cond-mat.mes-hall - 尺度和物理纳米
cond-mat.mtrl-sci - 材料科学 cs.AI - 人工智能 cs.AR - 硬件体系结构 cs.CE - 计算工程、 金融和科学 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 cs.GT - 计算机科学与博弈论 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.MA - 多代理系统 cs.MM - 多媒体 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.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.OC - 优化与控制 math.ST - 统计理论 physics.data-an - 数据分析、 统计和概率 physics.soc-ph - 物理学与社会 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
• [cond-mat.mes-hall]Computational Study of Ultrathin CNT Films with the Scalable Mesoscopic Distinct Element Method
• [cond-mat.mtrl-sci]Style transfer based data augmentation in material microscopic image processing
• [cs.AI]Controlled Natural Languages and Default Reasoning
• [cs.AI]Explaining intuitive difficulty judgments by modeling physical effort and risk
• [cs.AI]Learning and Planning in Feature Deception Games
• [cs.AI]Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs
• [cs.AI]Ludii - The ludemic General Game System
• [cs.AI]Mega-Reward: Achieving Human-Level Play without Extrinsic Rewards
• [cs.AR]Optimizing Routerless Network-on-Chip Designs: An Innovative Learning-Based Framework
• [cs.CE]Similarity Grouping-Guided Neural Network Modeling for Maritime Time Series Prediction
• [cs.CL]A Benchmark Study on Machine Learning Methods for Fake News Detection
• [cs.CL]A Comparison of Techniques for Sentiment Classification of Film Reviews
• [cs.CL]A Review of Keyphrase Extraction
• [cs.CL]Improving Natural Language Interaction with Robots Using Advice
• [cs.CL]Modelling Instance-Level Annotator Reliability for Natural Language Labelling Tasks
• [cs.CL]Semantic categories of artifacts and animals reflect efficient coding
• [cs.CL]Synchronous Bidirectional Neural Machine Translation
• [cs.CR]GraphSE$^2$: An Encrypted Graph Database for Privacy-Preserving Social Search
• [cs.CR]On the Compositionality of Dynamic Leakage and Its Application to the Quantification Problem
• [cs.CR]The Language of Biometrics: Analysing Public Perceptions
• [cs.CR]Understanding eWhoring
• [cs.CV]”The cracks that wanted to be a graph”: application of image processing and Graph Neural Networks to the description of craquelure patterns
• [cs.CV]A High-Efficiency Framework for Constructing Large-Scale Face Parsing Benchmark
• [cs.CV]A novel statistical metric learning for hyperspectral image classification
• [cs.CV]Adaptive Composition GAN towards Realistic Image Synthesis
• [cs.CV]Appearance-Based Gaze Estimation via Gaze Decomposition and Single Gaze Point Calibration
• [cs.CV]Block Coordinate Regularization by Denoising
• [cs.CV]Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints
• [cs.CV]CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
• [cs.CV]Cyclone intensity estimate with context-aware cyclegan
• [cs.CV]Deep Plug-and-play Prior for Low-rank Tensor Completion
• [cs.CV]Deep Unsupervised Learning of 3D Point Clouds via Graph Topology Inference and Filtering
• [cs.CV]Deep Zero-Shot Learning for Scene Sketch
• [cs.CV]DeepIlluminance: Contextual Illuminance Estimation via Deep Neural Networks
• [cs.CV]Disentangling Content and Style via Unsupervised Geometry Distillation
• [cs.CV]Ensemble Super-Resolution with A Reference Dataset
• [cs.CV]FPGA-based Binocular Image Feature Extraction and Matching System
• [cs.CV]Few-Shot Viewpoint Estimation
• [cs.CV]Follow the Attention: Combining Partial Pose and Object Motion for Fine-Grained Action Detection
• [cs.CV]Group Re-identification via Transferred Single and Couple Representation Learning
• [cs.CV]Illumination-Adaptive Person Re-identification
• [cs.CV]Joint Learning of Self-Representation and Indicator for Multi-View Image Clustering
• [cs.CV]Joint demosaicing and denoising by overfitting of bursts of raw images
• [cs.CV]Leveraging synthetic imagery for collision-at-sea avoidance
• [cs.CV]Medical image super-resolution method based on dense blended attention network
• [cs.CV]Monocular Depth Estimation with Directional Consistency by Deep Networks
• [cs.CV]Multitask deep learning with spectral knowledge for hyperspectral image classification
• [cs.CV]NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding
• [cs.CV]Object Detection in 20 Years: A Survey
• [cs.CV]Object Detection in Specific Traffic Scenes using YOLOv2
• [cs.CV]On Flow Profile Image for Video Representation
• [cs.CV]One-Shot Image-to-Image Translation via Part-Global Learning with a Multi-adversarial Framework
• [cs.CV]PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization
• [cs.CV]Play and Prune: Adaptive Filter Pruning for Deep Model Compression
• [cs.CV]Precipitation nowcasting using a stochastic variational frame predictor with learned prior distribution
• [cs.CV]Predictive Ensemble Learning with Application to Scene Text Detection
• [cs.CV]Quantifying and Alleviating the Language Prior Problem in Visual Question Answering
• [cs.CV]Robustness of Object Recognition under Extreme Occlusion in Humans and Computational Models
• [cs.CV]Segregation Network for Multi-Class Novelty Detection
• [cs.CV]Self-Supervised Visual Place Recognition Learning in Mobile Robots
• [cs.CV]Social Relation Recognition in Egocentric Photostreams
• [cs.CV]Some Research Problems in Biometrics: The Future Beckons
• [cs.CV]Structure from Articulated Motion: An Accurate and Stable Monocular 3D Reconstruction Approach without Training Data
• [cs.CV]Structured Discriminative Tensor Dictionary Learning for Unsupervised Domain Adaptation
• [cs.CV]Triplet Distillation for Deep Face Recognition
• [cs.CV]Unified Generator-Classifier for Efficient Zero-Shot Learning
• [cs.CV]Video Instance Segmentation
• [cs.CV]VideoGraph: Recognizing Minutes-Long Human Activities in Videos
• [cs.CV]Weakly-supervised Caricature Face Parsing through Domain Adaptation
• [cs.CV]Zoom To Learn, Learn To Zoom
• [cs.CY]A resource-based rule engine for energy savings recommendations in educational buildings
• [cs.CY]Enhancing Trust in eAssessment - the TeSLA System Solution
• [cs.CY]Lie on the Fly: Strategic Voting in an Iterative Preference Elicitation Process
• [cs.DB]NFTracer: A Non-Fungible Token Tracking Proof-of-Concept Using Hyperledger Fabric
• [cs.DC]A Distributed Laplacian Solver and its Applications to Electrical Flow and Random Spanning Tree Computation
• [cs.DC]A new SSO-based Algorithm for the Bi-Objective Time-constrained task Scheduling Problem in Cloud Computing Services
• [cs.DC]Analysis of Committee Selection Mechanism in Blockchain
• [cs.DC]Analysis of Global Fixed-Priority Scheduling for Generalized Sporadic DAG Tasks
• [cs.DC]Energy-Aware Scheduling of Task Graphs with Imprecise Computations and End-to-End Deadlines
• [cs.DC]F-FDN: Federation of Fog Computing Systems for Low Latency Video Streaming
• [cs.DC]Improving Robustness of Heterogeneous Serverless Computing Systems Via Probabilistic Task Pruning
• [cs.DC]Introduction to StarNEig — A Task-based Library for Solving Nonsymmetric Eigenvalue Problems
• [cs.DC]K-Athena: a performance portable structured grid finite volume magnetohydrodynamics code
• [cs.DC]NeuPart: Using Analytical Models to Drive Energy-Efficient Partitioning of CNN Computations on Cloud-Connected Mobile Clients
• [cs.DC]ONLAY: Online Layering for scalable asynchronous BFT system
• [cs.DC]Quantitative Analysis of Cloud Function Evolution in the AWS Serverless Application Repository
• [cs.DC]Robust Resource Allocation Using Edge Computing for Vehicle to Infrastructure (V2I) Networks
• [cs.DC]Serverless Edge Computing for Green Oil and Gas Industry
• [cs.DS]PrivateJobMatch: A Privacy-Oriented Deferred Multi-Match Recommender System for Stable Employment
• [cs.DS]Solving Empirical Risk Minimization in the Current Matrix Multiplication Time
• [cs.GT]Exogenous Rewards for Promoting Cooperation in Scale-Free Networks
• [cs.IR]Data description and retrieval using periods represented by uncertain time intervals
• [cs.IR]Deep Landscape Forecasting for Real-time Bidding Advertising
• [cs.IR]Hadamard Matrix Guided Online Hashing
• [cs.IR]Information search in a professional context - exploring a collection of professional search tasks
• [cs.IT]Construction of three classes of Strictly Optimal Frequency-Hopping Sequence Sets
• [cs.IT]Hessian transport Gradient flows
• [cs.IT]Radio Map Based Path Planning for Cellular-Connected UAV
• [cs.IT]Secure Hybrid Digital and Analog Precoder for mmWave Systems with low-resolution DACs and finite-quantized phase shifters
• [cs.IT]Sparse Optimization Problem with s-difference Regularization
• [cs.IT]Structured Mappings and Conferencing Common Information for Multiple-access Channels
• [cs.IT]Ultra-small Cell Networks with Collaborative RF and Lightwave Power Transfer
• [cs.LG]A New Look at an Old Problem: A Universal Learning Approach to Linear Regression
• [cs.LG]Accuracy Improvement of Neural Network Training using Particle Swarm Optimization and its Stability Analysis for Classification
• [cs.LG]Approximated Oracle Filter Pruning for Destructive CNN Width Optimization
• [cs.LG]BayesNAS: A Bayesian Approach for Neural Architecture Search
• [cs.LG]Boosting Generative Models by Leveraging Cascaded Meta-Models
• [cs.LG]CASTNet: Community-Attentive Spatio-Temporal Networks for Opioid Overdose Forecasting
• [cs.LG]Diagnosing Reinforcement Learning for Traffic Signal Control
• [cs.LG]Differentiable Game Mechanics
• [cs.LG]Differentially Private Empirical Risk Minimization with Sparsity-Inducing Norms
• [cs.LG]Dissecting Graph Neural Networks on Graph Classification
• [cs.LG]Explainable AI for Trees: From Local Explanations to Global Understanding
• [cs.LG]Federated Multi-task Hierarchical Attention Model for Sensor Analytics
• [cs.LG]Few-Shot Learning with Embedded Class Models and Shot-Free Meta Training
• [cs.LG]Flat Metric Minimization with Applications in Generative Modeling
• [cs.LG]Hierarchical Importance Weighted Autoencoders
• [cs.LG]ISBNet: Instance-aware Selective Branching Network
• [cs.LG]Implicit Filter Sparsification In Convolutional Neural Networks
• [cs.LG]Interpret Federated Learning with Shapley Values
• [cs.LG]Knowledge Graph Convolutional Networks for Recommender Systems with Label Smoothness Regularization
• [cs.LG]Learning Phase Competition for Traffic Signal Control
• [cs.LG]Learning in structured MDPs with convex cost functions: Improved regret bounds for inventory management
• [cs.LG]Learning to Convolve: A Generalized Weight-Tying Approach
• [cs.LG]Machine learning in cardiovascular flows modeling: Predicting pulse wave propagation from non-invasive clinical measurements using physics-informed deep learning
• [cs.LG]Multi-Agent Image Classification via Reinforcement Learning
• [cs.LG]Multi-Pass Q-Networks for Deep Reinforcement Learning with Parameterised Action Spaces
• [cs.LG]Multi-View Multi-Instance Multi-Label Learning based on Collaborative Matrix Factorization
• [cs.LG]Multi-View Multiple Clustering
• [cs.LG]On Graph Classification Networks, Datasets and Baselines
• [cs.LG]Ranking-based Deep Cross-modal Hashing
• [cs.LG]Robust Learning from Noisy Side-information by Semidefinite Programming
• [cs.LG]Solving Irregular and Data-enriched Differential Equations using Deep Neural Networks
• [cs.LG]Spectral Analysis of Kernel and Neural Embeddings: Optimization and Generalization
• [cs.LG]Stability Properties of Graph Neural Networks
• [cs.LG]Tabular Benchmarks for Joint Architecture and Hyperparameter Optimization
• [cs.LG]Task-Agnostic Dynamics Priors for Deep Reinforcement Learning
• [cs.LG]Theoretical Limits of One-Shot Distributed Learning
• [cs.LG]Towards a regularity theory for ReLU networks — chain rule and global error estimates
• [cs.LG]Training CNNs with Selective Allocation of Channels
• [cs.LG]Tree-wise Distribution Sensitive hashing: Efficient Maximum likelihood Classification by joint dimensionality reduction in known probabilistic settings
• [cs.LG]Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
• [cs.LG]Universal Invariant and Equivariant Graph Neural Networks
• [cs.LG]What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use
• [cs.LO]Rough Contact in General Rough Mereology
• [cs.MA]Evidence Propagation and Consensus Formation in Noisy Environments
• [cs.MA]Physically-interpretable classification of network dynamics for complex collective motions
• [cs.MM]Deep Vocoder: Low Bit Rate Speech Compression of Speech with Deep Autoencoder
• [cs.NE]A Stock Selection Method Based on Earning Yield Forecast Using Sequence Prediction Models
• [cs.NE]Deep Learning: a new definition of artificial neuron with double weight
• [cs.NE]Enabling Explainable Fusion in Deep Learning with Fuzzy Integral Neural Networks
• [cs.NI]Analyzing Adversarial Attacks Against Deep Learning for Intrusion Detection in IoT Networks
• [cs.RO]AMZ Driverless: The Full Autonomous Racing System
• [cs.RO]Automatic Calibration of Multiple 3D LiDARs in Urban Environments
• [cs.RO]Ceiling Effects for Hybrid Aerial-Surface Locomotion of Small Rotorcraft
• [cs.RO]Decentralized Impedance Control for Cooperative Manipulation of Multiple Underwater Vehicle Manipulator Systems under Lean Communication
• [cs.RO]Extending Policy from One-Shot Learning through Coaching
• [cs.RO]Failure-Tolerant Connectivity Maintenance for Robot Swarms
• [cs.RO]Integrating Objects into Monocular SLAM: Line Based Category Specific Models
• [cs.RO]Let’s Push Things Forward: A Survey on Robot Pushing
• [cs.RO]Locally Weighted Regression Pseudo-Rehearsal for Online Learning of Vehicle Dynamics
• [cs.RO]Occlusion-Robust MVO: Multimotion Estimation Through Occlusion Via Motion Closure
• [cs.RO]Real-Time Kinodynamic Motion Planning for Omnidirectional Mobile Robot Soccer using Rapidly-Exploring Random Tree in Dynamic Environment with Moving Obstacles
• [cs.SD]Time-Contrastive Learning Based Deep Bottleneck Features for Text-Dependent Speaker Verification
• [cs.SE]Automating chaos experiments in production
• [cs.SI]Election Control with Voters’ Uncertainty: Hardness and Approximation Results
• [cs.SI]Influencing Opinions of Heterogeneous Populations over Finite Time Horizons
• [cs.SI]Language in Our Time: An Empirical Analysis of Hashtags
• [cs.SI]Mining Hidden Populations through Attributed Search
• [cs.SI]Seeding with Costly Network Information
• [cs.SI]The Secret Lives of Names? Name Embeddings from Social Media
• [eess.IV]A Cone-Beam X-Ray CT Data Collection Designed for Machine Learning
• [eess.IV]Generative Adversarial Networks and Conditional Random Fields for Hyperspectral Image Classification
• [eess.IV]Generative Modeling and Inverse Imaging of Cardiac Transmembrane Potential
• [eess.IV]Programmable Spectrometry — Per-pixel Classification of Materials using Learned Spectral Filters
• [eess.SP]Adversarial Examples for Electrocardiograms
• [eess.SP]ECG Identification under Exercise and Rest Situations via Various Learning Methods
• [eess.SP]Interference Mitigation and Resource Allocation in Underlay Cognitive Radio Networks
• [eess.SP]Large-Scale Spectrum Occupancy Learning via Tensor Decomposition and LSTM Networks
• [eess.SP]Low Noise Non-Linear Equalization Using Neural Networks and Belief Propagation
• [eess.SP]Massive MIMO Extensions to the COST 2100 Channel Model: Modeling and Validation
• [eess.SP]Sparse Recovery Beyond Compressed Sensing: Separable Nonlinear Inverse Problems
• [eess.SP]Terahertz-Band Ultra-Massive Spatial Modulation MIMO
• [math.OC]Channels, Learning, Queueing and Remote Estimation Systems With A Utilization-Dependent Component
• [math.ST]ACF estimation via difference schemes for a semiparametric model with $m$-dependent errors
• [math.ST]Hyperparameter Estimation in Bayesian MAP Estimation: Parameterizations and Consistency
• [math.ST]Is Volatility Rough ?
• [math.ST]Moment Identifiability of Homoscedastic Gaussian Mixtures
• [math.ST]Sub-Weibull distributions: generalizing sub-Gaussian and sub-Exponential properties to heavier-tailed distributions
• [physics.data-an]A class of randomized Subset Selection Methods for large complex networks
• [physics.soc-ph]Emergence of an Onion-like Network in Surface Growth and Its Strong Robustness
• [stat.AP]Modeling failures times with dependent renewal type models via exchangeability
• [stat.AP]Partially Specified Space Time Autoregressive Model with Artificial Neural Network
• [stat.AP]Partisan Lean of States: Electoral College and Popular Vote
• [stat.AP]Time delay estimation in satellite imagery time series of precipitation and NDVI: Pearson’s cross correlation revisited
• [stat.AP]Urban greenery and mental wellbeing in adults: Cross-sectional mediation analyses on multiple pathways across different greenery measures
• [stat.CO]The compound product distribution; a solution to the distributional equation X=AX+1
• [stat.ME]A Spatial Concordance Correlation Coefficient with an Application to Image Analysis
• [stat.ME]Asymmetric tail dependence modeling, with application to cryptocurrency market data
• [stat.ME]Note on Thompson sampling for large decision problems
• [stat.ME]Prediction and outlier detection: a distribution-free prediction set with a balanced objective
• [stat.ME]Statistical inference with anchored Bayesian mixture of regressions models: A case study analysis of allometric data
• [stat.ME]Structural Equation Modeling using Computation Graphs
• [stat.ML]Active Embedding Search via Noisy Paired Comparisons
• [stat.ML]Bayesian Hierarchical Mixture Clustering using Multilevel Hierarchical Dirichlet Processes
• [stat.ML]Exact high-dimensional asymptotics for support vector machine
• [stat.ML]Functional Correlations in the Pursuit of Performance Assessment of Classifiers
• [stat.ML]Learning Hierarchical Priors in VAEs
• [stat.ML]Learning to Search Efficiently Using Comparisons
• [stat.ML]On the Performance of Thompson Sampling on Logistic Bandits
• [stat.ML]Rotation Invariant Householder Parameterization for Bayesian PCA
• [stat.ML]Variational inference for neural network matrix factorization and its application to stochastic blockmodeling
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• [cond-mat.mes-hall]Computational Study of Ultrathin CNT Films with the Scalable Mesoscopic Distinct Element Method
Igor Ostanin, Traian Dumitrică, Sebastian Eibl, Ulrich Rüde
http://arxiv.org/abs/1905.05042v1
• [cond-mat.mtrl-sci]Style transfer based data augmentation in material microscopic image processing
Boyuan Ma, Xiaoyan Wei, Chuni Liu, Xiaojuan Ban, Haiyou Huan, Hao Wang, Weihua Xue
http://arxiv.org/abs/1905.04711v1
• [cs.AI]Controlled Natural Languages and Default Reasoning
Tiantian Gao
http://arxiv.org/abs/1905.04422v1
• [cs.AI]Explaining intuitive difficulty judgments by modeling physical effort and risk
Ilker Yildirim, Basil Saeed, Grace Bennett-Pierre, Tobias Gerstenberg, Joshua Tenenbaum, Hyowon Gweon
http://arxiv.org/abs/1905.04445v1
• [cs.AI]Learning and Planning in Feature Deception Games
Zheyuan Ryan Shi, Ariel D. Procaccia, Kevin S. Chan, Sridhar Venkatesan, Noam Ben-Asher, Nandi O. Leslie, Charles Kamhoua, Fei Fang
http://arxiv.org/abs/1905.04833v1
• [cs.AI]Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs
Lingbing Guo, Zequn Sun, Wei Hu
http://arxiv.org/abs/1905.04914v1
• [cs.AI]Ludii - The ludemic General Game System
Eric Piette, Dennis J. N. J. Soemers, Matthew Stephenson, Chiara F. Sironi, Mark H. M. Winands, Cameron Browne
http://arxiv.org/abs/1905.05013v1
• [cs.AI]Mega-Reward: Achieving Human-Level Play without Extrinsic Rewards
Yuhang Song, Jianyi Wang, Thomas Lukasiewicz, Zhenghua Xu, Shangtong Zhang, Mai Xu
http://arxiv.org/abs/1905.04640v1
• [cs.AR]Optimizing Routerless Network-on-Chip Designs: An Innovative Learning-Based Framework
Ting-Ru Lin, Drew Penney, Massoud Pedram, Lizhong Chen
http://arxiv.org/abs/1905.04423v1
• [cs.CE]Similarity Grouping-Guided Neural Network Modeling for Maritime Time Series Prediction
Yan Li, Ryan Wen Liu, Zhao Liu, Jingxian Liu
http://arxiv.org/abs/1905.04872v1
• [cs.CL]A Benchmark Study on Machine Learning Methods for Fake News Detection
Junaed Younus Khan, Md. Tawkat Islam Khondaker, Anindya Iqbal, Sadia Afroz
http://arxiv.org/abs/1905.04749v1
• [cs.CL]A Comparison of Techniques for Sentiment Classification of Film Reviews
Milan Gritta
http://arxiv.org/abs/1905.04727v1
• [cs.CL]A Review of Keyphrase Extraction
Eirini Papagiannopoulou, Grigorios Tsoumakas
http://arxiv.org/abs/1905.05044v1
• [cs.CL]Improving Natural Language Interaction with Robots Using Advice
Nikhil Mehta, Dan Goldwasser
http://arxiv.org/abs/1905.04655v1
• [cs.CL]Modelling Instance-Level Annotator Reliability for Natural Language Labelling Tasks
Maolin Li, Arvid Fahlström Myrman, Tingting Mu, Sophia Ananiadou
http://arxiv.org/abs/1905.04981v1
• [cs.CL]Semantic categories of artifacts and animals reflect efficient coding
Noga Zaslavsky, Terry Regier, Naftali Tishby, Charles Kemp
http://arxiv.org/abs/1905.04562v1
• [cs.CL]Synchronous Bidirectional Neural Machine Translation
Long Zhou, Jiajun Zhang, Chengqing Zong
http://arxiv.org/abs/1905.04847v1
• [cs.CR]GraphSE$^2$: An Encrypted Graph Database for Privacy-Preserving Social Search
Shangqi Lai, Xingliang Yuan, Shi-Feng Sun, Joseph K. Liu, Yuhong Liu, Dongxi Liu
http://arxiv.org/abs/1905.04501v1
• [cs.CR]On the Compositionality of Dynamic Leakage and Its Application to the Quantification Problem
Bao Trung Chu, Kenji Hashimoto, Hiroyuki Seki
http://arxiv.org/abs/1905.04409v1
• [cs.CR]The Language of Biometrics: Analysing Public Perceptions
Oliver Buckley, Jason R. C. Nurse
http://arxiv.org/abs/1905.04615v1
• [cs.CR]Understanding eWhoring
Alice Hutchings, Sergio Pastrana
http://arxiv.org/abs/1905.04576v1
• [cs.CV]“The cracks that wanted to be a graph”: application of image processing and Graph Neural Networks to the description of craquelure patterns
Oleksii Sidorov, Jon Yngve Hardeberg
http://arxiv.org/abs/1905.05010v1
• [cs.CV]A High-Efficiency Framework for Constructing Large-Scale Face Parsing Benchmark
Yinglu Liu, Hailin Shi, Yue Si, Hao Shen, Xiaobo Wang, Tao Mei
http://arxiv.org/abs/1905.04830v1
• [cs.CV]A novel statistical metric learning for hyperspectral image classification
Zhiqiang Gong, Ping Zhong, Weidong Hu, Zixuan Xiao, Xuping Yin
http://arxiv.org/abs/1905.05087v1
• [cs.CV]Adaptive Composition GAN towards Realistic Image Synthesis
Fangneng Zhan, Jiaxing Huang, Shijian Lu
http://arxiv.org/abs/1905.04693v1
• [cs.CV]Appearance-Based Gaze Estimation via Gaze Decomposition and Single Gaze Point Calibration
Zhaokang Chen, Bertram E. Shi
http://arxiv.org/abs/1905.04451v1
• [cs.CV]Block Coordinate Regularization by Denoising
Yu Sun, Jiaming Liu, Ulugbek S. Kamilov
http://arxiv.org/abs/1905.05113v1
• [cs.CV]Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints
Mengtian Li, Ersin Yumer, Deva Ramanan
http://arxiv.org/abs/1905.04753v1
• [cs.CV]CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, Youngjoon Yoo
http://arxiv.org/abs/1905.04899v1
• [cs.CV]Cyclone intensity estimate with context-aware cyclegan
Yajing Xu, Haitao Yang, Mingfei Cheng, Si Li
http://arxiv.org/abs/1905.04425v1
• [cs.CV]Deep Plug-and-play Prior for Low-rank Tensor Completion
Wen-Hao Xu, Xi-Le Zhao, Tai-Xiang Jiang, Yao Wang, Michael Ng
http://arxiv.org/abs/1905.04449v1
• [cs.CV]Deep Unsupervised Learning of 3D Point Clouds via Graph Topology Inference and Filtering
Siheng Chen, Chaojing Duan, Yaoqing Yang, Duanshun Li, Chen Feng, Dong Tian
http://arxiv.org/abs/1905.04571v1
• [cs.CV]Deep Zero-Shot Learning for Scene Sketch
Yao Xie, Peng Xu, Zhanyu Ma
http://arxiv.org/abs/1905.04510v1
• [cs.CV]DeepIlluminance: Contextual Illuminance Estimation via Deep Neural Networks
Jun Zhang, Tong Zheng, Shengping Zhang, Meng Wang
http://arxiv.org/abs/1905.04791v1
• [cs.CV]Disentangling Content and Style via Unsupervised Geometry Distillation
Wayne Wu, Kaidi Cao, Cheng Li, Chen Qian, Chen Change Loy
http://arxiv.org/abs/1905.04538v1
• [cs.CV]Ensemble Super-Resolution with A Reference Dataset
Junjun Jiang, Yi Yu, Zheng Wang, Suhua Tang, Ruimin Hu, Jiayi Ma
http://arxiv.org/abs/1905.04696v1
• [cs.CV]FPGA-based Binocular Image Feature Extraction and Matching System
Qi Ni, Fei Wang, Ziwei Zhao, Peng Gao
http://arxiv.org/abs/1905.04890v1
• [cs.CV]Few-Shot Viewpoint Estimation
Hung-Yu Tseng, Shalini De Mello, Jonathan Tremblay, Sifei Liu, Stan Birchfield, Ming-Hsuan Yang, Jan Kautz
http://arxiv.org/abs/1905.04957v1
• [cs.CV]Follow the Attention: Combining Partial Pose and Object Motion for Fine-Grained Action Detection
Mohammad Mahdi Kazemi Moghaddam, Ehsan Abbasnejad, Javen Shi
http://arxiv.org/abs/1905.04430v1
• [cs.CV]Group Re-identification via Transferred Single and Couple Representation Learning
Ziling Huang, Zheng Wang, Shin’ichi Satoh, Chia-Wen Lin
http://arxiv.org/abs/1905.04854v1
• [cs.CV]Illumination-Adaptive Person Re-identification
Zelong Zeng, Zhixiang Wang, Zheng Wang, Yung-Yu Chuang, Shin’ichi Satoh
http://arxiv.org/abs/1905.04525v1
• [cs.CV]Joint Learning of Self-Representation and Indicator for Multi-View Image Clustering
Songsong Wu, Zhiqiang Lu, Hao Tang, Yan Yan, Songhao Zhu, Xiao-Yuan Jing, Zuoyong Li
http://arxiv.org/abs/1905.04432v1
• [cs.CV]Joint demosaicing and denoising by overfitting of bursts of raw images
Thibaud Ehret, Axel Davy, Pablo Arias, Gabriele Facciolo
http://arxiv.org/abs/1905.05092v1
• [cs.CV]Leveraging synthetic imagery for collision-at-sea avoidance
Chris M. Ward, Josh Harguess, Alexander G. Corelli
http://arxiv.org/abs/1905.04828v1
• [cs.CV]Medical image super-resolution method based on dense blended attention network
Kewen Liu, Yuan Ma, Hongxia Xiong, Zejun Yan, Zhijun Zhou, Panpan Fang, Chaoyang Liu
http://arxiv.org/abs/1905.05084v1
• [cs.CV]Monocular Depth Estimation with Directional Consistency by Deep Networks
Fabian Truetsch, Alfred Schöttl
http://arxiv.org/abs/1905.04467v1
• [cs.CV]Multitask deep learning with spectral knowledge for hyperspectral image classification
Shengjie Liu, Qian Shi, Zhixin Qi
http://arxiv.org/abs/1905.04535v1
• [cs.CV]NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding
Jun Liu, Amir Shahroudy, Mauricio Perez, Gang Wang, Ling-Yu Duan, Alex C. Kot
http://arxiv.org/abs/1905.04757v1
• [cs.CV]Object Detection in 20 Years: A Survey
Zhengxia Zou, Zhenwei Shi, Yuhong Guo, Jieping Ye
http://arxiv.org/abs/1905.05055v1
• [cs.CV]Object Detection in Specific Traffic Scenes using YOLOv2
Shouyu Wang, Weitao Tang
http://arxiv.org/abs/1905.04740v1
• [cs.CV]On Flow Profile Image for Video Representation
Mohammadreza Babaee, David Full, Gerhard Rigoll
http://arxiv.org/abs/1905.04668v1
• [cs.CV]One-Shot Image-to-Image Translation via Part-Global Learning with a Multi-adversarial Framework
Ziqiang Zheng, Zhibin Yu, Haiyong Zheng, Yang Yang, Heng Tao Shen
http://arxiv.org/abs/1905.04729v1
• [cs.CV]PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization
Shunsuke Saito, Zeng Huang, Ryota Natsume, Shigeo Morishima, Angjoo Kanazawa, Hao Li
http://arxiv.org/abs/1905.05172v1
• [cs.CV]Play and Prune: Adaptive Filter Pruning for Deep Model Compression
Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri
http://arxiv.org/abs/1905.04446v1
• [cs.CV]Precipitation nowcasting using a stochastic variational frame predictor with learned prior distribution
Alexander Bihlo
http://arxiv.org/abs/1905.05037v1
• [cs.CV]Predictive Ensemble Learning with Application to Scene Text Detection
Danlu Chen, Xu-Yao Zhang, Wei Zhang, Yao Lu, Xiuli Li, Tao Me
http://arxiv.org/abs/1905.04641v1
• [cs.CV]Quantifying and Alleviating the Language Prior Problem in Visual Question Answering
Yangyang Guo, Zhiyong Cheng, Liqiang Nie, Yibing Liu, Yinglong Wang, Mohan Kankanhalli
http://arxiv.org/abs/1905.04877v1
• [cs.CV]Robustness of Object Recognition under Extreme Occlusion in Humans and Computational Models
Hongru Zhu, Peng Tang, Alan Yuille
http://arxiv.org/abs/1905.04598v1
• [cs.CV]Segregation Network for Multi-Class Novelty Detection
Supritam Bhattacharjee, Devraj Mandal, Soma Biswas
http://arxiv.org/abs/1905.04523v1
• [cs.CV]Self-Supervised Visual Place Recognition Learning in Mobile Robots
Sudeep Pillai, John Leonard
http://arxiv.org/abs/1905.04453v1
• [cs.CV]Social Relation Recognition in Egocentric Photostreams
Emanuel Sanchez Aimar, Petia Radeva, Mariella Dimiccoli
http://arxiv.org/abs/1905.04734v1
• [cs.CV]Some Research Problems in Biometrics: The Future Beckons
Arun Ross, Sudipta Banerjee, Cunjian Chen, Anurag Chowdhury, Vahid Mirjalili, Renu Sharma, Thomas Swearingen, Shivangi Yadav
http://arxiv.org/abs/1905.04717v1
• [cs.CV]Structure from Articulated Motion: An Accurate and Stable Monocular 3D Reconstruction Approach without Training Data
Onorina Kovalenko, Vladislav Golyanik, Jameel Malik, Ahmed Elhayek, Didier Stricker
http://arxiv.org/abs/1905.04789v1
• [cs.CV]Structured Discriminative Tensor Dictionary Learning for Unsupervised Domain Adaptation
Songsong Wu, Yan Yan, Hao Tang, Jianjun Qian, Jian Zhang, Xiao-Yuan Jing
http://arxiv.org/abs/1905.04424v1
• [cs.CV]Triplet Distillation for Deep Face Recognition
Yushu Feng, Huan Wang, Roland Hu, Daniel T. Yi
http://arxiv.org/abs/1905.04457v1
• [cs.CV]Unified Generator-Classifier for Efficient Zero-Shot Learning
Ayyappa Kumar Pambala, Titir Dutta, Soma Biswas
http://arxiv.org/abs/1905.04511v1
• [cs.CV]Video Instance Segmentation
Linjie Yang, Yuchen Fan, Ning Xu
http://arxiv.org/abs/1905.04804v1
• [cs.CV]VideoGraph: Recognizing Minutes-Long Human Activities in Videos
Noureldien Hussein, Efstratios Gavves, Arnold W. M. Smeulders
http://arxiv.org/abs/1905.05143v1
• [cs.CV]Weakly-supervised Caricature Face Parsing through Domain Adaptation
Wenqing Chu, Wei-Chih Hung, Yi-Hsuan Tsai, Deng Cai, Ming-Hsuan Yang
http://arxiv.org/abs/1905.05091v1
• [cs.CV]Zoom To Learn, Learn To Zoom
Xuaner Cecilia Zhang, Qifeng Chen, Ren Ng, Vladlen Koltun
http://arxiv.org/abs/1905.05169v1
• [cs.CY]A resource-based rule engine for energy savings recommendations in educational buildings
Giovanni Cuffaro, Federica Paganelli, Georgios Mylonas
http://arxiv.org/abs/1905.05015v1
• [cs.CY]Enhancing Trust in eAssessment - the TeSLA System Solution
Malinka Ivanova, Sushil Bhattacharjee, Sebastien Marcel, Anna Rozeva, Mariana Durcheva
http://arxiv.org/abs/1905.04985v1
• [cs.CY]Lie on the Fly: Strategic Voting in an Iterative Preference Elicitation Process
Lihi Dery, Svetlana Obraztsova, Zinovi Rabinovich, Meir Kalech
http://arxiv.org/abs/1905.04933v1
• [cs.DB]NFTracer: A Non-Fungible Token Tracking Proof-of-Concept Using Hyperledger Fabric
Mustafa Bal, Caitlin Ner
http://arxiv.org/abs/1905.04795v1
• [cs.DC]A Distributed Laplacian Solver and its Applications to Electrical Flow and Random Spanning Tree Computation
Iqra Altaf Gillani, Amitabha Bagchi
http://arxiv.org/abs/1905.04989v1
• [cs.DC]A new SSO-based Algorithm for the Bi-Objective Time-constrained task Scheduling Problem in Cloud Computing Services
Chia-Ling Huang, Wei-Chang Yeh
http://arxiv.org/abs/1905.04855v1
• [cs.DC]Analysis of Committee Selection Mechanism in Blockchain
Shiyu Cai
http://arxiv.org/abs/1905.05079v1
• [cs.DC]Analysis of Global Fixed-Priority Scheduling for Generalized Sporadic DAG Tasks
Son Dinh, Christopher Gill, Kunal Agrawal
http://arxiv.org/abs/1905.05119v1
• [cs.DC]Energy-Aware Scheduling of Task Graphs with Imprecise Computations and End-to-End Deadlines
Amirhossein Esmaili, Mahdi Nazemi, Massoud Pedram
http://arxiv.org/abs/1905.04391v1
• [cs.DC]F-FDN: Federation of Fog Computing Systems for Low Latency Video Streaming
Vaughan Veillon, Chavit Denninnart, Mohsen Amini Salehi
http://arxiv.org/abs/1905.04459v1
• [cs.DC]Improving Robustness of Heterogeneous Serverless Computing Systems Via Probabilistic Task Pruning
Chavit Denninnart, James Gentry, Mohsen Amini Salehi
http://arxiv.org/abs/1905.04456v1
• [cs.DC]Introduction to StarNEig — A Task-based Library for Solving Nonsymmetric Eigenvalue Problems
Mirko Myllykoski, Carl Christian Kjelgaard Mikkelsen
http://arxiv.org/abs/1905.04975v1
• [cs.DC]K-Athena: a performance portable structured grid finite volume magnetohydrodynamics code
Philipp Grete, Forrest W. Glines, Brian W. O’Shea
http://arxiv.org/abs/1905.04341v1
• [cs.DC]NeuPart: Using Analytical Models to Drive Energy-Efficient Partitioning of CNN Computations on Cloud-Connected Mobile Clients
Susmita Dey Manasi, Farhana Sharmin Snigdha, Sachin S. Sapatnekar
http://arxiv.org/abs/1905.05011v1
• [cs.DC]ONLAY: Online Layering for scalable asynchronous BFT system
Quan Nguyen, Andre Cronje
http://arxiv.org/abs/1905.04867v1
• [cs.DC]Quantitative Analysis of Cloud Function Evolution in the AWS Serverless Application Repository
Josef Spillner
http://arxiv.org/abs/1905.04800v1
• [cs.DC]Robust Resource Allocation Using Edge Computing for Vehicle to Infrastructure (V2I) Networks
Anna Kovalenko, Razin Farhan Hussain, Omid Semiari, Mohsen Amini Salehi
http://arxiv.org/abs/1905.04458v1
• [cs.DC]Serverless Edge Computing for Green Oil and Gas Industry
Razin Farhan Hussain, Mohsen Amini Salehi, Omid Semiari
http://arxiv.org/abs/1905.04460v1
• [cs.DS]PrivateJobMatch: A Privacy-Oriented Deferred Multi-Match Recommender System for Stable Employment
Amar Saini
http://arxiv.org/abs/1905.04564v1
• [cs.DS]Solving Empirical Risk Minimization in the Current Matrix Multiplication Time
Yin Tat Lee, Zhao Song, Qiuyi Zhang
http://arxiv.org/abs/1905.04447v1
• [cs.GT]Exogenous Rewards for Promoting Cooperation in Scale-Free Networks
Theodor Cimpeanu, The Anh Han, Francisco C. Santos
http://arxiv.org/abs/1905.04964v1
• [cs.IR]Data description and retrieval using periods represented by uncertain time intervals
Tatsuki Sekino
http://arxiv.org/abs/1905.04611v1
• [cs.IR]Deep Landscape Forecasting for Real-time Bidding Advertising
Kan Ren, Jiarui Qin, Lei Zheng, Zhengyu Yang, Weinan Zhang, Yong Yu
http://arxiv.org/abs/1905.03028v2
• [cs.IR]Hadamard Matrix Guided Online Hashing
Mingbao Lin, Rongrong Ji, Hong Liu, Xiaoshuai Sun, Shen Chen, Qi Tian
http://arxiv.org/abs/1905.04454v1
• [cs.IR]Information search in a professional context - exploring a collection of professional search tasks
Suzan Verberne, Jiyin He, Gineke Wiggers, Tony Russell-Rose, Udo Kruschwitz, Arjen P. de Vries
http://arxiv.org/abs/1905.04577v1
• [cs.IT]Construction of three classes of Strictly Optimal Frequency-Hopping Sequence Sets
Yi Ouyang, Xianhong Xie, Honggang Hu, Ming Mao
http://arxiv.org/abs/1905.04940v1
• [cs.IT]Hessian transport Gradient flows
Wuchen Li, Lexing Ying
http://arxiv.org/abs/1905.04556v1
• [cs.IT]Radio Map Based Path Planning for Cellular-Connected UAV
Shuowen Zhang, Rui Zhang
http://arxiv.org/abs/1905.05046v1
• [cs.IT]Secure Hybrid Digital and Analog Precoder for mmWave Systems with low-resolution DACs and finite-quantized phase shifters
Ling Xu, Feng Shu, Guiyang Xia, Yijin Zhang, Zhihong Zhuang, Jiangzhou Wang
http://arxiv.org/abs/1905.04837v1
• [cs.IT]Sparse Optimization Problem with s-difference Regularization
Yuli Sun, Xiang Tan, Xiao Li, Lin Lei, Gangyao Kuang
http://arxiv.org/abs/1905.04474v1
• [cs.IT]Structured Mappings and Conferencing Common Information for Multiple-access Channels
Mohsen Heidari, S. Sandeep Pradhan
http://arxiv.org/abs/1905.04760v1
• [cs.IT]Ultra-small Cell Networks with Collaborative RF and Lightwave Power Transfer
Ha-Vu Tran, Georges Kaddoum, Panagiotis D. Diamantoulakis, Chadi Abou-Rjeily, George K. Karagiannidis
http://arxiv.org/abs/1905.04738v1
• [cs.LG]A New Look at an Old Problem: A Universal Learning Approach to Linear Regression
Koby Bibas, Yaniv Fogel, Meir Feder
http://arxiv.org/abs/1905.04708v1
• [cs.LG]Accuracy Improvement of Neural Network Training using Particle Swarm Optimization and its Stability Analysis for Classification
Arijit Nandi, Nanda Dulal Jana
http://arxiv.org/abs/1905.04522v1
• [cs.LG]Approximated Oracle Filter Pruning for Destructive CNN Width Optimization
Xiaohan Ding, Guiguang Ding, Yuchen Guo, Jungong Han, Chenggang Yan
http://arxiv.org/abs/1905.04748v1
• [cs.LG]BayesNAS: A Bayesian Approach for Neural Architecture Search
Hongpeng Zhou, Minghao Yang, Jun Wang, Wei Pan
http://arxiv.org/abs/1905.04919v1
• [cs.LG]Boosting Generative Models by Leveraging Cascaded Meta-Models
Fan Bao, Hang Su, Jun Zhu
http://arxiv.org/abs/1905.04534v1
• [cs.LG]CASTNet: Community-Attentive Spatio-Temporal Networks for Opioid Overdose Forecasting
Ali Mert Ertugrul, Yu-Ru Lin, Tugba Taskaya-Temizel
http://arxiv.org/abs/1905.04714v1
• [cs.LG]Diagnosing Reinforcement Learning for Traffic Signal Control
Guanjie Zheng, Xinshi Zang, Nan Xu, Hua Wei, Zhengyao Yu, Vikash Gayah, Kai Xu, Zhenhui Li
http://arxiv.org/abs/1905.04716v1
• [cs.LG]Differentiable Game Mechanics
Alistair Letcher, David Balduzzi, Sebastien Racaniere, James Martens, Jakob Foerster, Karl Tuyls, Thore Graepel
http://arxiv.org/abs/1905.04926v1
• [cs.LG]Differentially Private Empirical Risk Minimization with Sparsity-Inducing Norms
K S Sesh Kumar, Marc Peter Deisenroth
http://arxiv.org/abs/1905.04873v1
• [cs.LG]Dissecting Graph Neural Networks on Graph Classification
Ting Chen, Song Bian, Yizhou Sun
http://arxiv.org/abs/1905.04579v1
• [cs.LG]Explainable AI for Trees: From Local Explanations to Global Understanding
Scott M. Lundberg, Gabriel Erion, Hugh Chen, Alex DeGrave, Jordan M. Prutkin, Bala Nair, Ronit Katz, Jonathan Himmelfarb, Nisha Bansal, Su-In Lee
http://arxiv.org/abs/1905.04610v1
• [cs.LG]Federated Multi-task Hierarchical Attention Model for Sensor Analytics
Yujing Chen, Yue Ning, Zheng Chai, Huzefa Rangwala
http://arxiv.org/abs/1905.05142v1
• [cs.LG]Few-Shot Learning with Embedded Class Models and Shot-Free Meta Training
Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
http://arxiv.org/abs/1905.04398v1
• [cs.LG]Flat Metric Minimization with Applications in Generative Modeling
Thomas Möllenhoff, Daniel Cremers
http://arxiv.org/abs/1905.04730v1
• [cs.LG]Hierarchical Importance Weighted Autoencoders
Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane, Alexandre Lacoste, Aaron Courville
http://arxiv.org/abs/1905.04866v1
• [cs.LG]ISBNet: Instance-aware Selective Branching Network
Shaofeng Cai, Yao Shu, Wei Wang, Beng Chin Ooi
http://arxiv.org/abs/1905.04849v1
• [cs.LG]Implicit Filter Sparsification In Convolutional Neural Networks
Dushyant Mehta, Kwang In Kim, Christian Theobalt
http://arxiv.org/abs/1905.04967v1
• [cs.LG]Interpret Federated Learning with Shapley Values
Guan Wang
http://arxiv.org/abs/1905.04519v1
• [cs.LG]Knowledge Graph Convolutional Networks for Recommender Systems with Label Smoothness Regularization
Hongwei Wang, Fuzheng Zhang, Mengdi Zhang, Jure Leskovec, Miao Zhao, Wenjie Li, Zhongyuan Wang
http://arxiv.org/abs/1905.04413v1
• [cs.LG]Learning Phase Competition for Traffic Signal Control
Guanjie Zheng, Yuanhao Xiong, Xinshi Zang, Jie Feng, Hua Wei, Huichu Zhang, Yong Li, Kai Xu, Zhenhui Li
http://arxiv.org/abs/1905.04722v1
• [cs.LG]Learning in structured MDPs with convex cost functions: Improved regret bounds for inventory management
Shipra Agrawal, Randy Jia
http://arxiv.org/abs/1905.04337v1
• [cs.LG]Learning to Convolve: A Generalized Weight-Tying Approach
Nichita Diaconu, Daniel E Worrall
http://arxiv.org/abs/1905.04663v1
• [cs.LG]Machine learning in cardiovascular flows modeling: Predicting pulse wave propagation from non-invasive clinical measurements using physics-informed deep learning
Georgios Kissas, Yibo Yang, Eileen Hwuang, Walter R. Witschey, John A. Detre, Paris Perdikaris
http://arxiv.org/abs/1905.04817v1
• [cs.LG]Multi-Agent Image Classification via Reinforcement Learning
Hossein K. Mousavi, Mohammadreza Nazari, Martin Takáč, Nader Motee
http://arxiv.org/abs/1905.04835v1
• [cs.LG]Multi-Pass Q-Networks for Deep Reinforcement Learning with Parameterised Action Spaces
Craig J. Bester, Steven D. James, George D. Konidaris
http://arxiv.org/abs/1905.04388v1
• [cs.LG]Multi-View Multi-Instance Multi-Label Learning based on Collaborative Matrix Factorization
Yuying Xing, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Zili Zhang, Maozu Guo
http://arxiv.org/abs/1905.05061v1
• [cs.LG]Multi-View Multiple Clustering
Shixing Yao, Guoxian Yu, Jun Wang, Carlotta Domeniconi, Xiangliang Zhang
http://arxiv.org/abs/1905.05053v1
• [cs.LG]On Graph Classification Networks, Datasets and Baselines
Enxhell Luzhnica, Ben Day, Pietro Liò
http://arxiv.org/abs/1905.04682v1
• [cs.LG]Ranking-based Deep Cross-modal Hashing
Xuanwu Liu, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Yazhou Ren, Maozu Guo
http://arxiv.org/abs/1905.04450v1
• [cs.LG]Robust Learning from Noisy Side-information by Semidefinite Programming
En-Liang Hu, Quanming Yao
http://arxiv.org/abs/1905.04629v1
• [cs.LG]Solving Irregular and Data-enriched Differential Equations using Deep Neural Networks
Craig Michoski, Milos Milosavljevic, Todd Oliver, David Hatch
http://arxiv.org/abs/1905.04351v1
• [cs.LG]Spectral Analysis of Kernel and Neural Embeddings: Optimization and Generalization
Emilio Jorge, Morteza Haghir Chehreghani, Devdatt Dubhashi
http://arxiv.org/abs/1905.05095v1
• [cs.LG]Stability Properties of Graph Neural Networks
Fernando Gama, Joan Bruna, Alejandro Ribeiro
http://arxiv.org/abs/1905.04497v1
• [cs.LG]Tabular Benchmarks for Joint Architecture and Hyperparameter Optimization
Aaron Klein, Frank Hutter
http://arxiv.org/abs/1905.04970v1
• [cs.LG]Task-Agnostic Dynamics Priors for Deep Reinforcement Learning
Yilun Du, Karthik Narasimhan
http://arxiv.org/abs/1905.04819v1
• [cs.LG]Theoretical Limits of One-Shot Distributed Learning
Saber Salehkaleybar, Arsalan Sharifnassab, S. Jamaloddin Golestani
http://arxiv.org/abs/1905.04634v1
• [cs.LG]Towards a regularity theory for ReLU networks — chain rule and global error estimates
Julius Berner, Dennis Elbrächter, Philipp Grohs, Arnulf Jentzen
http://arxiv.org/abs/1905.04992v1
• [cs.LG]Training CNNs with Selective Allocation of Channels
Jongheon Jeong, Jinwoo Shin
http://arxiv.org/abs/1905.04509v1
• [cs.LG]Tree-wise Distribution Sensitive hashing: Efficient Maximum likelihood Classification by joint dimensionality reduction in known probabilistic settings
Arash Gholami Davoodi, Anubhav Baweja, Hosein Mohimani
http://arxiv.org/abs/1905.04559v1
• [cs.LG]Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
Pengfei Chen, Benben Liao, Guangyong Chen, Shengyu Zhang
http://arxiv.org/abs/1905.05040v1
• [cs.LG]Universal Invariant and Equivariant Graph Neural Networks
Nicolas Keriven, Gabriel Peyré
http://arxiv.org/abs/1905.04943v1
• [cs.LG]What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use
Sana Tonekaboni, Shalmali Joshi, Melissa D McCradden, Anna Goldenberg
http://arxiv.org/abs/1905.05134v1
• [cs.LO]Rough Contact in General Rough Mereology
A. Mani
http://arxiv.org/abs/1905.04689v1
• [cs.MA]Evidence Propagation and Consensus Formation in Noisy Environments
Michael Crosscombe, Jonathan Lawry
http://arxiv.org/abs/1905.04840v1
• [cs.MA]Physically-interpretable classification of network dynamics for complex collective motions
Keisuke Fujii, Naoya Takeishi, Motokazu Hojo, Yuki Inaba, Yoshinobu Kawahara
http://arxiv.org/abs/1905.04859v1
• [cs.MM]Deep Vocoder: Low Bit Rate Speech Compression of Speech with Deep Autoencoder
Gang Min, Changqing Zhang, Xiongwei Zhang, Wei Tan
http://arxiv.org/abs/1905.04709v1
• [cs.NE]A Stock Selection Method Based on Earning Yield Forecast Using Sequence Prediction Models
Jessie Sun
http://arxiv.org/abs/1905.04842v1
• [cs.NE]Deep Learning: a new definition of artificial neuron with double weight
Adriano Baldeschi, Raffaella Margutti, Adam Miller
http://arxiv.org/abs/1905.04545v1
• [cs.NE]Enabling Explainable Fusion in Deep Learning with Fuzzy Integral Neural Networks
Muhammad Aminul Islam, Derek T. Anderson, Anthony J. Pinar, Timothy C. Havens, Grant Scott, James M. Keller
http://arxiv.org/abs/1905.04394v1
• [cs.NI]Analyzing Adversarial Attacks Against Deep Learning for Intrusion Detection in IoT Networks
Olakunle Ibitoye, Omair Shafiq, Ashraf Matrawy
http://arxiv.org/abs/1905.05137v1
• [cs.RO]AMZ Driverless: The Full Autonomous Racing System
Juraj Kabzan, Miguel de la Iglesia Valls, Victor Reijgwart, Hubertus Franciscus Cornelis Hendrikx, Claas Ehmke, Manish Prajapat, Andreas Bühler, Nikhil Gosala, Mehak Gupta, Ramya Sivanesan, Ankit Dhall, Eugenio Chisari, Napat Karnchanachari, Sonja Brits, Manuel Dangel, Inkyu Sa, Renaud Dubé, Abel Gawel, Mark Pfeiffer, Alexander Liniger, John Lygeros, Roland Siegwart
http://arxiv.org/abs/1905.05150v1
• [cs.RO]Automatic Calibration of Multiple 3D LiDARs in Urban Environments
Jianhao Jiao, Yang Yu, Qinghai Liao, Haoyang Ye, Ming Liu
http://arxiv.org/abs/1905.04912v1
• [cs.RO]Ceiling Effects for Hybrid Aerial-Surface Locomotion of Small Rotorcraft
Yi Hsuan Hsiao, Pakpong Chirarattananon
http://arxiv.org/abs/1905.04632v1
• [cs.RO]Decentralized Impedance Control for Cooperative Manipulation of Multiple Underwater Vehicle Manipulator Systems under Lean Communication
Shahab Heshmati-alamdari, Charalampos P. Bechlioulis, George C. Karras, Kostas J. Kyriakopoulos
http://arxiv.org/abs/1905.04531v1
• [cs.RO]Extending Policy from One-Shot Learning through Coaching
Mythra V. Balakuntala, Vishnunandan L. N. Venkatesh, Jyothsna Padmakumar Bindu, Richard M. Voyles, Juan Wachs
http://arxiv.org/abs/1905.04841v1
• [cs.RO]Failure-Tolerant Connectivity Maintenance for Robot Swarms
Vivek Shankar Varadharajan, Bram Adams, Giovanni Beltrame
http://arxiv.org/abs/1905.04771v1
• [cs.RO]Integrating Objects into Monocular SLAM: Line Based Category Specific Models
Nayan Joshi, Yogesh Sharma, Parv Parkhiya, Rishabh Khawad, K Madhava Krishna, Brojeshwar Bhowmick
http://arxiv.org/abs/1905.04698v1
• [cs.RO]Let’s Push Things Forward: A Survey on Robot Pushing
Jochen Stüber, Claudio Zito, Rustam Stolkin
http://arxiv.org/abs/1905.05138v1
• [cs.RO]Locally Weighted Regression Pseudo-Rehearsal for Online Learning of Vehicle Dynamics
Grady Williams, Brian Goldfain, James M. Rehg, Evangelos A. Theodorou
http://arxiv.org/abs/1905.05162v1
• [cs.RO]Occlusion-Robust MVO: Multimotion Estimation Through Occlusion Via Motion Closure
Kevin M. Judd, Jonathan D. Gammell
http://arxiv.org/abs/1905.05121v1
• [cs.RO]Real-Time Kinodynamic Motion Planning for Omnidirectional Mobile Robot Soccer using Rapidly-Exploring Random Tree in Dynamic Environment with Moving Obstacles
Fahri Ali Rahman, Igi Ardiyanto, Adha Imam Cahyadi
http://arxiv.org/abs/1905.04762v1
• [cs.SD]Time-Contrastive Learning Based Deep Bottleneck Features for Text-Dependent Speaker Verification
Achintya kr. Sarkar, Zheng-Hua Tan, Hao Tang, Suwon Shon, James Glass
http://arxiv.org/abs/1905.04554v1
• [cs.SE]Automating chaos experiments in production
Ali Basiri, Lorin Hochstein, Nora Jones, Haley Tucker
http://arxiv.org/abs/1905.04648v1
• [cs.SI]Election Control with Voters’ Uncertainty: Hardness and Approximation Results
Mohammad Aboueimehrizi, Federico Corò, Emilio Cruciani, Gianlorenzo D’Angelo
http://arxiv.org/abs/1905.04694v1
• [cs.SI]Influencing Opinions of Heterogeneous Populations over Finite Time Horizons
Arunabh Saxena, Bhumesh Kumar, Neeraja Sahasrabudhe, Sharayu Moharir
http://arxiv.org/abs/1905.04448v1
• [cs.SI]Language in Our Time: An Empirical Analysis of Hashtags
Yang Zhang
http://arxiv.org/abs/1905.04590v1
• [cs.SI]Mining Hidden Populations through Attributed Search
Suhansanu Kumar, Heting Gao, Changyu Wang, Hari Sundaram, Kevin Chen-Chuan Chang
http://arxiv.org/abs/1905.04505v1
• [cs.SI]Seeding with Costly Network Information
Dean Eckles, Hossein Esfandiari, Elchanan Mossel, M. Amin Rahimian
http://arxiv.org/abs/1905.04325v1
• [cs.SI]The Secret Lives of Names? Name Embeddings from Social Media
Junting Ye, Steven Skiena
http://arxiv.org/abs/1905.04799v1
• [eess.IV]A Cone-Beam X-Ray CT Data Collection Designed for Machine Learning
Henri Der Sarkissian, Felix Lucka, Maureen van Eijnatten, Giulia Colacicco, Sophia Bethany Coban, Kees Joost Batenburg
http://arxiv.org/abs/1905.04787v1
• [eess.IV]Generative Adversarial Networks and Conditional Random Fields for Hyperspectral Image Classification
Zilong Zhong, Jonathan Li, David A. Clausi, Alexander Wong
http://arxiv.org/abs/1905.04621v1
• [eess.IV]Generative Modeling and Inverse Imaging of Cardiac Transmembrane Potential
Sandesh Ghimire, Jwala Dhamala, Prashnna Kumar Gyawali, John L Sapp, B. Milan Horacek, Linwei Wang
http://arxiv.org/abs/1905.04803v1
• [eess.IV]Programmable Spectrometry — Per-pixel Classification of Materials using Learned Spectral Filters
Vishwanath Saragadam, Aswin C. Sankaranarayanan
http://arxiv.org/abs/1905.04815v1
• [eess.SP]Adversarial Examples for Electrocardiograms
Xintian Han, Yuxuan Hu, Luca Foschini, Larry Chinitz, Lior Jankelson, Rajesh Ranganath
http://arxiv.org/abs/1905.05163v1
• [eess.SP]ECG Identification under Exercise and Rest Situations via Various Learning Methods
Zihan Wang, Yaoguang Li, Wei Cui
http://arxiv.org/abs/1905.04442v1
• [eess.SP]Interference Mitigation and Resource Allocation in Underlay Cognitive Radio Networks
Shailesh Chaudhari
http://arxiv.org/abs/1905.04572v1
• [eess.SP]Large-Scale Spectrum Occupancy Learning via Tensor Decomposition and LSTM Networks
Mohsen Joneidi, Ismail Alkhouri, Nazanin Rahnavard
http://arxiv.org/abs/1905.04392v1
• [eess.SP]Low Noise Non-Linear Equalization Using Neural Networks and Belief Propagation
Etsushi Yamazaki, Nariman Farsad, Andrea Goldsmith
http://arxiv.org/abs/1905.04893v1
• [eess.SP]Massive MIMO Extensions to the COST 2100 Channel Model: Modeling and Validation
Jose Flordelis, Xuhong Li, Ove Edfors, Fredrik Tufvesson
http://arxiv.org/abs/1905.04931v1
• [eess.SP]Sparse Recovery Beyond Compressed Sensing: Separable Nonlinear Inverse Problems
Brett Bernstein, Sheng Liu, Chrysa Papadaniil, Carlos Fernandez-Granda
http://arxiv.org/abs/1905.04627v1
• [eess.SP]Terahertz-Band Ultra-Massive Spatial Modulation MIMO
Hadi Sarieddeen, Mohamed-Slim Alouini, Tareq Y. Al-Naffouri
http://arxiv.org/abs/1905.04732v1
• [math.OC]Channels, Learning, Queueing and Remote Estimation Systems With A Utilization-Dependent Component
Varun Jog, Richard J. La, Nuno C. Martins
http://arxiv.org/abs/1905.04362v1
• [math.ST]ACF estimation via difference schemes for a semiparametric model with $m$-dependent errors
Michael Levine, Inder Tecuapetla-Gomez
http://arxiv.org/abs/1905.04578v1
• [math.ST]Hyperparameter Estimation in Bayesian MAP Estimation: Parameterizations and Consistency
Matthew M. Dunlop, Tapio Helin, Andrew M. Stuart
http://arxiv.org/abs/1905.04365v1
• [math.ST]Is Volatility Rough ?
Masaaki Fukasawa, Tetsuya Takabatake, Rebecca Westphal
http://arxiv.org/abs/1905.04852v1
• [math.ST]Moment Identifiability of Homoscedastic Gaussian Mixtures
Daniele Agostini, Carlos Améndola, Kristian Ranestad
http://arxiv.org/abs/1905.05141v1
• [math.ST]Sub-Weibull distributions: generalizing sub-Gaussian and sub-Exponential properties to heavier-tailed distributions
Mariia Vladimirova, Julyan Arbel
http://arxiv.org/abs/1905.04955v1
• [physics.data-an]A class of randomized Subset Selection Methods for large complex networks
Amit Reza, Richa Tripathi
http://arxiv.org/abs/1905.04452v1
• [physics.soc-ph]Emergence of an Onion-like Network in Surface Growth and Its Strong Robustness
Yukio Hayashi, Yuki Tanaka
http://arxiv.org/abs/1905.04812v1
• [stat.AP]Modeling failures times with dependent renewal type models via exchangeability
Arrigo Coen, Luis Gutiérrez, Ramsés H. Mena
http://arxiv.org/abs/1905.05145v1
• [stat.AP]Partially Specified Space Time Autoregressive Model with Artificial Neural Network
Wenqian Wang, Beth Andrews
http://arxiv.org/abs/1905.05074v1
• [stat.AP]Partisan Lean of States: Electoral College and Popular Vote
Andrey Sarantsev
http://arxiv.org/abs/1905.04444v1
• [stat.AP]Time delay estimation in satellite imagery time series of precipitation and NDVI: Pearson’s cross correlation revisited
Inder Tecuapetla-Gómez
http://arxiv.org/abs/1905.04606v1
• [stat.AP]Urban greenery and mental wellbeing in adults: Cross-sectional mediation analyses on multiple pathways across different greenery measures
Ruoyu Wang, Marco Helbich, Yao Yao, Jinbao Zhang, Penghua Liu, Yuan Yuana, Ye Liu
http://arxiv.org/abs/1905.04488v1
• [stat.CO]The compound product distribution; a solution to the distributional equation X=AX+1
Arrigo Coen
http://arxiv.org/abs/1905.04758v1
• [stat.ME]A Spatial Concordance Correlation Coefficient with an Application to Image Analysis
Ronny Vallejos, Javier Pérez, Aaron M. Ellison, Andrew D. Richardson
http://arxiv.org/abs/1905.05016v1
• [stat.ME]Asymmetric tail dependence modeling, with application to cryptocurrency market data
Yan Gong, Raphael Huser
http://arxiv.org/abs/1905.05056v1
• [stat.ME]Note on Thompson sampling for large decision problems
Tao Hu, Eric B. Laber, Zhen Li, Nick J. Meyer, Krishna Pacifici
http://arxiv.org/abs/1905.04735v1
• [stat.ME]Prediction and outlier detection: a distribution-free prediction set with a balanced objective
Leying Guan, Rob Tibshirani
http://arxiv.org/abs/1905.04396v1
• [stat.ME]Statistical inference with anchored Bayesian mixture of regressions models: A case study analysis of allometric data
Deborah Kunkel, Mario Peruggia
http://arxiv.org/abs/1905.04389v1
• [stat.ME]Structural Equation Modeling using Computation Graphs
Erik-Jan van Kesteren, Daniel L. Oberski
http://arxiv.org/abs/1905.04492v1
• [stat.ML]Active Embedding Search via Noisy Paired Comparisons
Gregory H. Canal, Andrew K. Massimino, Mark A. Davenport, Christopher J. Rozell
http://arxiv.org/abs/1905.04363v1
• [stat.ML]Bayesian Hierarchical Mixture Clustering using Multilevel Hierarchical Dirichlet Processes
Weipeng Huang, Nishma Laitonjam, Guangyuan Piao, Neil Hurley
http://arxiv.org/abs/1905.05022v1
• [stat.ML]Exact high-dimensional asymptotics for support vector machine
Haoyang Liu
http://arxiv.org/abs/1905.05125v1
• [stat.ML]Functional Correlations in the Pursuit of Performance Assessment of Classifiers
Nadezhda Gribkova, Ričardas Zitikis
http://arxiv.org/abs/1905.04667v1
• [stat.ML]Learning Hierarchical Priors in VAEs
Alexej Klushyn, Nutan Chen, Richard Kurle, Botond Cseke, Patrick van der Smagt
http://arxiv.org/abs/1905.04982v1
• [stat.ML]Learning to Search Efficiently Using Comparisons
Daniyar Chumbalov, Lucas Maystre, Matthias Grossglauser
http://arxiv.org/abs/1905.05049v1
• [stat.ML]On the Performance of Thompson Sampling on Logistic Bandits
Shi Dong, Tengyu Ma, Benjamin Van Roy
http://arxiv.org/abs/1905.04654v1
• [stat.ML]Rotation Invariant Householder Parameterization for Bayesian PCA
Rajbir S. Nirwan, Nils Bertschinger
http://arxiv.org/abs/1905.04720v1
• [stat.ML]Variational inference for neural network matrix factorization and its application to stochastic blockmodeling
Onno Kampman, Creighton Heaukulani
http://arxiv.org/abs/1905.04502v1
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