finite Amount of Communication
    Shreyas Sundaram, Aritra Mitra
    http://arxiv.org/abs/2004.01306v1

    • [cs.NE]Benchmarking Deep Spiking Neural Networks on Neuromorphic Hardware
    Christoph Ostrau, Jonas Homburg, Christian Klarhorst, Michael Thies, Ulrich Rückert
    http://arxiv.org/abs/2004.01656v1

    • [cs.NE]Does Comma Selection Help To Cope With Local Optima
    Benjamin Doerr
    http://arxiv.org/abs/2004.01274v1

    • [cs.NE]The data-driven physical-based equations discovery using evolutionary approach
    Alexander Hvatov, Mikhail Maslyaev
    http://arxiv.org/abs/2004.01680v1

    • [cs.NE]Under the Hood of Neural Networks: Characterizing Learned Representations by Functional Neuron Populations and Network Ablations
    Richard Meyes, Constantin Waubert de Puiseau, Andres Posada-Moreno, Tobias Meisen
    http://arxiv.org/abs/2004.01254v1

    • [cs.NI]On the Path to High Precise IP Geolocation: A Self-Optimizing Model
    Peter Hillmann, Lars Stiemert, Gabi Dreo, Oliver Rose
    http://arxiv.org/abs/2004.01531v1

    • [cs.NI]RACE: Reinforced Cooperative Autonomous Vehicle Collision AvoidancE
    Yali Yuan, Robert Tasik, Sripriya Srikant Adhatarao, Yachao Yuan, Zheli Liu, Xiaoming Fu
    http://arxiv.org/abs/2004.01286v1

    • [cs.RO]Characterization of Multiple 3D LiDARs for Localization and Mapping using Normal Distributions Transform
    Alexander Carballo, Abraham Monrroy, David Wong, Patiphon Narksri, Jacob Lambert, Yuki Kitsukawa, Eijiro Takeuchi, Shinpei Kato, Kazuya Takeda
    http://arxiv.org/abs/2004.01374v1

    • [cs.RO]Extraction and Assessment of Naturalistic Human Driving Trajectories from Infrastructure Camera and Radar Sensors
    Dominik Notz, Felix Becker, Thomas Kühbeck, Daniel Watzenig
    http://arxiv.org/abs/2004.01288v1

    • [cs.RO]Series Elastic Force Control for Soft Robotic Fluid Actuators
    Chunpeng Wang, John P. Whitney
    http://arxiv.org/abs/2004.01269v1

    • [cs.RO]VGPN: Voice-Guided Pointing Robot Navigation for Humans
    Jun Hu, Zhongyu Jiang, Xionghao Ding, Peter Hall, Taijiang Mu
    http://arxiv.org/abs/2004.01600v1

    • [cs.SE]Using Large-Scale Anomaly Detection on Code to Improve Kotlin Compiler
    Timofey Bryksin, Victor Petukhov, Ilya Alexin, Stanislav Prikhodko, Alexey Shpilman, Vladimir Kovalenko, Nikita Povarov
    http://arxiv.org/abs/2004.01618v1

    • [cs.SI]How mobility patterns drive disease spread: A case study using public transit passenger card travel data
    Ahmad El Shoghri, Jessica Liebig, Lauren Gardner, Raja Jurdak, Salil Kanhere
    http://arxiv.org/abs/2004.01466v1

    • [cs.SI]Identifying highly influential travellers for spreading disease on a public transport system
    Ahmad El Shoghri, Jessica Liebig, Raja Jurdak, Lauren Gardner, Salil S. Kanhere
    http://arxiv.org/abs/2004.01581v1

    • [cs.SI]Motif-Based Spectral Clustering of Weighted Directed Networks
    William George Underwood, Andrew Elliott, Mihai Cucuringu
    http://arxiv.org/abs/2004.01293v1

    • [econ.GN]Predicting Labor Shortages from Labor Demand and LaborSupply Data: A Machine Learning Approach
    Nikolas Dawson, Marian-Andrei Rizoiu, Benjamin Johnston, Mary-Anne Williams
    http://arxiv.org/abs/2004.01311v1

    • [eess.AS]AI4COVID-19: AI Enabled Preliminary Diagnosis for COVID-19 from Cough Samples via an App
    Ali Imran, Iryna Posokhova, Haneya N. Qureshi, Usama Masood, Sajid Riaz, Kamran Ali, Charles N. John, Muhammad Nabeel
    http://arxiv.org/abs/2004.01275v1

    • [eess.AS]Neural i-vectors
    Ville Vestman, Kong Aik Lee, Tomi H. Kinnunen
    http://arxiv.org/abs/2004.01559v1

    • [eess.AS]Towards Relevance and Sequence Modeling in Language Recognition
    Bharat Padi, Anand Mohan, Sriram Ganapathy
    http://arxiv.org/abs/2004.01221v1

    • [eess.IV]Cell Segmentation by Combining Marker-Controlled Watershed and Deep Learning
    Filip Lux, Petr Matula
    http://arxiv.org/abs/2004.01607v1

    • [eess.IV]Crossover-Net: Leveraging the Vertical-Horizontal Crossover Relation for Robust Segmentation
    Qian Yu, Yinghuan Shi, Yefeng Zheng, Yang Gao, Jianbing Zhu, Yakang Dai
    http://arxiv.org/abs/2004.01397v1

    • [eess.IV]Deep Transfer Learning for Texture Classification in Colorectal Cancer Histology
    Srinath Jayachandran, Ashlin Ghosh
    http://arxiv.org/abs/2004.01614v1

    • [eess.IV]Detection of Perineural Invasion in Prostate Needle Biopsies with Deep Neural Networks
    Peter Ström, Kimmo Kartasalo, Pekka Ruusuvuori, Henrik Grönberg, Hemamali Samaratunga, Brett Delahunt, Toyonori Tsuzuki, Lars Egevad, Martin Eklund
    http://arxiv.org/abs/2004.01589v1

    • [eess.IV]Quantification of Tomographic Patterns associated with COVID-19 from Chest CT
    Shikha Chaganti, Abishek Balachandran, Guillaume Chabin, Stuart Cohen, Thomas Flohr, Bogdan Georgescu, Philippe Grenier, Sasa Grbic, Siqi Liu, François Mellot, Nicolas Murray, Savvas Nicolaou, William Parker, Thomas Re, Pina Sanelli, Alexander W. Sauter, Zhoubing Xu, Youngjin Yoo, Valentin Ziebandt, Dorin Comaniciu
    http://arxiv.org/abs/2004.01279v1

    • [eess.IV]Retinopathy of Prematurity Stage Diagnosis Using Object Segmentation and Convolutional Neural Networks
    Alexander Ding, Qilei Chen, Yu Cao, Benyuan Liu
    http://arxiv.org/abs/2004.01582v1

    • [eess.IV]STAN-CT: Standardizing CT Image using Generative Adversarial Network
    Md Selim, Jie Zhang, Baowei Fei, Guo-Qiang Zhang, Jin Chen
    http://arxiv.org/abs/2004.01307v1

    • [eess.SY]Data-Driven Transient Stability Boundary Generation for Online Security Monitoring
    Rong Yan, Guangchao Geng, Quanyuan Jiang
    http://arxiv.org/abs/2004.01369v1

    • [eess.SY]Event-Triggered Distributed Inference
    Aritra Mitra, Saurabh Bagchi, Shreyas Sundaram
    http://arxiv.org/abs/2004.01302v1

    • [eess.SY]FeederGAN: Synthetic Feeder Generation via Deep Graph Adversarial Nets
    Ming Liang, Yao Meng, Jiyu Wang, David Lubkeman, Ning Lu
    http://arxiv.org/abs/2004.01407v1

    • [eess.SY]Reinforcement Learning for Mixed-Integer Problems Based on MPC
    Sebastien Gros, Mario Zanon
    http://arxiv.org/abs/2004.01430v1

    • [math.NA]Resampling with neural networks for stochastic parameterization in multiscale systems
    Daan Crommelin, Wouter Edeling
    http://arxiv.org/abs/2004.01457v1

    • [math.ST]Relaxing the Gaussian assumption in Shrinkage and SURE in high dimension
    Max Fathi, Larry Goldstein, Gesine Reinert, Adrien Saumard
    http://arxiv.org/abs/2004.01378v1

    • [physics.med-ph]Predicting the risk of pancreatic cancer with a CT-based ensemble AI algorithm
    Chenjie Zhou MD, Jianhua Ma Ph. D, Xiaoping Xu MD, Lei Feng MD, Adilijiang Yimamu MD, Xianlong Wang MD, Zhiming Li MD, Jianhua Mo MS, Chengyan Huang MS, Dexia Kong MS, Yi Gao MD, Shulong Li Ph. D
    http://arxiv.org/abs/2004.01388v1

    • [physics.soc-ph]Bridging the gap between graphs and networks
    Gerardo Iñiguez, Federico Battiston, Márton Karsai
    http://arxiv.org/abs/2004.01467v1

    • [physics.soc-ph]Generating Similarity Map in COVID-19 Transmission Dynamics with Topological Autoencoder
    Pitoyo Hartono
    http://arxiv.org/abs/2004.01481v1

    • [physics.soc-ph]Layer entanglement in multiplex, temporal multiplex, and coupled multilayer networks
    Blaž Škrlj, Benjamin Renoust
    http://arxiv.org/abs/2004.01534v1

    • [physics.soc-ph]The Wigner’s Semicircle Law of Weighted Random Networks
    Yusuke Sakumoto, Masaki Aida
    http://arxiv.org/abs/2004.00125v2

    • [q-bio.PE]Analysis of the COVID-19 pandemic by SIR model and machine learning technics for forecasting
    Babacar Mbaye Ndiaye, Lena Tendeng, Diaraf Seck
    http://arxiv.org/abs/2004.01574v1

    • [q-bio.QM]Predicting rice blast disease: machine learning versus process based models
    David F. Nettleton, Dimitrios Katsantonis, Argyris Kalaitzidis, Natasa Sarafijanovic-Djukic, Pau Puigdollers, Roberto Confalonieri
    http://arxiv.org/abs/2004.01602v1

    • [stat.AP]COVID-19: Should We Test Everyone?
    Grace Yi, Wenqing He, Dennis Kon-Jin Lin, Chun-Ming Yu
    http://arxiv.org/abs/2004.01252v1

    • [stat.AP]Estimation of daily streamflow from multiple donor catchments with Graphical Lasso
    German A. Villalba, Xu Liang, Yao Liang
    http://arxiv.org/abs/2004.01373v1

    • [stat.CO]Hierarchical Bayesian Nearest Neighbor Co-Kriging Gaussian Process Models; An Application to Intersatellite Calibration
    Si Cheng, Bledar A. Konomi, Jessica L. Matthews, Georgios Karagianis, Emily L. Kang
    http://arxiv.org/abs/2004.01341v1

    • [stat.ME]A sequential design for extreme quantiles estimation under binary sampling
    Michel Broniatowski, Emilie Miranda
    http://arxiv.org/abs/2004.01563v1

    • [stat.ME]Composite mixture of log-linear models for categorical data
    Emanuele Aliverti, David B. Dunson
    http://arxiv.org/abs/2004.01462v1

    • [stat.ME]General Identification of Dynamic Treatment Regimes Under Interference
    Eli Sherman, David Arbour, Ilya Shpitser
    http://arxiv.org/abs/2004.01218v1

    • [stat.ME]Generalized inverse-Gaussian frailty models with application to TARGET neuroblastoma data
    Luiza Sette Câmara Piancastelli, Wagner Barreto-Souza, Vinícius Diniz Mayrink
    http://arxiv.org/abs/2004.01292v1

    • [stat.ME]Penalized composite likelihood for colored graphical Gaussian models
    Qiong Li, Xiaoying Sun, Nanwei Wang
    http://arxiv.org/abs/2004.01328v1

    • [stat.ME]Robust Parametric Inference for Finite Markov Chains
    Abhik Ghosh
    http://arxiv.org/abs/2004.01249v1

    • [stat.ME]Uniform Inference in High-Dimensional Generalized Additive Models
    Philipp Bach, Sven Klaassen, Jannis Kueck, Martin Spindler
    http://arxiv.org/abs/2004.01623v1

    • [stat.ML]A rigorous method to compare interpretability of rule-based algorithms
    Vincent Margot
    http://arxiv.org/abs/2004.01570v1

    • [stat.ML]Distributed Primal-Dual Optimization for Online Multi-Task Learning
    Peng Yang, Ping Li
    http://arxiv.org/abs/2004.01305v1

    • [stat.ML]Faster Gaussian Processes via Deep Embeddings
    Constantinos Daskalakis, Petros Dellaportas, Aristeidis Panos
    http://arxiv.org/abs/2004.01584v1

    • [stat.ML]IVFS: Simple and Efficient Feature Selection for High Dimensional Topology Preservation
    Xiaoyun Li, Chengxi Wu, Ping Li
    http://arxiv.org/abs/2004.01299v1

    • [stat.ML]Neural Conditional Event Time Models
    Matthew Engelhard, Samuel Berchuck, Joshua D’Arcy, Ricardo Henao
    http://arxiv.org/abs/2004.01376v1

    • [stat.ML]Predicting the outputs of finite networks trained with noisy gradients
    Gadi Naveh, Oded Ben-David, Haim Sompolinsky, Zohar Ringel
    http://arxiv.org/abs/2004.01190v1

    • [stat.ML]TRAMP: Compositional Inference with TRee Approximate Message Passing
    Antoine Baker, Benjamin Aubin, Florent Krzakala, Lenka Zdeborová
    http://arxiv.org/abs/2004.01571v1