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
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• [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