astro-ph.IM - 仪器仪表和天体物理学方法
cs.AI - 人工智能
cs.AR - 硬件体系结构
cs.CC - 计算复杂度
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.HC - 人机接口
cs.IR - 信息检索
cs.IT - 信息论
cs.LG - 自动学习
cs.NE - 神经与进化计算
cs.OH - 其他CS
cs.RO - 机器人学
cs.SC - 符号计算
cs.SD - 声音处理
cs.SI - 社交网络与信息网络
cs.SY - 系统与控制
eess.AS - 语音处理
eess.SP - 信号处理
math.CO - 组合数学
math.NA - 数值分析
math.OC - 优化与控制
math.PR - 概率
math.ST - 统计理论
physics.soc-ph - 物理学与社会
q-bio.PE - 人口与发展
quant-ph - 量子物理
stat.AP - 应用统计
stat.ME - 统计方法论
stat.ML - (统计)机器学习
• [astro-ph.IM]Application of Google Cloud Platform in Astrophysics
• [cs.AI]Dynamic Demand Prediction for Expanding Electric Vehicle Sharing Systems: A Graph Sequence Learning Approach
• [cs.AI]From Low-Level Events to Activities -- A Session-Based Approach (Extended Version)
• [cs.AI]Improving Humanness of Virtual Agents and Users' Cooperation through Emotions
• [cs.AI]Learning Self-Game-Play Agents for Combinatorial Optimization Problems
• [cs.AI]Literal or Pedagogic Human? Analyzing Human Model Misspecification in Objective Learning
• [cs.AI]Logic Rules Powered Knowledge Graph Embedding
• [cs.AI]Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Autonomous Robots
• [cs.AI]Physics Enhanced Artificial Intelligence
• [cs.AI]Program Classification Using Gated Graph Attention Neural Network for Online Programming Service
• [cs.AI]Reachability and Coverage Planning for Connected Agents: Extended Version
• [cs.AI]Rethinking System Health Management
• [cs.AR]Automated Circuit Approximation Method Driven by Data Distribution
• [cs.CC]Knowledge compilation languages as proof systems
• [cs.CE]A Decision Support System for Multi-target Geosteering
• [cs.CL]An Innovative Word Encoding Method For Text Classification Using Convolutional Neural Network
• [cs.CL]Contextualised concept embedding for efficiently adapting natural language processing models for phenotype identification
• [cs.CL]ETNLP: A Toolkit for Extraction, Evaluation and Visualization of Pre-trained Word Embeddings
• [cs.CL]HLT@SUDA at SemEval 2019 Task 1: UCCA Graph Parsing as Constituent Tree Parsing
• [cs.CL]Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
• [cs.CL]Named Entity Recognition for Electronic Health Records: A Comparison of Rule-based and Machine Learning Approaches
• [cs.CL]Partially Shuffling the Training Data to Improve Language Models
• [cs.CL]Toward Fast and Accurate Neural Chinese Word Segmentation with Multi-Criteria Learning
• [cs.CR]Incentives in Ethereum's Hybrid Casper Protocol
• [cs.CV]A Hybrid Framework for Action Recognition in Low-Quality Video Sequences
• [cs.CV]A Hybrid GA-PSO Method for Evolving Architecture and Short Connections of Deep Convolutional Neural Networks
• [cs.CV]A Unified Formulation for Visual Odometry
• [cs.CV]ADS-ME: Anomaly Detection System for Micro-expression Spotting
• [cs.CV]Accuracy Booster: Performance Boosting using Feature Map Re-calibration
• [cs.CV]Automated Segmentation of Knee MRI Using Hierarchical Classifiers and Just Enough Interaction Based Learning: Data from Osteoarthritis Initiative
• [cs.CV]BayesOD: A Bayesian Approach for Uncertainty Estimation in Deep Object Detectors
• [cs.CV]Combining 3D Morphable Models: A Large scale Face-and-Head Model
• [cs.CV]Deep Generative Models: Deterministic Prediction with an Application in Inverse Rendering
• [cs.CV]Deep Reinforcement Learning of Volume-guided Progressive View Inpainting for 3D Point Scene Completion from a Single Depth Image
• [cs.CV]Deep Robust Subjective Visual Property Prediction in Crowdsourcing
• [cs.CV]Distributed deep learning for robust multi-site segmentation of CT imaging after traumatic brain injury
• [cs.CV]Domain Randomization for Active Pose Estimation
• [cs.CV]Fast Single Image Reflection Suppression via Convex Optimization
• [cs.CV]Group-wise Correlation Stereo Network
• [cs.CV]HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs
• [cs.CV]Hierarchy Denoising Recursive Autoencoders for 3D Scene Layout Prediction
• [cs.CV]How Effectively Can Indoor Wireless Positioning Relieve Visual Tracking Pains: A Camera-Rao Bound Viewpoint
• [cs.CV]Image Privacy Prediction Using Deep Neural Networks
• [cs.CV]Instance- and Category-level 6D Object Pose Estimation
• [cs.CV]Investigation on Combining 3D Convolution of Image Data and Optical Flow to Generate Temporal Action Proposals
• [cs.CV]Joint inference on structural and diffusion MRI for sequence-adaptive Bayesian segmentation of thalamic nuclei with probabilistic atlases
• [cs.CV]Just-Enough Interaction Approach to Knee MRI Segmentation: Data from the Osteoarthritis Initiative
• [cs.CV]Learning-Based Cost Functions for 3D and 4D Multi-Surface Multi-Object Segmentation of Knee MRI: Data from the Osteoarthritis Initiative
• [cs.CV]LumiPath - Towards Real-time Physically-based Rendering on Embedded Devices
• [cs.CV]MSFD:Multi-Scale Receptive Field Face Detector
• [cs.CV]MTRNet: A Generic Scene Text Eraser
• [cs.CV]Manifold Mixup improves text recognition with CTC loss
• [cs.CV]Mix and match networks: multi-domain alignment for unpaired image-to-image translation
• [cs.CV]Multiview 2D/3D Rigid Registration via a Point-Of-Interest Network for Tracking and Triangulation (POINT^2)
• [cs.CV]Partial Order Pruning: for Best Speed/Accuracy Trade-off in Neural Architecture Search
• [cs.CV]Pluralistic Image Completion
• [cs.CV]Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge Distillation for Unsupervised Monocular Depth Estimation
• [cs.CV]RoPAD: Robust Presentation Attack Detection through Unsupervised Adversarial Invariance
• [cs.CV]Rolling-Shutter-Aware Differential SfM and Image Rectification
• [cs.CV]SSN: Learning Sparse Switchable Normalization via SparsestMax
• [cs.CV]Shape2Motion: Joint Analysis of Motion Parts and Attributes from 3D Shapes
• [cs.CV]Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation
• [cs.CV]Sparse Representations for Object and Ego-motion Estimation in Dynamic Scenes
• [cs.CV]Spatial-Aware Non-Local Attention for Fashion Landmark Detection
• [cs.CV]Stroke-based Artistic Rendering Agent with Deep Reinforcement Learning
• [cs.CV]Structured Knowledge Distillation for Semantic Segmentation
• [cs.CV]The Past and the Present of the Color Checker Dataset Misuse
• [cs.CV]The Unconstrained Ear Recognition Challenge 2019
• [cs.CV]Video Generation from Single Semantic Label Map
• [cs.CY]A reference architecture for integrating the Industrial Internet of Things in the Industry 4.0
• [cs.CY]Blameworthiness in Multi-Agent Settings
• [cs.CY]Gathering Insights from Teenagers' Hacking Experience with Authentic Cybersecurity Tools
• [cs.CY]Standardisation of cyber risk impact assessment for the Internet of Things (IoT)
• [cs.DB]Graph Data on the Web: extend the pivot, don't reinvent the wheel
• [cs.DB]RESTORE: Automated Regression Testing for Datasets
• [cs.DB]Transparency, Fairness, Data Protection, Neutrality: Data Management Challenges in the Face of New Regulation
• [cs.DC]A GraphBLAS Approach for Subgraph Counting
• [cs.DC]Analyzing GPU Tensor Core Potential for Fast Reductions
• [cs.DC]Asynchronous Federated Optimization
• [cs.DC]Auto-Vectorizing TensorFlow Graphs: Jacobians, Auto-Batching And Beyond
• [cs.DC]Proteus: A Scalable BFT Consesus Protocol for Blockchains
• [cs.DC]Security, Performance and Energy Trade-offs of Hardware-assisted Memory Protection Mechanisms
• [cs.DC]TensorFlow Doing HPC
• [cs.HC]Exploring OpenStreetMap Availability for Driving Environment Understanding
• [cs.IR]A Clustering-Based Combinatorial Approach to Unsupervised Matching of Product Titles
• [cs.IR]A New Approach for Topic Detection using Adaptive Neural Networks
• [cs.IR]Automatic Ontology Learning from Domain-Specific Short Unstructured Text Data
• [cs.IR]Jointly Learning Explainable Rules for Recommendation with Knowledge Graph
• [cs.IR]Mutual Clustering on Comparative Texts via Heterogeneous Information Networks
• [cs.IR]The Web is missing an essential part of infrastructure: an Open Web Index
• [cs.IT]A Low-Complexity Cache-Aided Multi-antenna Content Delivery Scheme
• [cs.IT]A simple bound on the BER of the MAP decoder for massive MIMO systems
• [cs.IT]Clustering-Correcting Codes
• [cs.IT]Hybrid Transceiver Optimization for Multi-Hop Communications
• [cs.IT]Interference Mitigation for Ultrareliable Low-Latency Wireless Communication
• [cs.IT]Molecular Information Delivery in Porous Media
• [cs.IT]Optimizing Information Freshness in Broadcast Network with Unreliable Links and Random Arrivals: An Approximate Index Policy
• [cs.IT]Probability Mass Functions for which Sources have the Maximum Minimum Expected Length
• [cs.IT]Publicness, Privacy and Confidentiality in the Single-Serving Quantum Broadcast Channel
• [cs.IT]Semi-Blind Channel-and-Signal Estimation for Uplink Massive MIMO With Channel Sparsity
• [cs.IT]Strengthened Information-theoretic Bounds on the Generalization Error
• [cs.IT]The parameters of a family of linear codes
• [cs.LG]Accelerating Minibatch Stochastic Gradient Descent using Typicality Sampling
• [cs.LG]Algorithms for an Efficient Tensor Biclustering
• [cs.LG]Based on Graph-VAE Model to Predict Student's Score
• [cs.LG]Continual Learning via Neural Pruning
• [cs.LG]Deep Recurrent Q-Learning vs Deep Q-Learning on a simple Partially Observable Markov Decision Process with Minecraft
• [cs.LG]Deep learning for molecular generation and optimization - a review of the state of the art
• [cs.LG]Fair Logistic Regression: An Adversarial Perspective
• [cs.LG]Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation
• [cs.LG]Fisher-Bures Adversary Graph Convolutional Networks
• [cs.LG]GNN Explainer: A Tool for Post-hoc Explanation of Graph Neural Networks
• [cs.LG]Gradient Descent based Optimization Algorithms for Deep Learning Models Training
• [cs.LG]Hybrid Reinforcement Learning with Expert State Sequences
• [cs.LG]InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction
• [cs.LG]Interpreting and Understanding Graph Convolutional Neural Network using Gradient-based Attribution Methods
• [cs.LG]Labeler-hot Detection of EEG Epileptic Transients
• [cs.LG]Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games
• [cs.LG]Learning Quantum Graphical Models using Constrained Gradient Descent on the Stiefel Manifold
• [cs.LG]Machine Learning Based Prediction and Classification of Computational Jobs in Cloud Computing Centers
• [cs.LG]Multinomial Random Forests: Fill the Gap between Theoretical Consistency and Empirical Soundness
• [cs.LG]Non-Negative Kernel Sparse Coding for the Classification of Motion Data
• [cs.LG]One-Pass Sparsified Gaussian Mixtures
• [cs.LG]Optimal Collusion-Free Teaching
• [cs.LG]Revisiting clustering as matrix factorisation on the Stiefel manifold
• [cs.LG]Robust Influence Maximization for Hyperparametric Models
• [cs.LG]Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics
• [cs.LG]Scaling up deep neural networks: a capacity allocation perspective
• [cs.LG]Scene Memory Transformer for Embodied Agents in Long-Horizon Tasks
• [cs.LG]Similarity Learning via Kernel Preserving Embedding
• [cs.LG]Skew-Fit: State-Covering Self-Supervised Reinforcement Learning
• [cs.LG]SleepNet: Automated Sleep Disorder Detection via Dense Convolutional Neural Network
• [cs.LG]Stochastic Incremental Algorithms for Optimal Transport with SON Regularizer
• [cs.LG]Successive Over Relaxation Q-Learning
• [cs.LG]Two-Hop Walks Indicate PageRank Order
• [cs.NE]A Genetic Programming System with an Epigenetic Mechanism for Traffic Signal Control
• [cs.NE]A Spiking Network for Inference of Relations Trained with Neuromorphic Backpropagation
• [cs.NE]DeepPool: Distributed Model-free Algorithm for Ride-sharing using Deep Reinforcement Learning
• [cs.OH]Pragmatic inference and visual abstraction enable contextual flexibility during visual communication
• [cs.RO]2-Entity RANSAC for robust visual localization in changing environment
• [cs.RO]Adaptive Trajectory Planning and Optimization at Limits of Handling
• [cs.RO]Affordance Learning for End-to-End Visuomotor Robot Control
• [cs.RO]Building an Affordances Map with Interactive Perception
• [cs.RO]Communication constrained cloud-based long-term visual localization in real time
• [cs.RO]Data-Driven Model Predictive Control for Food-Cutting
• [cs.RO]Joint Inference of Kinematic and Force Trajectories with Visuo-Tactile Sensing
• [cs.RO]Locomotion Planning through a Hybrid Bayesian Trajectory Optimization
• [cs.RO]Manipulation by Feel: Touch-Based Control with Deep Predictive Models
• [cs.RO]Object recognition and tracking using Haar-like Features Cascade Classifiers: Application to a quad-rotor UAV
• [cs.RO]Realtime Rooftop Landing Site Identification and Selection in Urban City Simulation
• [cs.RO]Robot kinematic structure classification from time series of visual data
• [cs.SC]Recursive Matrix Algorithms in Commutative Domain for Cluster with Distributed Memory
• [cs.SD]Deep Griffin-Lim Iteration
• [cs.SI]DeepTagRec: A Content-cum-User based Tag Recommendation Framework for Stack Overflow
• [cs.SI]Hashtag Usage in a Geographically-Local Microblogging App
• [cs.SI]Redditors in Recovery: Text Mining Reddit to Investigate Transitions into Drug Addiction
• [cs.SI]Towards a new social laboratory: An experimental study of search through community participation at Burning Man
• [cs.SY]A tractable ellipsoidal approximation for voltage regulation problems
• [eess.AS]Singing voice conversion with non-parallel data
• [eess.SP]Towards Ultra-Reliable Low-Latency Communications: Typical Scenarios, Possible Solutions, and Open Issues
• [math.CO]Equivalence classes of Niho bent functions
• [math.NA]A highly parallel multilevel Newton-Krylov-Schwarz method with subspace-based coarsening and partition-based balancing for the multigroup neutron transport equations on 3D unstructured meshes
• [math.OC]Conformal Symplectic and Relativistic Optimization
• [math.OC]Scalable and Congestion-aware Routing for Autonomous Mobility-on-Demand via Frank-Wolfe Optimization
• [math.PR]Mean Field Analysis of Deep Neural Networks
• [math.PR]Quantitative spectral gap estimate and Wasserstein contraction of simple slice sampling
• [math.ST]Consistency of the maximum likelihood and variational estimators in a dynamic stochastic block model
• [math.ST]Diffusion -means clustering on manifolds: provable exact recovery via semidefinite relaxations
• [math.ST]Extreme events of higher-order Markov chains: hidden tail chains and extremal Yule-Walker equations
• [math.ST]Fitting Tractable Convex Sets to Support Function Evaluations
• [math.ST]Maximum pseudo-likelihood estimation based on estimated residuals in copula semiparametric models
• [physics.soc-ph]Scaling in Words on Twitter
• [q-bio.PE]On the convergence of the maximum likelihood estimator for the transition rate under a 2-state symmetric model
• [quant-ph]Quantifying the magic of quantum channels
• [stat.AP]Better-than-expert detection of early coronary artery occlusion from 12 lead electrocardiograms using deep learning
• [stat.AP]Retailer response to wholesale stockouts
• [stat.AP]Semi-Supervised Non-Parametric Bayesian Modelling of Spatial Proteomics
• [stat.ME]A Potential Outcomes Calculus for Identifying Conditional Path-Specific Effects
• [stat.ME]A synthetic likelihood-based Laplace approximation for efficient design of biological processes
• [stat.ME]Adaptive-to-model hybrid of tests for regressions
• [stat.ME]Confidence Interval for Quantile Ratio of the Dagum Distribution
• [stat.ME]Distributed Feature Screening via Componentwise Debiasing
• [stat.ME]Estimating Individualized Decision Rules with Tail Controls
• [stat.ME]Estimation and Inference for High Dimensional Generalized Linear Models: A Splitting and Smoothing Approach
• [stat.ME]Lasso tuning through the flexible-weighted bootstrap
• [stat.ME]Streamlined Variational Inference for Higher Level Group-Specific Curve Models
• [stat.ME]The Shortest Confidence Interval for the Ratio of Quantiles of the Dagum Distribution
• [stat.ME]Transporting stochastic direct and indirect effects to new populations
• [stat.ME]Two paradoxical results in linear models: the variance inflation factor and the analysis of covariance
• [stat.ML]-IRT: A New Item Response Model and its Applications
• [stat.ML]A cross-center smoothness prior for variational Bayesian brain tissue segmentation
• [stat.ML]Bayesian Allocation Model: Inference by Sequential Monte Carlo for Nonnegative Tensor Factorizations and Topic Models using Polya Urns
• [stat.ML]Functional Principal Component Analysis for Extrapolating Multi-stream Longitudinal Data
• [stat.ML]Interpolation Consistency Training for Semi-Supervised Learning
• [stat.ML]Likelihood-free MCMC with Approximate Likelihood Ratios
• [stat.ML]Manifold Preserving Adversarial Learning
• [stat.ML]Orthogonal Estimation of Wasserstein Distances
• [stat.ML]Rectangular Bounding Process
• [stat.ML]Shapley regressions: A framework for statistical inference on machine learning models
• [stat.ML]Sparse Grouped Gaussian Processes for Solar Power Forecasting
• [stat.ML]Uncertainty Propagation in Deep Neural Network Using Active Subspace
• [stat.ML]Variational Inference of Joint Models using Multivariate Gaussian Convolution Processes
·····································
• [astro-ph.IM]Application of Google Cloud Platform in Astrophysics
M. Landoni, G. Taffoni, A. Bignamini, R. Smareglia
http://arxiv.org/abs/1903.03337v1
• [cs.AI]Dynamic Demand Prediction for Expanding Electric Vehicle Sharing Systems: A Graph Sequence Learning Approach
Man Luo, Hongkai Wen, Yi Luo, Bowen Du, Konstantin Klemmer, Hongming Zhu
http://arxiv.org/abs/1903.04051v1
• [cs.AI]From Low-Level Events to Activities -- A Session-Based Approach (Extended Version)
Massimiliano de Leoni
http://arxiv.org/abs/1903.03993v1
• [cs.AI]Improving Humanness of Virtual Agents and Users' Cooperation through Emotions
Moojan Ghafurian, Neil Budnarain, Jesse Hoey
http://arxiv.org/abs/1903.03980v1
• [cs.AI]Learning Self-Game-Play Agents for Combinatorial Optimization Problems
Ruiyang Xu, Karl Lieberherr
http://arxiv.org/abs/1903.03674v1
• [cs.AI]Literal or Pedagogic Human? Analyzing Human Model Misspecification in Objective Learning
Smitha Milli, Anca D. Dragan
http://arxiv.org/abs/1903.03877v1
• [cs.AI]Logic Rules Powered Knowledge Graph Embedding
Pengwei Wang, Dejing Dou, Fangzhao Wu, Nisansa de Silva, Lianwen Jin
http://arxiv.org/abs/1903.03772v1
• [cs.AI]Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Autonomous Robots
Pooyan Jamshidi, Javier Cámara, Bradley Schmerl, Christian Kästner, David Garlan
http://arxiv.org/abs/1903.03920v1
• [cs.AI]Physics Enhanced Artificial Intelligence
Patrick O'Driscoll, Jaehoon Lee, Bo Fu
http://arxiv.org/abs/1903.04442v1
• [cs.AI]Program Classification Using Gated Graph Attention Neural Network for Online Programming Service
Mingming Lu, Dingwu Tan, Naixue Xiong, Zailiang Chen, Haifeng Li
http://arxiv.org/abs/1903.03804v1
• [cs.AI]Reachability and Coverage Planning for Connected Agents: Extended Version
Tristan Charrier, Arthur Queffelec, Ocan Sankur, François Schwarzentruber
http://arxiv.org/abs/1903.04300v1
• [cs.AI]Rethinking System Health Management
Edward Balaban, Stephen B. Johnson, Mykel J. Kochenderfer
http://arxiv.org/abs/1903.03948v1
• [cs.AR]Automated Circuit Approximation Method Driven by Data Distribution
Zdenek Vasicek, Vojtech Mrazek, Lukas Sekanina
http://arxiv.org/abs/1903.04188v1
• [cs.CC]Knowledge compilation languages as proof systems
Florent Capelli
http://arxiv.org/abs/1903.04039v1
• [cs.CE]A Decision Support System for Multi-target Geosteering
Sergey Alyaev, Erich Suter, Reidar Bratvold, Aojie Hong, Xiaodong Luo
http://arxiv.org/abs/1903.03933v1
• [cs.CL]An Innovative Word Encoding Method For Text Classification Using Convolutional Neural Network
Amr Adel Helmy, Yasser M. K. Omar, Rania Hodhod
http://arxiv.org/abs/1903.04146v1
• [cs.CL]Contextualised concept embedding for efficiently adapting natural language processing models for phenotype identification
Honghan Wu, Karen Hodgson, Susan Dyson, Katherine I. Morley, Zina M. Ibrahim, Ehtesham Iqbal, Robert Stewart, Richard JB Dobson, Cathie Sudlow
http://arxiv.org/abs/1903.03995v1
• [cs.CL]ETNLP: A Toolkit for Extraction, Evaluation and Visualization of Pre-trained Word Embeddings
Xuan-Son Vu, Thanh Vu, Son N. Tran, Lili Jiang
http://arxiv.org/abs/1903.04433v1
• [cs.CL]HLT@SUDA at SemEval 2019 Task 1: UCCA Graph Parsing as Constituent Tree Parsing
Wei Jiang, Yu Zhang, Zhenghua Li, Min Zhang
http://arxiv.org/abs/1903.04153v1
• [cs.CL]Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
Hila Gonen, Yoav Goldberg
http://arxiv.org/abs/1903.03862v1
• [cs.CL]Named Entity Recognition for Electronic Health Records: A Comparison of Rule-based and Machine Learning Approaches
Philip John Gorinski, Honghan Wu, Claire Grover, Richard Tobin, Conn Talbot, Heather Whalley, Cathie Sudlow, William Whiteley, Beatrice Alex
http://arxiv.org/abs/1903.03985v1
• [cs.CL]Partially Shuffling the Training Data to Improve Language Models
Ofir Press
http://arxiv.org/abs/1903.04167v1
• [cs.CL]Toward Fast and Accurate Neural Chinese Word Segmentation with Multi-Criteria Learning
Weipeng Huang, Xingyi Cheng, Kunlong Chen, Taifeng Wang, Wei Chu
http://arxiv.org/abs/1903.04190v1
• [cs.CR]Incentives in Ethereum's Hybrid Casper Protocol
Vitalik Buterin, Daniel Reijsbergen, Stefanos Leonardos, Georgios Piliouras
http://arxiv.org/abs/1903.04205v1
• [cs.CV]A Hybrid Framework for Action Recognition in Low-Quality Video Sequences
Tej Singh, Dinesh Kumar Vishwakarma
http://arxiv.org/abs/1903.04090v1
• [cs.CV]A Hybrid GA-PSO Method for Evolving Architecture and Short Connections of Deep Convolutional Neural Networks
Bin Wang, Yanan Sun, Bing Xue, Mengjie Zhang
http://arxiv.org/abs/1903.03893v1
• [cs.CV]A Unified Formulation for Visual Odometry
Georges Younes, Daniel Asmar, John Zelek
http://arxiv.org/abs/1903.04253v1
• [cs.CV]ADS-ME: Anomaly Detection System for Micro-expression Spotting
Dawood Al Chanti, Alice Caplier
http://arxiv.org/abs/1903.04354v1
• [cs.CV]Accuracy Booster: Performance Boosting using Feature Map Re-calibration
Pravendra Singh, Pratik Mazumder, Vinay P. Namboodiri
http://arxiv.org/abs/1903.04407v1
• [cs.CV]Automated Segmentation of Knee MRI Using Hierarchical Classifiers and Just Enough Interaction Based Learning: Data from Osteoarthritis Initiative
Satyananda Kashyap, Ipek Oguz, Honghai Zhang, Milan Sonka
http://arxiv.org/abs/1903.03929v1
• [cs.CV]BayesOD: A Bayesian Approach for Uncertainty Estimation in Deep Object Detectors
Ali Harakeh, Michael Smart, Steven L. Waslander
http://arxiv.org/abs/1903.03838v1
• [cs.CV]Combining 3D Morphable Models: A Large scale Face-and-Head Model
Stylianos Ploumpis, Haoyang Wang, Nick Pears, William A. P. Smith, Stefanos Zafeiriou
http://arxiv.org/abs/1903.03785v1
• [cs.CV]Deep Generative Models: Deterministic Prediction with an Application in Inverse Rendering
Shima Kamyab, Rasool Sabzi, Zohreh Azimifar
http://arxiv.org/abs/1903.04144v1
• [cs.CV]Deep Reinforcement Learning of Volume-guided Progressive View Inpainting for 3D Point Scene Completion from a Single Depth Image
Xiaoguang Han, Zhaoxuan Zhang, Dong Du, Mingdai Yang, Jingming Yu, Pan Pan, Xin Yang, Ligang Liu, Zixiang Xiong, Shuguang Cui
http://arxiv.org/abs/1903.04019v1
• [cs.CV]Deep Robust Subjective Visual Property Prediction in Crowdsourcing
Qianqian Xu, Zhiyong Yang, Yangbangyan Jiang, Xiaochun Cao, Qingming Huang, Yuan Yao
http://arxiv.org/abs/1903.03956v1
• [cs.CV]Distributed deep learning for robust multi-site segmentation of CT imaging after traumatic brain injury
Samuel Remedios, Snehashis Roy, Justin Blaber, Camilo Bermudez, Vishwesh Nath, Mayur B. Patel, John A. Butman, Bennett A. Landman, Dzung L. Pham
http://arxiv.org/abs/1903.04207v1
• [cs.CV]Domain Randomization for Active Pose Estimation
Xinyi Ren, Jianlan Luo, Eugen Solowjow, Juan Aparicio Ojea, Abhishek Gupta, Aviv Tamar, Pieter Abbeel
http://arxiv.org/abs/1903.03953v1
• [cs.CV]Fast Single Image Reflection Suppression via Convex Optimization
Yang Yang, Wenye Ma, Yin Zheng, Jian-Feng Cai, Weiyu Xu
http://arxiv.org/abs/1903.03889v1
• [cs.CV]Group-wise Correlation Stereo Network
Xiaoyang Guo, Kai Yang, Wukui Yang, Xiaogang Wang, Hongsheng Li
http://arxiv.org/abs/1903.04025v1
• [cs.CV]HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs
Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri
http://arxiv.org/abs/1903.04120v1
• [cs.CV]Hierarchy Denoising Recursive Autoencoders for 3D Scene Layout Prediction
Yifei Shi, Angel Xuan Chang, Zhelun Wu, Manolis Savva, Kai Xu
http://arxiv.org/abs/1903.03757v1
• [cs.CV]How Effectively Can Indoor Wireless Positioning Relieve Visual Tracking Pains: A Camera-Rao Bound Viewpoint
Panwen Hu, Zizheng Yan, Rui Huang, Feng Yin
http://arxiv.org/abs/1903.03736v1
• [cs.CV]Image Privacy Prediction Using Deep Neural Networks
Ashwini Tonge, Cornelia Caragea
http://arxiv.org/abs/1903.03695v1
• [cs.CV]Instance- and Category-level 6D Object Pose Estimation
Caner Sahin, Guillermo Garcia-Hernando, Juil Sock, Tae-Kyun Kim
http://arxiv.org/abs/1903.04229v1
• [cs.CV]Investigation on Combining 3D Convolution of Image Data and Optical Flow to Generate Temporal Action Proposals
Patrick Schlosser, David Münch, Michael Arens
http://arxiv.org/abs/1903.04176v1
• [cs.CV]Joint inference on structural and diffusion MRI for sequence-adaptive Bayesian segmentation of thalamic nuclei with probabilistic atlases
Juan Eugenio Iglesias, Koen Van Leemput, Polina Golland, Anastasia Yendiki
http://arxiv.org/abs/1903.04352v1
• [cs.CV]Just-Enough Interaction Approach to Knee MRI Segmentation: Data from the Osteoarthritis Initiative
Satyananda Kashyap, Honghai Zhang, Milan Sonka
http://arxiv.org/abs/1903.04027v1
• [cs.CV]Learning-Based Cost Functions for 3D and 4D Multi-Surface Multi-Object Segmentation of Knee MRI: Data from the Osteoarthritis Initiative
Satyananda Kashyap, Honghai Zhang, Karan Rao, Milan Sonka
http://arxiv.org/abs/1903.03927v1
• [cs.CV]LumiPath - Towards Real-time Physically-based Rendering on Embedded Devices
Laura Fink, Sing Chun Lee, Marc Stamminger, Nassir Navab, Mathias Unberath
http://arxiv.org/abs/1903.03837v1
• [cs.CV]MSFD:Multi-Scale Receptive Field Face Detector
Qiushan Guo, Yuan Dong, Yu Guo, Hongliang Bai
http://arxiv.org/abs/1903.04147v1
• [cs.CV]MTRNet: A Generic Scene Text Eraser
Osman Tursun, Rui Zeng, Simon Denman, Sabesan Sivipalan, Sridha Sridharan, Clinton Fookes
http://arxiv.org/abs/1903.04092v1
• [cs.CV]Manifold Mixup improves text recognition with CTC loss
Bastien Moysset, Ronaldo Messina
http://arxiv.org/abs/1903.04246v1
• [cs.CV]Mix and match networks: multi-domain alignment for unpaired image-to-image translation
Yaxing Wang, Luis Herranz, Joost van de Weijer
http://arxiv.org/abs/1903.04294v1
• [cs.CV]Multiview 2D/3D Rigid Registration via a Point-Of-Interest Network for Tracking and Triangulation (POINT^2)
Haofu Liao, Wei-An Lin, Jiarui Zhang, Jingdan Zhang, Jiebo Luo, S. Kevin Zhou
http://arxiv.org/abs/1903.03896v1
• [cs.CV]Partial Order Pruning: for Best Speed/Accuracy Trade-off in Neural Architecture Search
Xin Li, Yiming Zhou, Zheng Pan, Jiashi Feng
http://arxiv.org/abs/1903.03777v1
• [cs.CV]Pluralistic Image Completion
Chuanxia Zheng, Tat-Jen Cham, Jianfei Cai
http://arxiv.org/abs/1903.04227v1
• [cs.CV]Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge Distillation for Unsupervised Monocular Depth Estimation
Andrea Pilzer, Stéphane Lathuilière, Nicu Sebe, Elisa Ricci
http://arxiv.org/abs/1903.04202v1
• [cs.CV]RoPAD: Robust Presentation Attack Detection through Unsupervised Adversarial Invariance
Ayush Jaiswal, Shuai Xia, Iacopo Masi, Wael AbdAlmageed
http://arxiv.org/abs/1903.03691v1
• [cs.CV]Rolling-Shutter-Aware Differential SfM and Image Rectification
Bingbing Zhuang, Loong-Fah Cheong, Gim Hee Lee
http://arxiv.org/abs/1903.03943v1
• [cs.CV]SSN: Learning Sparse Switchable Normalization via SparsestMax
Wenqi Shao, Tianjian Meng, Jingyu Li, Ruimao Zhang, Yudian Li, Xiaogang Wang, Ping Luo
http://arxiv.org/abs/1903.03793v1
• [cs.CV]Shape2Motion: Joint Analysis of Motion Parts and Attributes from 3D Shapes
Xiaogang Wang, Bin Zhou, Yahao Shi, Xiaowu Chen, Qinping Zhao, Kai Xu
http://arxiv.org/abs/1903.03911v1
• [cs.CV]Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation
Chen-Yu Lee, Tanmay Batra, Mohammad Haris Baig, Daniel Ulbricht
http://arxiv.org/abs/1903.04064v1
• [cs.CV]Sparse Representations for Object and Ego-motion Estimation in Dynamic Scenes
Hirak J Kashyap, Charless Fowlkes, Jeffrey L Krichmar
http://arxiv.org/abs/1903.03731v1
• [cs.CV]Spatial-Aware Non-Local Attention for Fashion Landmark Detection
Yixin Li, Shengqin Tang, Yun Ye, Jinwen Ma
http://arxiv.org/abs/1903.04104v1
• [cs.CV]Stroke-based Artistic Rendering Agent with Deep Reinforcement Learning
Zhewei Huang, Wen Heng, Shuchang Zhou
http://arxiv.org/abs/1903.04411v1
• [cs.CV]Structured Knowledge Distillation for Semantic Segmentation
Yifan Liu, Ke Chen, Chris Liu, Zengchang Qin, Zhenbo Luo, Jingdong Wang
http://arxiv.org/abs/1903.04197v1
• [cs.CV]The Past and the Present of the Color Checker Dataset Misuse
Nikola Banić, Karlo Koš{č}ević, Marko Subašić, Sven Lon{č}arić
http://arxiv.org/abs/1903.04473v1
• [cs.CV]The Unconstrained Ear Recognition Challenge 2019
Žiga Emeršič, Aruna Kumar S. V., B. S. Harish, Weronika Gutfeter, Jalil Nourmohammadi Khiarak, Andrzej Pacut, Earnest Hansley, Mauricio Pamplona Segundo, Sudeep Sarkar, Hyeonjung Park, Gi Pyo Nam, Ig-Jae Kim, Sagar G. Sangodkar, Ümit Kaçar, Murvet Kirci, Li Yuan, Jishou Yuan, Haonan Zhao, Fei Lu, Junying Mao, Xiaoshuang Zhang, Dogucan Yaman, Fevziye Irem Eyiokur, Kadir Bulut Özler, Hazım Kemal Ekenel, Debbrota Paul Chowdhury, Sambit Bakshi, Banshidhar Majhi, Peter Peer, Vitomir Štruc
http://arxiv.org/abs/1903.04143v1
• [cs.CV]Video Generation from Single Semantic Label Map
Junting Pan, Chengyu Wang, Xu Jia, Jing Shao, Lu Sheng, Junjie Yan, Xiaogang Wang
http://arxiv.org/abs/1903.04480v1
• [cs.CY]A reference architecture for integrating the Industrial Internet of Things in the Industry 4.0
Petar Radanliev, David De Roure, Razvan Nicolescu, Michael Huth
http://arxiv.org/abs/1903.04369v1
• [cs.CY]Blameworthiness in Multi-Agent Settings
Meir Friedenberg, Joseph Y. Halpern
http://arxiv.org/abs/1903.04102v1
• [cs.CY]Gathering Insights from Teenagers' Hacking Experience with Authentic Cybersecurity Tools
Valdemar Švábenský, Jan Vykopal
http://arxiv.org/abs/1903.04174v1
• [cs.CY]Standardisation of cyber risk impact assessment for the Internet of Things (IoT)
Petar Radanliev, David De Roure, Jason Nurse, Rafael Mantilla Montalvo, Peter Burnap
http://arxiv.org/abs/1903.04428v1
• [cs.DB]Graph Data on the Web: extend the pivot, don't reinvent the wheel
Fabien Gandon, Franck Michel, Olivier Corby, Michel Buffa, Andrea Tettamanzi, Catherine Faron Zucker, Elena Cabrio, Serena Villata
http://arxiv.org/abs/1903.04181v1
• [cs.DB]RESTORE: Automated Regression Testing for Datasets
Lei Zhang, Sean Howard, Tom Montpool, Jessica Moore, Krittika Mahajan, Andriy Miranskyy
http://arxiv.org/abs/1903.03676v1
• [cs.DB]Transparency, Fairness, Data Protection, Neutrality: Data Management Challenges in the Face of New Regulation
Serge Abiteboul, Julia Stoyanovich
http://arxiv.org/abs/1903.03683v1
• [cs.DC]A GraphBLAS Approach for Subgraph Counting
Langshi Chen, Jiayu Li, Ariful Azad, Lei Jiang, Madhav Marathe, Anil Vullikanti, Andrey Nikolaev, Egor Smirnov, Ruslan Israfilov, Judy Qiu
http://arxiv.org/abs/1903.04395v1
• [cs.DC]Analyzing GPU Tensor Core Potential for Fast Reductions
Roberto Carrasco, Raimundo Vega, Cristóbal A. Navarro
http://arxiv.org/abs/1903.03640v1
• [cs.DC]Asynchronous Federated Optimization
Cong Xie, Sanmi Koyejo, Indranil Gupta
http://arxiv.org/abs/1903.03934v1
• [cs.DC]Auto-Vectorizing TensorFlow Graphs: Jacobians, Auto-Batching And Beyond
Ashish Agarwal, Igor Ganichev
http://arxiv.org/abs/1903.04243v1
• [cs.DC]Proteus: A Scalable BFT Consesus Protocol for Blockchains
Mohammad M. Jalalzai, Costas Busch, Golden Richard III
http://arxiv.org/abs/1903.04134v1
• [cs.DC]Security, Performance and Energy Trade-offs of Hardware-assisted Memory Protection Mechanisms
Christian Göttel, Rafael Pires, Isabelly Rocha, Sébastien Vaucher, Pascal Felber, Marcelo Pasin, Valerio Schiavoni
http://arxiv.org/abs/1903.04203v1
• [cs.DC]TensorFlow Doing HPC
Steven W. D. Chien, Stefano Markidis, Vyacheslav Olshevsky, Yaroslav Bulatov, Erwin Laure, Jeffrey S. Vetter
http://arxiv.org/abs/1903.04364v1
• [cs.HC]Exploring OpenStreetMap Availability for Driving Environment Understanding
Yang Zheng, Izzat H. Izzat, John H. L. Hansen
http://arxiv.org/abs/1903.04084v1
• [cs.IR]A Clustering-Based Combinatorial Approach to Unsupervised Matching of Product Titles
Leonidas Akritidis, Athanasios Fevgas, Panayiotis Bozanis, Christos Makris
http://arxiv.org/abs/1903.04276v1
• [cs.IR]A New Approach for Topic Detection using Adaptive Neural Networks
Meriem Manai
http://arxiv.org/abs/1903.03775v1
• [cs.IR]Automatic Ontology Learning from Domain-Specific Short Unstructured Text Data
Yiming Xu, Dnyanesh Rajpathak, Ian Gibbs, Diego Klabjan
http://arxiv.org/abs/1903.04360v1
• [cs.IR]Jointly Learning Explainable Rules for Recommendation with Knowledge Graph
Weizhi Ma, Min Zhang, Yue Cao, Woojeong, Jin, Chenyang Wang, Yiqun Liu, Shaoping Ma, Xiang Ren
http://arxiv.org/abs/1903.03714v1
• [cs.IR]Mutual Clustering on Comparative Texts via Heterogeneous Information Networks
Jianping Cao, Senzhang Wang, Danyan Wen, Zhaohui Peng, Philip S. Yu, Fei-yue Wang
http://arxiv.org/abs/1903.03762v1
• [cs.IR]The Web is missing an essential part of infrastructure: an Open Web Index
Dirk Lewandowski
http://arxiv.org/abs/1903.03846v1
• [cs.IT]A Low-Complexity Cache-Aided Multi-antenna Content Delivery Scheme
Junlin Zhao, Mohammad Mohammadi Amiri, Deniz Gündüz
http://arxiv.org/abs/1903.03856v1
• [cs.IT]A simple bound on the BER of the MAP decoder for massive MIMO systems
Christos Thrampoulidis, Ilias Zadik, Yury Polyanskiy
http://arxiv.org/abs/1903.03949v1
• [cs.IT]Clustering-Correcting Codes
Tal Shinkar, Eitan Yaakobi, Andreas Lenz, Antonia Wachter-Zeh
http://arxiv.org/abs/1903.04122v1
• [cs.IT]Hybrid Transceiver Optimization for Multi-Hop Communications
Chengwen Xing, Xin Zhao, Shuai Wang, Wei Xu, Soon Xin Ng, Sheng Chen
http://arxiv.org/abs/1903.03820v1
• [cs.IT]Interference Mitigation for Ultrareliable Low-Latency Wireless Communication
S. Arvin Ayoughi, Wei Yu, Saeed R. Khosravirad, Harish Viswanathan
http://arxiv.org/abs/1903.04130v1
• [cs.IT]Molecular Information Delivery in Porous Media
Yuting Fang, Weisi Guo, Matteo Icardi, Adam Noel, Nan Yang
http://arxiv.org/abs/1903.03738v1
• [cs.IT]Optimizing Information Freshness in Broadcast Network with Unreliable Links and Random Arrivals: An Approximate Index Policy
Jingzhou Sun, Zhiyuan Jiang, Sheng Zhou, Zhisheng Niu
http://arxiv.org/abs/1903.03723v1
• [cs.IT]Probability Mass Functions for which Sources have the Maximum Minimum Expected Length
Shivkumar K. Manickam
http://arxiv.org/abs/1903.03755v1
• [cs.IT]Publicness, Privacy and Confidentiality in the Single-Serving Quantum Broadcast Channel
Farzin Salek, Min-Hsiu Hsieh, Javier R. Fonollosa
http://arxiv.org/abs/1903.04463v1
• [cs.IT]Semi-Blind Channel-and-Signal Estimation for Uplink Massive MIMO With Channel Sparsity
Wenjing Yan, Xiaojun Yuan
http://arxiv.org/abs/1903.04163v1
• [cs.IT]Strengthened Information-theoretic Bounds on the Generalization Error
Ibrahim Issa, Amedeo Roberto Esposito, Michael Gastpar
http://arxiv.org/abs/1903.03787v1
• [cs.IT]The parameters of a family of linear codes
Weiqiong Wang, Yan Wang
http://arxiv.org/abs/1903.03720v1
• [cs.LG]Accelerating Minibatch Stochastic Gradient Descent using Typicality Sampling
Xinyu Peng, Li Li, Fei-Yue Wang
http://arxiv.org/abs/1903.04192v1
• [cs.LG]Algorithms for an Efficient Tensor Biclustering
Andriantsiory Dina Faneva, Mustapha Lebbah, Hanane Azzag, Gaël Beck
http://arxiv.org/abs/1903.04042v1
• [cs.LG]Based on Graph-VAE Model to Predict Student's Score
Yang Zhang, Mingming Lu
http://arxiv.org/abs/1903.03609v1
• [cs.LG]Continual Learning via Neural Pruning
Siavash Golkar, Michael Kagan, Kyunghyun Cho
http://arxiv.org/abs/1903.04476v1
• [cs.LG]Deep Recurrent Q-Learning vs Deep Q-Learning on a simple Partially Observable Markov Decision Process with Minecraft
Clément Romac, Vincent Béraud
http://arxiv.org/abs/1903.04311v1
• [cs.LG]Deep learning for molecular generation and optimization - a review of the state of the art
Daniel C. Elton, Zois Boukouvalas, Mark D. Fuge, Peter W. Chung
http://arxiv.org/abs/1903.04388v1
• [cs.LG]Fair Logistic Regression: An Adversarial Perspective
Ashkan Rezaei, Rizal Fathony, Omid Memarrast, Brian Ziebart
http://arxiv.org/abs/1903.03910v1
• [cs.LG]Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation
Cong Xie, Sanmi Koyejo, Indranil Gupta
http://arxiv.org/abs/1903.03936v1
• [cs.LG]Fisher-Bures Adversary Graph Convolutional Networks
Ke Sun, Piotr Koniusz, Jeff Wang
http://arxiv.org/abs/1903.04154v1
• [cs.LG]GNN Explainer: A Tool for Post-hoc Explanation of Graph Neural Networks
Rex Ying, Dylan Bourgeois, Jiaxuan You, Marinka Zitnik, Jure Leskovec
http://arxiv.org/abs/1903.03894v1
• [cs.LG]Gradient Descent based Optimization Algorithms for Deep Learning Models Training
Jiawei Zhang
http://arxiv.org/abs/1903.03614v1
• [cs.LG]Hybrid Reinforcement Learning with Expert State Sequences
Xiaoxiao Guo, Shiyu Chang, Mo Yu, Gerald Tesauro, Murray Campbell
http://arxiv.org/abs/1903.04110v1
• [cs.LG]InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction
Anees Kazi, Shayan shekarforoush, S. Arvind krishna, Hendrik Burwinkel, Gerome Vivar, Karsten Kortuem, Seyed-Ahmad Ahmadi, Shadi Albarqouni, Nassir Navab
http://arxiv.org/abs/1903.04233v1
• [cs.LG]Interpreting and Understanding Graph Convolutional Neural Network using Gradient-based Attribution Methods
Shangsheng Xie, Mingming Lu
http://arxiv.org/abs/1903.03768v1
• [cs.LG]Labeler-hot Detection of EEG Epileptic Transients
Lukasz Czekaj, Wojciech Ziembla, Pawel Jezierski, Pawel Swiniarski, Anna Kolodziejak, Pawel Ogniewski, Pawel Niedbalski, Anna Jezierska, Daniel Wesierski
http://arxiv.org/abs/1903.04337v1
• [cs.LG]Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games
Chun Kai Ling, Fei Fang, J. Zico Kolter
http://arxiv.org/abs/1903.04101v1
• [cs.LG]Learning Quantum Graphical Models using Constrained Gradient Descent on the Stiefel Manifold
Sandesh Adhikary, Siddarth Srinivasan, Byron Boots
http://arxiv.org/abs/1903.03730v1
• [cs.LG]Machine Learning Based Prediction and Classification of Computational Jobs in Cloud Computing Centers
Zheqi Zhu, Pingyi Fan
http://arxiv.org/abs/1903.03759v1
• [cs.LG]Multinomial Random Forests: Fill the Gap between Theoretical Consistency and Empirical Soundness
Yiming Li, Jiawang Bai, Qingtao Tang, Yong Jiang, Chun Li, Shutao Xia
http://arxiv.org/abs/1903.04003v1
• [cs.LG]Non-Negative Kernel Sparse Coding for the Classification of Motion Data
Babak Hosseini, Felix Hülsmann, Mario Botsch, Barbara Hammer
http://arxiv.org/abs/1903.03891v1
• [cs.LG]One-Pass Sparsified Gaussian Mixtures
Eric Kightley, Stephen Becker
http://arxiv.org/abs/1903.04056v1
• [cs.LG]Optimal Collusion-Free Teaching
David Kirkpatrick, Hans U. Simon, Sandra Zilles
http://arxiv.org/abs/1903.04012v1
• [cs.LG]Revisiting clustering as matrix factorisation on the Stiefel manifold
Stéphane Chrétien, Benjamin Guedj
http://arxiv.org/abs/1903.04479v1
• [cs.LG]Robust Influence Maximization for Hyperparametric Models
Dimitris Kalimeris, Gal Kaplun, Yaron Singer
http://arxiv.org/abs/1903.03746v1
• [cs.LG]Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics
Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers, Ann Nowé
http://arxiv.org/abs/1903.04193v1
• [cs.LG]Scaling up deep neural networks: a capacity allocation perspective
Jonathan Donier
http://arxiv.org/abs/1903.04455v1
• [cs.LG]Scene Memory Transformer for Embodied Agents in Long-Horizon Tasks
Kuan Fang, Alexander Toshev, Li Fei-Fei, Silvio Savarese
http://arxiv.org/abs/1903.03878v1
• [cs.LG]Similarity Learning via Kernel Preserving Embedding
Zhao Kang, Yiwei Lu, Yuanzhang Su, Changsheng Li, Zenglin Xu
http://arxiv.org/abs/1903.04235v1
• [cs.LG]Skew-Fit: State-Covering Self-Supervised Reinforcement Learning
Vitchyr H. Pong, Murtaza Dalal, Steven Lin, Ashvin Nair, Shikhar Bahl, Sergey Levine
http://arxiv.org/abs/1903.03698v1
• [cs.LG]SleepNet: Automated Sleep Disorder Detection via Dense Convolutional Neural Network
Bahareh Pourbabaee, Matthew Howe-Patterson, Matthew Patterson, Frederic Benard
http://arxiv.org/abs/1903.04377v1
• [cs.LG]Stochastic Incremental Algorithms for Optimal Transport with SON Regularizer
Ashkan Panahi, Erik Thiel, Morteza H. Cheraghani, Devdatt Dubhashi
http://arxiv.org/abs/1903.03850v1
• [cs.LG]Successive Over Relaxation Q-Learning
Chandramouli Kamanchi, Raghuram Bharadwaj Diddigi, Shalabh Bhatnagar
http://arxiv.org/abs/1903.03812v1
• [cs.LG]Two-Hop Walks Indicate PageRank Order
Ying Tang
http://arxiv.org/abs/1903.03756v1
• [cs.NE]A Genetic Programming System with an Epigenetic Mechanism for Traffic Signal Control
Esteban Ricalde
http://arxiv.org/abs/1903.03854v1
• [cs.NE]A Spiking Network for Inference of Relations Trained with Neuromorphic Backpropagation
Johannes C. Thiele, Olivier Bichler, Antoine Dupret, Sergio Solinas, Giacomo Indiveri
http://arxiv.org/abs/1903.04341v1
• [cs.NE]DeepPool: Distributed Model-free Algorithm for Ride-sharing using Deep Reinforcement Learning
Abubakr Alabbasi, Arnob Ghosh, Vaneet Aggarwal
http://arxiv.org/abs/1903.03882v1
• [cs.OH]Pragmatic inference and visual abstraction enable contextual flexibility during visual communication
Judith Fan, Robert Hawkins, Mike Wu, Noah Goodman
http://arxiv.org/abs/1903.04448v1
• [quant-ph]Quantifying the magic of quantum channels
Xin Wang, Mark M. Wilde, Yuan Su
http://arxiv.org/abs/1903.04483v1
• [stat.AP]Better-than-expert detection of early coronary artery occlusion from 12 lead electrocardiograms using deep learning
Rob Brisk, Raymond R Bond. Dewar D Finlay, James McLaughlin, Alicja Piadlo, Stephen J Leslie, David E Gossman, Ian B A Menown, David J McEneaney
http://arxiv.org/abs/1903.04421v1
• [stat.AP]Retailer response to wholesale stockouts
George Liberopoulos, Isidoros Tsikis
http://arxiv.org/abs/1903.04035v1
• [stat.AP]Semi-Supervised Non-Parametric Bayesian Modelling of Spatial Proteomics
Oliver M. Crook, Kathryn S. Lilley, Laurent Gatto, Paul D. W. Kirk
http://arxiv.org/abs/1903.02909v2
• [stat.ME]A Potential Outcomes Calculus for Identifying Conditional Path-Specific Effects
Daniel Malinsky, Ilya Shpitser, Thomas Richardson
http://arxiv.org/abs/1903.03662v1
• [stat.ME]A synthetic likelihood-based Laplace approximation for efficient design of biological processes
Mahasen Dehideniya, Antony M. Overstall, Chris C. Drovandi, James M. McGree
http://arxiv.org/abs/1903.04168v1
• [stat.ME]Adaptive-to-model hybrid of tests for regressions
Lingzhu Li, Xuehu Zhu, Lixing Zhu
http://arxiv.org/abs/1903.03742v1
• [stat.ME]Confidence Interval for Quantile Ratio of the Dagum Distribution
Alina Jędrzejczak, Dorota Pekasiewicz, Wojciech Zieliński
http://arxiv.org/abs/1903.04223v1
• [stat.ME]Distributed Feature Screening via Componentwise Debiasing
Xingxiang Li, Runze Li, Zhiming Xia, Chen Xu
http://arxiv.org/abs/1903.03810v1
• [stat.ME]Estimating Individualized Decision Rules with Tail Controls
Zhengling Qi, Jong-Shi Pang, Yufeng Liu
http://arxiv.org/abs/1903.04367v1
• [stat.ME]Estimation and Inference for High Dimensional Generalized Linear Models: A Splitting and Smoothing Approach
Zhe Fei, Yi Li
http://arxiv.org/abs/1903.04408v1
• [stat.ME]Lasso tuning through the flexible-weighted bootstrap
Ellis Patrick, Samuel Mueller
http://arxiv.org/abs/1903.03935v1
• [stat.ME]Streamlined Variational Inference for Higher Level Group-Specific Curve Models
M. Menictas, T. H. Nolan, D. G. Simpson, M. P. Wand
http://arxiv.org/abs/1903.04043v1
• [stat.ME]The Shortest Confidence Interval for the Ratio of Quantiles of the Dagum Distribution
Alina Jȩdrzejczak, Dorota Pekasiewicz, Wojciech Zieliński
http://arxiv.org/abs/1903.04226v1
• [stat.ME]Transporting stochastic direct and indirect effects to new populations
Kara E Rudolph, Jonathan Levy, Mark J van der Laan
http://arxiv.org/abs/1903.03690v1
• [stat.ME]Two paradoxical results in linear models: the variance inflation factor and the analysis of covariance
Peng Ding
http://arxiv.org/abs/1903.03883v1
• [stat.ML]-IRT: A New Item Response Model and its Applications
Yu Chen, Telmo Silva Filho, Ricardo B. C. Prudêncio, Tom Diethe, Peter Flach
http://arxiv.org/abs/1903.04016v1
• [stat.ML]A cross-center smoothness prior for variational Bayesian brain tissue segmentation
Wouter M. Kouw, Silas N. Ørting, Jens Petersen, Kim S. Pedersen, Marleen de Bruijne
http://arxiv.org/abs/1903.04191v1
• [stat.ML]Bayesian Allocation Model: Inference by Sequential Monte Carlo for Nonnegative Tensor Factorizations and Topic Models using Polya Urns
Ali Taylan Cemgil, Mehmet Burak Kurutmaz, Sinan Yildirim, Melih Barsbey, Umut Simsekli
http://arxiv.org/abs/1903.04478v1
• [stat.ML]Functional Principal Component Analysis for Extrapolating Multi-stream Longitudinal Data
Seokhyun Chung, Raed Kontar
http://arxiv.org/abs/1903.03871v1
• [stat.ML]Interpolation Consistency Training for Semi-Supervised Learning
Vikas Verma, Alex Lamb, Juho Kannala, Yoshua Bengio, David Lopez-Paz
http://arxiv.org/abs/1903.03825v1
• [stat.ML]Likelihood-free MCMC with Approximate Likelihood Ratios
Joeri Hermans, Volodimir Begy, Gilles Louppe
http://arxiv.org/abs/1903.04057v1
• [stat.ML]Manifold Preserving Adversarial Learning
Ousmane Amadou Dia, Elnaz Barshan, Reza Babanezhad
http://arxiv.org/abs/1903.03905v1
• [stat.ML]Orthogonal Estimation of Wasserstein Distances
Mark Rowland, Jiri Hron, Yunhao Tang, Krzysztof Choromanski, Tamas Sarlos, Adrian Weller
http://arxiv.org/abs/1903.03784v1
• [stat.ML]Rectangular Bounding Process
Xuhui Fan, Bin Li, Scott Anthony Sisson
http://arxiv.org/abs/1903.03906v1
• [stat.ML]Shapley regressions: A framework for statistical inference on machine learning models
Andreas Joseph
http://arxiv.org/abs/1903.04209v1
• [stat.ML]Sparse Grouped Gaussian Processes for Solar Power Forecasting
Astrid Dahl, Edwin V. Bonilla
http://arxiv.org/abs/1903.03986v1
• [stat.ML]Uncertainty Propagation in Deep Neural Network Using Active Subspace
Weiqi Ji, Zhuyin Ren, Chung K. Law
http://arxiv.org/abs/1903.03989v1
• [stat.ML]Variational Inference of Joint Models using Multivariate Gaussian Convolution Processes
Xubo Yue, Raed Kontar
http://arxiv.org/abs/1903.03867v1
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