cs.AI - 人工智能
cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DC - 分布式、并行与集群计算 cs.DL - 数字图书馆 cs.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.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.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.NA - 数值分析 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.app-ph - 应用物理 physics.soc-ph - 物理学与社会 q-bio.NC - 神经元与认知 q-bio.PE - 人口与发展 q-fin.ST - 统计金融学 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 stat.OT - 其他统计学
• [cs.AI]An Ontology-based Approach to Explaining Artificial Neural Networks
• [cs.AI]An Open-World Extension to Knowledge Graph Completion Models
• [cs.AI]Designing Game of Theorems
• [cs.AI]Generic Ontology Design Patterns at Work
• [cs.AI]Modeling AGI Safety Frameworks with Causal Influence Diagrams
• [cs.AI]Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks
• [cs.CL]A New Statistical Approach for Comparing Algorithms for Lexicon Based Sentiment Analysis
• [cs.CL]Autonomous Haiku Generation
• [cs.CL]Conflict as an Inverse of Attention in Sequence Relationship
• [cs.CL]Considerations for the Interpretation of Bias Measures of Word Embeddings
• [cs.CL]Embedding time expressions for deep temporal ordering models
• [cs.CL]Few-Shot Sequence Labeling with Label Dependency Transfer
• [cs.CL]Fine-tuning Pre-Trained Transformer Language Models to Distantly Supervised Relation Extraction
• [cs.CL]HappyBot: Generating Empathetic Dialogue Responses by Improving User Experience Look-ahead
• [cs.CL]Hierarchical Document Encoder for Parallel Corpus Mining
• [cs.CL]Hindi Question Generation Using Dependency Structures
• [cs.CL]Improving Zero-shot Translation with Language-Independent Constraints
• [cs.CL]Incorporating Priors with Feature Attribution on Text Classification
• [cs.CL]Learning Compressed Sentence Representations for On-Device Text Processing
• [cs.CL]Multi-Grained Named Entity Recognition
• [cs.CL]Multilingual Multi-Domain Adaptation Approaches for Neural Machine Translation
• [cs.CL]Reflex: Flexible Framework for Relation Extraction in Multiple Domains
• [cs.CL]Robust Machine Translation with Domain Sensitive Pseudo-Sources: Baidu-OSU WMT19 MT Robustness Shared Task System Report
• [cs.CL]Semi-supervised acoustic model training for five-lingual code-switched ASR
• [cs.CR]Reversible Privacy Preservation using Multi-level Encryption and Compressive Sensing
• [cs.CR]SoK of Used Cryptography in Blockchain
• [cs.CV]3D Instance Segmentation via Multi-task Metric Learning
• [cs.CV]A Strong Baseline and Batch Normalization Neck for Deep Person Re-identification
• [cs.CV]Algorithmic Guarantees for Inverse Imaging with Untrained Network Priors
• [cs.CV]BGrowth: an efficient approach for the segmentation of vertebral compression fractures in magnetic resonance imaging
• [cs.CV]Deep-Learning-Based Aerial Image Classification for Emergency Response Applications Using Unmanned Aerial Vehicles
• [cs.CV]From Zero-Shot Learning to Cold-Start Recommendation
• [cs.CV]GAN-Knowledge Distillation for one-stage Object Detection
• [cs.CV]Homogeneous Vector Capsules Enable Adaptive Gradient Descent in Convolutional Neural Networks
• [cs.CV]Human \textit{vs} Machine Attention in Neural Networks: A Comparative Study
• [cs.CV]Improving the robustness of ImageNet classifiers using elements of human visual cognition
• [cs.CV]Learning Generalized Transformation Equivariant Representations via Autoencoding Transformations
• [cs.CV]Let’s Take This Online: Adapting Scene Coordinate Regression Network Predictions for Online RGB-D Camera Relocalisation
• [cs.CV]Light Field Saliency Detection with Deep Convolutional Networks
• [cs.CV]Model-based Deep MR Imaging: the roadmap of generalizing compressed sensing model using deep learning
• [cs.CV]Monocular 3D Object Detection and Box Fitting Trained End-to-End Using Intersection-over-Union Loss
• [cs.CV]Multiple-Identity Image Attacks Against Face-based Identity Verification
• [cs.CV]Nested Network with Two-Stream Pyramid for Salient Object Detection in Optical Remote Sensing Images
• [cs.CV]Pattern Spotting in Historical Documents Using Convolutional Models
• [cs.CV]Performance Evaluation Methodology for Long-Term Visual Object Tracking
• [cs.CV]PointNLM: Point Nonlocal-Means for vegetation segmentation based on middle echo point clouds
• [cs.CV]Uncovering Why Deep Neural Networks Lack Robustness: Representation Metrics that Link to Adversarial Attacks
• [cs.CV]vireoJD-MM at Activity Detection in Extended Videos
• [cs.CY]Measuring the Importance of User-Generated Content to Search Engines
• [cs.DC]Using Machine Learning to Optimize Web Interactions on Heterogeneous Mobile Multi-cores
• [cs.DL]Cleaning Noisy and Heterogeneous Metadata for Record Linking Across Scholarly Big Datasets
• [cs.DS]Coresets for Clustering with Fairness Constraints
• [cs.GT]Individual Fairness in Sponsored Search Auctions
• [cs.GT]Privacy, altruism, and experience: Estimating the perceived value of Internet data for medical uses
• [cs.IR]Citizens’ Emotion on GST: A Spatio-Temporal Analysis over Twitter Data
• [cs.IT]Complex phase retrieval from subgaussian measurements
• [cs.IT]Joint Uplink and Downlink Transmissions in User-Centric OFDMA Cloud-RAN
• [cs.IT]Low Probability of Detection Communication: Opportunities and Challenges
• [cs.IT]On the Dynamic Centralized Coded Caching Design
• [cs.IT]Physical Layer Security for Ultra-Reliable and Low-Latency Communications
• [cs.LG]Accelerating Mini-batch SARAH by Step Size Rules
• [cs.LG]Adversarial Regularization for Visual Question Answering: Strengths, Shortcomings, and Side Effects
• [cs.LG]An Improved Trade-off Between Accuracy and Complexity with Progressive Gradient Pruning
• [cs.LG]Analyzing and Storing Network Intrusion Detection Data using Bayesian Coresets: A Preliminary Study in Offline and Streaming Settings
• [cs.LG]Back to Simplicity: How to Train Accurate BNNs from Scratch?
• [cs.LG]Bayesian Modelling in Practice: Using Uncertainty to Improve Trustworthiness in Medical Applications
• [cs.LG]Beyond Supervised Classification: Extreme Minimal Supervision with the Graph 1-Laplacian
• [cs.LG]Boosting for Dynamical Systems
• [cs.LG]Calibrated Model-Based Deep Reinforcement Learning
• [cs.LG]Clustering and Classification Networks
• [cs.LG]Data Interpolating Prediction: Alternative Interpretation of Mixup
• [cs.LG]Differentiable probabilistic models of scientific imaging with the Fourier slice theorem
• [cs.LG]Disentangling Influence: Using Disentangled Representations to Audit Model Predictions
• [cs.LG]Experience Replay Optimization
• [cs.LG]Exploring Model-based Planning with Policy Networks
• [cs.LG]GEAR: Geometry-Aware Rényi Information
• [cs.LG]ID3 Learns Juntas for Smoothed Product Distributions
• [cs.LG]Inherent Tradeoffs in Learning Fair Representation
• [cs.LG]Learning Patient Engagement in Care Management: Performance vs. Interpretability
• [cs.LG]Max-Plus Matching Pursuit for Deterministic Markov Decision Processes
• [cs.LG]Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning
• [cs.LG]Preprocessing Methods and Pipelines of Data Mining: An Overview
• [cs.LG]Probabilistic Logic Neural Networks for Reasoning
• [cs.LG]Regional based query in graph active learning
• [cs.LG]Safe and Near-Optimal Policy Learning for Model Predictive Control using Primal-Dual Neural Networks
• [cs.LG]Scalable and Differentially Private Distributed Aggregation in the Shuffled Model
• [cs.LG]Solver Recommendation For Transport Problems in Slabs Using Machine Learning
• [cs.LG]Stochastic One-Sided Full-Information Bandit
• [cs.LG]Submodular Batch Selection for Training Deep Neural Networks
• [cs.LG]SwiftNet: Using Graph Propagation as Meta-knowledge to Search Highly Representative Neural Architectures
• [cs.LG]The Functional Neural Process
• [cs.LG]The Limited Multi-Label Projection Layer
• [cs.LG]The trade-off between long-term memory and smoothness for recurrent networks
• [cs.LG]Training on test data: Removing near duplicates in Fashion-MNIST
• [cs.LG]Unleashing the Unused Potential of I-Vectors Enabled by GPU Acceleration
• [cs.LG]We Need No Pixels: Video Manipulation Detection Using Stream Descriptors
• [cs.LO]Transformation of XML Documents with Prolog
• [cs.LO]Unification of Template-Expansion and XML-Validation
• [cs.MM]Understanding, Categorizing and Predicting Semantic Image-Text Relations
• [cs.MM]Zero-shot Learning and Knowledge Transfer in Music Classification and Tagging
• [cs.NE]testRNN: Coverage-guided Testing on Recurrent Neural Networks
• [cs.NI]A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art
• [cs.RO]2D Linear Time-Variant Controller for Human’s Intention Detection for Reach-to-Grasp Trajectories in Novel Scenes
• [cs.RO]A Hierarchical Architecture for Sequential Decision-Making in Autonomous Driving using Deep Reinforcement Learning
• [cs.RO]An observable time series based SLAM algorithm for deforming environment
• [cs.RO]Efficient two step optimization for large embedded deformation graph based SLAM
• [cs.RO]Metrics and Benchmarks for Remote Shared Controllers in Industrial Applications
• [cs.RO]Object Placement on Cluttered Surfaces: A Nested Local Search Approach
• [cs.RO]Predicting Motion of Vulnerable Road Users using High-Definition Maps and Efficient ConvNets
• [cs.RO]PuzzleFlex: kinematic motion of chains with loose joints
• [cs.SD]A Monaural Speech Enhancement Method for Robust Small-Footprint Keyword Spotting
• [cs.SD]Adversarial Learning for Improved Onsets and Frames Music Transcription
• [cs.SE]ENCORE: Ensemble Learning using Convolution Neural Machine Translation for Automatic Program Repair
• [cs.SI]A Graph Auto-Encoder for Attributed Network Embedding
• [cs.SI]Compressive Closeness in Networks
• [cs.SI]How the Avengers assemble: Ecological modelling of effective cast sizes for movies
• [cs.SI]Understanding Filter Bubbles and Polarization in Social Networks
• [eess.AS]Spatial Pyramid Encoding with Convex Length Normalization for Text-Independent Speaker Verification
• [eess.IV]A Segmentation-Oriented Inter-Class Transfer Method: Application to Retinal Vessel Segmentation
• [eess.IV]Learning the Sampling Pattern for MRI
• [eess.SP]Beam Entropy of 5G Cellular Millimetre-Wave Channels
• [eess.SP]Multitaper Spectral Analysis of Neuronal Spiking Activity Driven by Latent Stationary Processes
• [eess.SY]Cooperative Lane Changing via Deep Reinforcement Learning
• [math.NA]Sparse approximate matrix multiplication in a fully recursive distributed task-based parallel framework
• [math.OC]Global Convergence of Policy Gradient Methods to (Almost) Locally Optimal Policies
• [math.PR]First order covariance inequalities via Stein’s method
• [math.PR]On infinite covariance expansions
• [math.ST]Bounding the error of discretized Langevin algorithms for non-strongly log-concave targets
• [math.ST]Minimum Stein Discrepancy Estimators
• [math.ST]Optimal designs for estimating individual coefficients in polynomial regression with no intercept
• [math.ST]Universality in Learning from Linear Measurements
• [physics.app-ph]Tomographic Reconstruction of Triaxial Strain Fields from Bragg-Edge Neutron Imaging
• [physics.soc-ph]A network approach to cartel detection in public auction markets
• [q-bio.NC]Extraction of hierarchical functional connectivity components in human brain using resting-state fMRI
• [q-bio.PE]On the use of multiple compartment epidemiological models to describe the dynamics of influenza in Europe
• [q-fin.ST]Investment Ranking Challenge: Identifying the best performing stocks based on their semi-annual returns
• [stat.AP]An axiomatic nonparametric production function estimator: Modeling production in Japan’s cardboard industry
• [stat.AP]On Relative Ageing of Coherent Systems with Dependent Identically Distributed Components
• [stat.AP]On the probability of a causal inference is robust for internal validity
• [stat.AP]Ongoing Vaccine and Monoclonal Antibody HIV Prevention Efficacy Trials and Considerations for Sequel Efficacy Trial Designs
• [stat.AP]Reliable data from low cost ozone sensors in a hierarchical network
• [stat.AP]Sequential Rank Shiryaev-Roberts CUSUMs
• [stat.AP]Similarity indexing & GIS analysis of air pollution
• [stat.CO]PLS Generalized Linear Regression and Kernel Multilogit Algorithm (KMA) for Microarray Data Classification
• [stat.ME]Bayesian spatial clustering of extremal behaviour for hydrological variables
• [stat.ME]Causal Inference from Possibly Unbalanced Split-Plot Designs: A Randomization-based Perspective
• [stat.ME]Improving estimation of the volume under the ROC surface when data are missing not at random
• [stat.ME]Improving the Accuracy of Confidence Intervals and Regions in Multivariate Random-effects Meta-analysis
• [stat.ME]M-type penalized splines with auxiliary scale estimation
• [stat.ME]Model-free posterior inference on the area under the receiver operating characteristic curve
• [stat.ME]On application of a response propensity model to estimation from web samples
• [stat.ME]Regression Analysis of Dependent Binary Data for Estimating Disease Etiology from Case-Control Studies
• [stat.ML]Active Linear Regression
• [stat.ML]Adversarial Self-Paced Learning for Mixture Models of Hawkes Processes
• [stat.ML]Data Cleansing for Models Trained with SGD
• [stat.ML]Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup
• [stat.ML]Efficient data augmentation using graph imputation neural networks
• [stat.ML]Generalization error bounds for kernel matrix completion and extrapolation
• [stat.ML]Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities
• [stat.ML]More Efficient Policy Learning via Optimal Retargeting
• [stat.ML]Multi-resolution Multi-task Gaussian Processes
• [stat.ML]Screening Sinkhorn Algorithm for Regularized Optimal Transport
• [stat.ML]Sequential Experimental Design for Transductive Linear Bandits
• [stat.OT]Frequentist Inference without Repeated Sampling
·····································
• [cs.AI]An Ontology-based Approach to Explaining Artificial Neural Networks
Roberto Confalonieri, Fermín Moscoso del Prado, Sebastia Agramunt, Daniel Malagarriga, Daniele Faggion, Tillman Weyde, Tarek R. Besold
http://arxiv.org/abs/1906.08362v1
• [cs.AI]An Open-World Extension to Knowledge Graph Completion Models
Haseeb Shah, Johannes Villmow, Adrian Ulges, Ulrich Schwanecke, Faisal Shafait
http://arxiv.org/abs/1906.08382v1
• [cs.AI]Designing Game of Theorems
Yutaka Nagashima
http://arxiv.org/abs/1906.08549v1
• [cs.AI]Generic Ontology Design Patterns at Work
Bernd Krieg-Brückner, Till Mossakowski, Fabian Neuhaus
http://arxiv.org/abs/1906.08724v1
• [cs.AI]Modeling AGI Safety Frameworks with Causal Influence Diagrams
Tom Everitt, Ramana Kumar, Victoria Krakovna, Shane Legg
http://arxiv.org/abs/1906.08663v1
• [cs.AI]Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks
Roni Stern, Nathan Sturtevant, Ariel Felner, Sven Koenig, Hang Ma, Thayne Walker, Jiaoyang Li, Dor Atzmon, Liron Cohen, T. K. Satish Kumar, Eli Boyarski, Roman Bartak
http://arxiv.org/abs/1906.08291v1
• [cs.CL]A New Statistical Approach for Comparing Algorithms for Lexicon Based Sentiment Analysis
Mateus Machado, Evandro Ruiz, Kuruvilla Joseph Abraham
http://arxiv.org/abs/1906.08717v1
• [cs.CL]Autonomous Haiku Generation
Rui Aguiar, Kevin Liao
http://arxiv.org/abs/1906.08733v1
• [cs.CL]Conflict as an Inverse of Attention in Sequence Relationship
Rajarshee Mitra
http://arxiv.org/abs/1906.08593v1
• [cs.CL]Considerations for the Interpretation of Bias Measures of Word Embeddings
Inom Mirzaev, Anthony Schulte, Michael Conover, Sam Shah
http://arxiv.org/abs/1906.08379v1
• [cs.CL]Embedding time expressions for deep temporal ordering models
Tanya Goyal, Greg Durrett
http://arxiv.org/abs/1906.08287v1
• [cs.CL]Few-Shot Sequence Labeling with Label Dependency Transfer
Yutai Hou, Zhihan Zhou, Yijia Liu, Ning Wang, Wanxiang Che, Han Liu, Ting Liu
http://arxiv.org/abs/1906.08711v1
• [cs.CL]Fine-tuning Pre-Trained Transformer Language Models to Distantly Supervised Relation Extraction
Christoph Alt, Marc Hübner, Leonhard Hennig
http://arxiv.org/abs/1906.08646v1
• [cs.CL]HappyBot: Generating Empathetic Dialogue Responses by Improving User Experience Look-ahead
Jamin Shin, Peng Xu, Andrea Madotto, Pascale Fung
http://arxiv.org/abs/1906.08487v1
• [cs.CL]Hierarchical Document Encoder for Parallel Corpus Mining
Mandy Guo, Yinfei Yang, Keith Stevens, Daniel Cer, Heming Ge, Yun-Hsuan Sung, Brian Strope, Ray Kurzweil
http://arxiv.org/abs/1906.08401v1
• [cs.CL]Hindi Question Generation Using Dependency Structures
Kaveri Anuranjana, Vijjini Anvesh Rao, Radhika Mamidi
http://arxiv.org/abs/1906.08570v1
• [cs.CL]Improving Zero-shot Translation with Language-Independent Constraints
Ngoc-Quan Pham, Jan Niehues, Thanh-Le Ha, Alex Waibel
http://arxiv.org/abs/1906.08584v1
• [cs.CL]Incorporating Priors with Feature Attribution on Text Classification
Frederick Liu, Besim Avci
http://arxiv.org/abs/1906.08286v1
• [cs.CL]Learning Compressed Sentence Representations for On-Device Text Processing
Dinghan Shen, Pengyu Cheng, Dhanasekar Sundararaman, Xinyuan Zhang, Qian Yang, Meng Tang, Asli Celikyilmaz, Lawrence Carin
http://arxiv.org/abs/1906.08340v1
• [cs.CL]Multi-Grained Named Entity Recognition
Congying Xia, Chenwei Zhang, Tao Yang, Yaliang Li, Nan Du, Xian Wu, Wei Fan, Fenglong Ma, Philip Yu
http://arxiv.org/abs/1906.08449v1
• [cs.CL]Multilingual Multi-Domain Adaptation Approaches for Neural Machine Translation
Chenhui Chu, Raj Dabre
http://arxiv.org/abs/1906.07978v2
• [cs.CL]Reflex: Flexible Framework for Relation Extraction in Multiple Domains
Geeticka Chauhan, Matthew B. A. McDermott, Peter Szolovits
http://arxiv.org/abs/1906.08318v1
• [cs.CL]Robust Machine Translation with Domain Sensitive Pseudo-Sources: Baidu-OSU WMT19 MT Robustness Shared Task System Report
Renjie Zheng, Hairong Liu, Mingbo Ma, Baigong Zheng, Liang Huang
http://arxiv.org/abs/1906.08393v1
• [cs.CL]Semi-supervised acoustic model training for five-lingual code-switched ASR
Astik Biswas, Emre Yılmaz, Febe de Wet, Ewald van der Westhuizen, Thomas Niesler
http://arxiv.org/abs/1906.08647v1
• [cs.CR]Reversible Privacy Preservation using Multi-level Encryption and Compressive Sensing
Mehmet Yamac, Mete Ahishali, Nikolaos Passalis, Jenni Raitoharju, Bulent Sankur, Moncef Gabbouj
http://arxiv.org/abs/1906.08713v1
• [cs.CR]SoK of Used Cryptography in Blockchain
Mayank Raikwar, Danilo Gligoroski, Katina Kralevska
http://arxiv.org/abs/1906.08609v1
• [cs.CV]3D Instance Segmentation via Multi-task Metric Learning
Jean Lahoud, Bernard Ghanem, Marc Pollefeys, Martin R. Oswald
http://arxiv.org/abs/1906.08650v1
• [cs.CV]A Strong Baseline and Batch Normalization Neck for Deep Person Re-identification
Hao Luo, Wei Jiang, Youzhi Gu, Fuxu Liu, Xingyu Liao, Shenqi Lai, Jianyang Gu
http://arxiv.org/abs/1906.08332v1
• [cs.CV]Algorithmic Guarantees for Inverse Imaging with Untrained Network Priors
Gauri Jagatap, Chinmay Hegde
http://arxiv.org/abs/1906.08763v1
• [cs.CV]BGrowth: an efficient approach for the segmentation of vertebral compression fractures in magnetic resonance imaging
Jonathan S. Ramos, Carolina Y. V. Watanabe, Marcello H. Nogueira-Barbosa, Agma J. M. Traina
http://arxiv.org/abs/1906.08620v1
• [cs.CV]Deep-Learning-Based Aerial Image Classification for Emergency Response Applications Using Unmanned Aerial Vehicles
Christos Kyrkou, Theocharis Theocharides
http://arxiv.org/abs/1906.08716v1
• [cs.CV]From Zero-Shot Learning to Cold-Start Recommendation
v Li, Mengmeng Jing, Ke Lu, Lei Zhu, Yang Yang, Zi Huang
http://arxiv.org/abs/1906.08511v1
• [cs.CV]GAN-Knowledge Distillation for one-stage Object Detection
Wei Hong, Jingke Yu
http://arxiv.org/abs/1906.08467v1
• [cs.CV]Homogeneous Vector Capsules Enable Adaptive Gradient Descent in Convolutional Neural Networks
Adam Byerly, Tatiana Kalganova
http://arxiv.org/abs/1906.08676v1
• [cs.CV]Human \textit{vs} Machine Attention in Neural Networks: A Comparative Study
Qiuxia Lai, Wenguan Wang, Salman Khan, Jianbing Shen, Hanqiu Sun, Ling Shao
http://arxiv.org/abs/1906.08764v1
• [cs.CV]Improving the robustness of ImageNet classifiers using elements of human visual cognition
A. Emin Orhan, Brenden M. Lake
http://arxiv.org/abs/1906.08416v1
• [cs.CV]Learning Generalized Transformation Equivariant Representations via Autoencoding Transformations
Guo-Jun Qi
http://arxiv.org/abs/1906.08628v1
• [cs.CV]Let’s Take This Online: Adapting Scene Coordinate Regression Network Predictions for Online RGB-D Camera Relocalisation
Tommaso Cavallari, Luca Bertinetto, Jishnu Mukhoti, Philip Torr, Stuart Golodetz
http://arxiv.org/abs/1906.08744v1
• [cs.CV]Light Field Saliency Detection with Deep Convolutional Networks
Jun Zhang, Yamei Liu, Shengping Zhang, Ronald Poppe, Meng Wang
http://arxiv.org/abs/1906.08331v1
• [cs.CV]Model-based Deep MR Imaging: the roadmap of generalizing compressed sensing model using deep learning
Jing Cheng, Haifeng Wang, Yanjie Zhu, Qiegen Liu, Leslie Ying, Dong Liang
http://arxiv.org/abs/1906.08143v2
• [cs.CV]Monocular 3D Object Detection and Box Fitting Trained End-to-End Using Intersection-over-Union Loss
Eskil Jörgensen, Christopher Zach, Fredrik Kahl
http://arxiv.org/abs/1906.08070v2
• [cs.CV]Multiple-Identity Image Attacks Against Face-based Identity Verification
Jerone T. A. Andrews, Thomas Tanay, Lewis D. Griffin
http://arxiv.org/abs/1906.08507v1
• [cs.CV]Nested Network with Two-Stream Pyramid for Salient Object Detection in Optical Remote Sensing Images
Chongyi Li, Runmin Cong, Junhui Hou, Sanyi Zhang, Yue Qian, Sam Kwong
http://arxiv.org/abs/1906.08462v1
• [cs.CV]Pattern Spotting in Historical Documents Using Convolutional Models
Ignacio Úbeda, Jose M. Saavedra, Stéphane Nicolas, Caroline Petitjean, Laurent Heutte
http://arxiv.org/abs/1906.08580v1
• [cs.CV]Performance Evaluation Methodology for Long-Term Visual Object Tracking
Alan Lukežič, Luka Čehovin Zajc, Tomáš Vojíř, Jiří Matas, Matej Kristan
http://arxiv.org/abs/1906.08675v1
• [cs.CV]PointNLM: Point Nonlocal-Means for vegetation segmentation based on middle echo point clouds
Jonathan Li, Rongren Wu, Yiping Chen, Qing Zhu, Zhipeng Luo, Cheng Wang
http://arxiv.org/abs/1906.08476v1
• [cs.CV]Uncovering Why Deep Neural Networks Lack Robustness: Representation Metrics that Link to Adversarial Attacks
Danilo Vasconcellos Vargas, Shashank Kotyan, Moe Matsuki
http://arxiv.org/abs/1906.06627v2
• [cs.CV]vireoJD-MM at Activity Detection in Extended Videos
Fuchen Long, Qi Cai, Zhaofan Qiu, Zhijian Hou, Yingwei Pan, Ting Yao, Chong-Wah Ngo
http://arxiv.org/abs/1906.08547v1
• [cs.CY]Measuring the Importance of User-Generated Content to Search Engines
Nicholas Vincent, Isaac Johnson, Patrick Sheehan, Brent Hecht
http://arxiv.org/abs/1906.08576v1
• [cs.DC]Using Machine Learning to Optimize Web Interactions on Heterogeneous Mobile Multi-cores
Lu Yuan, Jie Ren, Ling Gao, Zhanyong Tang, Zheng Wang
http://arxiv.org/abs/1906.08689v1
• [cs.DL]Cleaning Noisy and Heterogeneous Metadata for Record Linking Across Scholarly Big Datasets
Athar Sefid, Jian Wu, Allen C. Ge, Jing Zhao, Lu Liu, Cornelia Caragea, Prasenjit Mitra, C. Lee Giles
http://arxiv.org/abs/1906.08470v1
• [cs.DS]Coresets for Clustering with Fairness Constraints
Lingxiao Huang, Shaofeng H. -C. Jiang, Nisheeth K. Vishnoi
http://arxiv.org/abs/1906.08484v1
• [cs.GT]Individual Fairness in Sponsored Search Auctions
Shuchi Chawla, Christina Ilvento, Meena Jagadeesan
http://arxiv.org/abs/1906.08732v1
• [cs.GT]Privacy, altruism, and experience: Estimating the perceived value of Internet data for medical uses
Gilie Gefen, Omer Ben-Porat, Moshe Tennenholtz, Elad Yom-Tov
http://arxiv.org/abs/1906.08562v1
• [cs.IR]Citizens’ Emotion on GST: A Spatio-Temporal Analysis over Twitter Data
Deepak Uniyal, Ankit Rai
http://arxiv.org/abs/1906.08693v1
• [cs.IT]Complex phase retrieval from subgaussian measurements
Felix Krahmer, Dominik Stöger
http://arxiv.org/abs/1906.08385v1
• [cs.IT]Joint Uplink and Downlink Transmissions in User-Centric OFDMA Cloud-RAN
Zehong Lin, Yuan Liu
http://arxiv.org/abs/1906.08490v1
• [cs.IT]Low Probability of Detection Communication: Opportunities and Challenges
Shihao Yan, Xiangyun Zhou, Jinsong Hu, Stephen V. Hanly
http://arxiv.org/abs/1906.07895v2
• [cs.IT]On the Dynamic Centralized Coded Caching Design
Qiaoling Zhang, Lei Zheng, Minquan Cheng, Qingchun Chen
http://arxiv.org/abs/1906.08539v1
• [cs.IT]Physical Layer Security for Ultra-Reliable and Low-Latency Communications
Riqing Chen, Chunhui Li, Shihao Yan, Robert Malaney, Jinhong Yuan
http://arxiv.org/abs/1906.08443v1
• [cs.LG]Accelerating Mini-batch SARAH by Step Size Rules
Zhuang Yang, Zengping Chen, Cheng Wang
http://arxiv.org/abs/1906.08496v1
• [cs.LG]Adversarial Regularization for Visual Question Answering: Strengths, Shortcomings, and Side Effects
Gabriel Grand, Yonatan Belinkov
http://arxiv.org/abs/1906.08430v1
• [cs.LG]An Improved Trade-off Between Accuracy and Complexity with Progressive Gradient Pruning
Le Thanh Nguyen-Meidine, Eric Granger, Madhu Kiran, Louis-Antoine Blais-Morin
http://arxiv.org/abs/1906.08746v1
• [cs.LG]Analyzing and Storing Network Intrusion Detection Data using Bayesian Coresets: A Preliminary Study in Offline and Streaming Settings
Fabio Massimo Zennaro
http://arxiv.org/abs/1906.08528v1
• [cs.LG]Back to Simplicity: How to Train Accurate BNNs from Scratch?
Joseph Bethge, Haojin Yang, Marvin Bornstein, Christoph Meinel
http://arxiv.org/abs/1906.08637v1
• [cs.LG]Bayesian Modelling in Practice: Using Uncertainty to Improve Trustworthiness in Medical Applications
David Ruhe, Giovanni Cinà, Michele Tonutti, Daan de Bruin, Paul Elbers
http://arxiv.org/abs/1906.08619v1
• [cs.LG]Beyond Supervised Classification: Extreme Minimal Supervision with the Graph 1-Laplacian
Angelica I. Aviles-Rivero, Nicolas Papadakis, Ruoteng Li, Samar M Alsaleh, Robby T Tan, Carola-Bibiane Schonlieb
http://arxiv.org/abs/1906.08635v1
• [cs.LG]Boosting for Dynamical Systems
Naman Agarwal, Nataly Brukhim, Elad Hazan, Zhou Lu
http://arxiv.org/abs/1906.08720v1
• [cs.LG]Calibrated Model-Based Deep Reinforcement Learning
Ali Malik, Volodymyr Kuleshov, Jiaming Song, Danny Nemer, Harlan Seymour, Stefano Ermon
http://arxiv.org/abs/1906.08312v1
• [cs.LG]Clustering and Classification Networks
Jin-mo Choi
http://arxiv.org/abs/1906.08714v1
• [cs.LG]Data Interpolating Prediction: Alternative Interpretation of Mixup
Takuya Shimada, Shoichiro Yamaguchi, Kohei Hayashi, Sosuke Kobayashi
http://arxiv.org/abs/1906.08412v1
• [cs.LG]Differentiable probabilistic models of scientific imaging with the Fourier slice theorem
Karen Ullrich, Rianne van den Berg, Marcus Brubaker, David Fleet, Max Welling
http://arxiv.org/abs/1906.07582v2
• [cs.LG]Disentangling Influence: Using Disentangled Representations to Audit Model Predictions
Charles T. Marx, Richard Lanas Phillips, Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian
http://arxiv.org/abs/1906.08652v1
• [cs.LG]Experience Replay Optimization
Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu
http://arxiv.org/abs/1906.08387v1
• [cs.LG]Exploring Model-based Planning with Policy Networks
Tingwu Wang, Jimmy Ba
http://arxiv.org/abs/1906.08649v1
• [cs.LG]GEAR: Geometry-Aware Rényi Information
Jose Gallego, Ankit Vani, Max Schwarzer, Simon Lacoste-Julien
http://arxiv.org/abs/1906.08325v1
• [cs.LG]ID3 Learns Juntas for Smoothed Product Distributions
Alon Brutzkus, Amit Daniely, Eran Malach
http://arxiv.org/abs/1906.08654v1
• [cs.LG]Inherent Tradeoffs in Learning Fair Representation
Han Zhao, Geoffrey J. Gordon
http://arxiv.org/abs/1906.08386v1
• [cs.LG]Learning Patient Engagement in Care Management: Performance vs. Interpretability
Subhro Das, Chandramouli Maduri, Ching-Hua Chen, Pei-Yun S. Hsueh
http://arxiv.org/abs/1906.08339v1
• [cs.LG]Max-Plus Matching Pursuit for Deterministic Markov Decision Processes
Francis Bach
http://arxiv.org/abs/1906.08524v1
• [cs.LG]Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning
Maizura Mokhtar, Valentin Robu, David Flynn, Ciaran Higgins, Jim Whyte, Caroline Loughran, Fiona Fulton
http://arxiv.org/abs/1906.08374v1
• [cs.LG]Preprocessing Methods and Pipelines of Data Mining: An Overview
Canchen Li
http://arxiv.org/abs/1906.08510v1
• [cs.LG]Probabilistic Logic Neural Networks for Reasoning
Meng Qu, Jian Tang
http://arxiv.org/abs/1906.08495v1
• [cs.LG]Regional based query in graph active learning
Roy Abel, Yoram Louzoun
http://arxiv.org/abs/1906.08541v1
• [cs.LG]Safe and Near-Optimal Policy Learning for Model Predictive Control using Primal-Dual Neural Networks
Xiaojing Zhang, Monimoy Bujarbaruah, Francesco Borrelli
http://arxiv.org/abs/1906.08257v1
• [cs.LG]Scalable and Differentially Private Distributed Aggregation in the Shuffled Model
Badih Ghazi, Rasmus Pagh, Ameya Velingker
http://arxiv.org/abs/1906.08320v1
• [cs.LG]Solver Recommendation For Transport Problems in Slabs Using Machine Learning
Jinzhao Chen, Japan K. Patel, Richard Vasques
http://arxiv.org/abs/1906.08259v1
• [cs.LG]Stochastic One-Sided Full-Information Bandit
Haoyu Zhao, Wei Chen
http://arxiv.org/abs/1906.08656v1
• [cs.LG]Submodular Batch Selection for Training Deep Neural Networks
K J Joseph, Vamshi Teja R, Krishnakant Singh, Vineeth N Balasubramanian
http://arxiv.org/abs/1906.08771v1
• [cs.LG]SwiftNet: Using Graph Propagation as Meta-knowledge to Search Highly Representative Neural Architectures
Hsin-Pai, Cheng, Tunhou Zhang, Yukun Yang, Feng Yan, Shiyu Li, Harris Teague, Hai, Li, Yiran Chen
http://arxiv.org/abs/1906.08305v1
• [cs.LG]The Functional Neural Process
Christos Louizos, Xiahan Shi, Klamer Schutte, Max Welling
http://arxiv.org/abs/1906.08324v1
• [cs.LG]The Limited Multi-Label Projection Layer
Brandon Amos, Vladlen Koltun, J. Zico Kolter
http://arxiv.org/abs/1906.08707v1
• [cs.LG]The trade-off between long-term memory and smoothness for recurrent networks
Antônio H. Ribeiro, Koen Tiels, Luis A. Aguirre, Thomas B. Schön
http://arxiv.org/abs/1906.08482v1
• [cs.LG]Training on test data: Removing near duplicates in Fashion-MNIST
Christopher Geier
http://arxiv.org/abs/1906.08255v1
• [cs.LG]Unleashing the Unused Potential of I-Vectors Enabled by GPU Acceleration
Ville Vestman, Kong Aik Lee, Tomi H. Kinnunen, Takafumi Koshinaka
http://arxiv.org/abs/1906.08556v1
• [cs.LG]We Need No Pixels: Video Manipulation Detection Using Stream Descriptors
David Güera, Sriram Baireddy, Paolo Bestagini, Stefano Tubaro, Edward J. Delp
http://arxiv.org/abs/1906.08743v1
• [cs.LO]Transformation of XML Documents with Prolog
René Haberland, Igor L. Bratchikov
http://arxiv.org/abs/1906.08361v1
• [cs.LO]Unification of Template-Expansion and XML-Validation
René Haberland
http://arxiv.org/abs/1906.08369v1
• [cs.MM]Understanding, Categorizing and Predicting Semantic Image-Text Relations
Christian Otto, Matthias Springstein, Avishek Anand, Ralph Ewerth
http://arxiv.org/abs/1906.08595v1
• [cs.MM]Zero-shot Learning and Knowledge Transfer in Music Classification and Tagging
Jeong Choi, Jongpil Lee, Jiyoung Park, Juhan Nam
http://arxiv.org/abs/1906.08615v1
• [cs.NE]testRNN: Coverage-guided Testing on Recurrent Neural Networks
Wei Huang, Youcheng Sun, Xiaowei Huang, James Sharp
http://arxiv.org/abs/1906.08557v1
• [cs.NI]A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art
Quoc-Viet Pham, Fang Fang, Vu Nguyen Ha, Mai Le, Zhiguo Ding, Long Bao Le, Won-Joo Hwang
http://arxiv.org/abs/1906.08452v1
• [cs.RO]2D Linear Time-Variant Controller for Human’s Intention Detection for Reach-to-Grasp Trajectories in Novel Scenes
Claudio Zito, Tomasz Deregowski, Rustam Stolkin
http://arxiv.org/abs/1906.08380v1
• [cs.RO]A Hierarchical Architecture for Sequential Decision-Making in Autonomous Driving using Deep Reinforcement Learning
Majid Moghadam, Gabriel Hugh Elkaim
http://arxiv.org/abs/1906.08464v1
• [cs.RO]An observable time series based SLAM algorithm for deforming environment
Jingwei Song, Liang Zhao, Shoudong Huang, Gamini Dissanayake
http://arxiv.org/abs/1906.08563v1
• [cs.RO]Efficient two step optimization for large embedded deformation graph based SLAM
Jingwei Song, Fang Bai, Liang Zhao, Shoudong Huang, Rong Xiong
http://arxiv.org/abs/1906.08477v1
• [cs.RO]Metrics and Benchmarks for Remote Shared Controllers in Industrial Applications
Claudio Zito, Maxime Adjigble, Brice D. Denoun, Lorenzo Jamone, Miles Hansard, Rustam Stolkin
http://arxiv.org/abs/1906.08381v1
• [cs.RO]Object Placement on Cluttered Surfaces: A Nested Local Search Approach
Abdul Rahman Dabbour, Esra Erdem, Volkan Patoglu
http://arxiv.org/abs/1906.08494v1
• [cs.RO]Predicting Motion of Vulnerable Road Users using High-Definition Maps and Efficient ConvNets
Fang-Chieh Chou, Tsung-Han Lin, Henggang Cui, Vladan Radosavljevic, Thi Nguyen, Tzu-Kuo Huang, Matthew Niedoba, Jeff Schneider, Nemanja Djuric
http://arxiv.org/abs/1906.08469v1
• [cs.RO]PuzzleFlex: kinematic motion of chains with loose joints
Samuel Lensgraf, Karim Itani, Yinan Zhang, Zezhou Sun, Yijia Wu, Alberto Quattrini Li, Bo Zhu, Emily Whiting, Weifu Wang, Devin Balkcom
http://arxiv.org/abs/1906.08708v1
• [cs.SD]A Monaural Speech Enhancement Method for Robust Small-Footprint Keyword Spotting
Yue Gu, Zhihao Du, Hui Zhang, Xueliang Zhang
http://arxiv.org/abs/1906.08415v1
• [cs.SD]Adversarial Learning for Improved Onsets and Frames Music Transcription
Jong Wook Kim, Juan Pablo Bello
http://arxiv.org/abs/1906.08512v1
• [cs.SE]ENCORE: Ensemble Learning using Convolution Neural Machine Translation for Automatic Program Repair
Thibaud Lutellier, Lawrence Pang, Viet Hung Pham, Moshi Wei, Lin Tan
http://arxiv.org/abs/1906.08691v1
• [cs.SI]A Graph Auto-Encoder for Attributed Network Embedding
Keting Cen, Huawei Shen, Jinhua Gao, Qi Cao, Bingbing Xu, Xueqi Cheng
http://arxiv.org/abs/1906.08745v1
• [cs.SI]Compressive Closeness in Networks
Hamidreza Mahyar, Rouzbeh Hasheminezhad, H Eugene Stanley
http://arxiv.org/abs/1906.08335v1
• [cs.SI]How the Avengers assemble: Ecological modelling of effective cast sizes for movies
Matthew Roughan, Lewis Mitchell, Tobin South
http://arxiv.org/abs/1906.08403v1
• [cs.SI]Understanding Filter Bubbles and Polarization in Social Networks
Uthsav Chitra, Christopher Musco
http://arxiv.org/abs/1906.08772v1
• [eess.AS]Spatial Pyramid Encoding with Convex Length Normalization for Text-Independent Speaker Verification
Youngmoon Jung, Younggwan Kim, Hyungjun Lim, Yeunju Choi, Hoirin Kim
http://arxiv.org/abs/1906.08333v1
• [eess.IV]A Segmentation-Oriented Inter-Class Transfer Method: Application to Retinal Vessel Segmentation
Chengzhi Shi, Jihong Liu, Dali Chen
http://arxiv.org/abs/1906.08501v1
• [eess.IV]Learning the Sampling Pattern for MRI
Ferdia Sherry, Martin Benning, Juan Carlos De los Reyes, Martin J. Graves, Georg Maierhofer, Guy Williams, Carola-Bibiane Schönlieb, Matthias J. Ehrhardt
http://arxiv.org/abs/1906.08754v1
• [eess.SP]Beam Entropy of 5G Cellular Millimetre-Wave Channels
Krishan Kumar Tiwari, Eckhard Grass, John S. Thompson, Rolf Kraemer
http://arxiv.org/abs/1906.07012v2
• [eess.SP]Multitaper Spectral Analysis of Neuronal Spiking Activity Driven by Latent Stationary Processes
Proloy Das, Behtash Babadi
http://arxiv.org/abs/1906.08451v1
• [eess.SY]Cooperative Lane Changing via Deep Reinforcement Learning
Guan Wang, Jianming Hu, Zhiheng Li, Li Li
http://arxiv.org/abs/1906.08662v1
• [math.NA]Sparse approximate matrix multiplication in a fully recursive distributed task-based parallel framework
Anton G. Artemov
http://arxiv.org/abs/1906.08148v2
• [math.OC]Global Convergence of Policy Gradient Methods to (Almost) Locally Optimal Policies
Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Başar
http://arxiv.org/abs/1906.08383v1
• [math.PR]First order covariance inequalities via Stein’s method
Marie Ernst, Gesine Reinert, Yvik Swan
http://arxiv.org/abs/1906.08372v1
• [math.PR]On infinite covariance expansions
Marie Ernst, Gesine Reinert, Yvik Swan
http://arxiv.org/abs/1906.08376v1
• [math.ST]Bounding the error of discretized Langevin algorithms for non-strongly log-concave targets
Arnak S. Dalalyan, Lionel Riou-Durand, Avetik Karagulyan
http://arxiv.org/abs/1906.08530v1
• [math.ST]Minimum Stein Discrepancy Estimators
Alessandro Barp, Francois-Xavier Briol, Andrew B. Duncan, Mark Girolami, Lester Mackey
http://arxiv.org/abs/1906.08283v1
• [math.ST]Optimal designs for estimating individual coefficients in polynomial regression with no intercept
Holger Dette, Viatcheslav B. Melas, Petr Shpilev
http://arxiv.org/abs/1906.08343v1
• [math.ST]Universality in Learning from Linear Measurements
Ehsan Abbasi, Fariborz Salehi, Babak Hassibi
http://arxiv.org/abs/1906.08396v1
• [physics.app-ph]Tomographic Reconstruction of Triaxial Strain Fields from Bragg-Edge Neutron Imaging
J. N. Hendriks, A. W. T. Gregg, R. R. Jackson, C. M. Wensrich, A. Wills, A. S. Tremsin, T. Shinohara, V. Luzin, O. Kirstein
http://arxiv.org/abs/1906.08506v1
• [physics.soc-ph]A network approach to cartel detection in public auction markets
Johannes Wachs, János Kertész
http://arxiv.org/abs/1906.08667v1
• [q-bio.NC]Extraction of hierarchical functional connectivity components in human brain using resting-state fMRI
Dushyant Sahoo, Christos Davatzikos, Danielle Bassett
http://arxiv.org/abs/1906.08365v1
• [q-bio.PE]On the use of multiple compartment epidemiological models to describe the dynamics of influenza in Europe
Inbar Seroussi, Nir Levy, Daniela Paolotti, Nir Sochen, Elad Yom-Tov
http://arxiv.org/abs/1906.08631v1
• [q-fin.ST]Investment Ranking Challenge: Identifying the best performing stocks based on their semi-annual returns
Shanka Subhra Mondal, Sharada Prasanna Mohanty, Benjamin Harlander, Mehmet Koseoglu, Lance Rane, Kirill Romanov, Wei-Kai Liu, Pranoot Hatwar, Marcel Salathe, Joe Byrum
http://arxiv.org/abs/1906.08636v1
• [stat.AP]An axiomatic nonparametric production function estimator: Modeling production in Japan’s cardboard industry
Daisuke Yagi, Yining Chen, Andrew L. Johnson, Hiroshi Morita
http://arxiv.org/abs/1906.08359v1
• [stat.AP]On Relative Ageing of Coherent Systems with Dependent Identically Distributed Components
Nil Kamal Hazra, Neeraj Misra
http://arxiv.org/abs/1906.08488v1
• [stat.AP]On the probability of a causal inference is robust for internal validity
Tenglong Li, Kenneth A. Frank
http://arxiv.org/abs/1906.08726v1
• [stat.AP]Ongoing Vaccine and Monoclonal Antibody HIV Prevention Efficacy Trials and Considerations for Sequel Efficacy Trial Designs
Peter B. Gilbert
http://arxiv.org/abs/1906.08409v1
• [stat.AP]Reliable data from low cost ozone sensors in a hierarchical network
Georgia Miskell, Kyle Alberti, Brandon Feenstra, Geoff S Henshaw, Vasileios Papapostolou, Hamesh Patel, Andrea Polidori, Jennifer A Salmond, Lena Weissert, David E Williams
http://arxiv.org/abs/1906.08421v1
• [stat.AP]Sequential Rank Shiryaev-Roberts CUSUMs
C van Zyl, F Lombard
http://arxiv.org/abs/1906.08755v1
• [stat.AP]Similarity indexing & GIS analysis of air pollution
Purusharth Saxena, Madhu Kashyap Jagdeesh
http://arxiv.org/abs/1906.08756v1
• [stat.CO]PLS Generalized Linear Regression and Kernel Multilogit Algorithm (KMA) for Microarray Data Classification
Adolphus Wagala, Graciela Gonzalez-Farıas, Rogelio Ramos, Oscar Dalmau
http://arxiv.org/abs/1906.08110v1
• [stat.ME]Bayesian spatial clustering of extremal behaviour for hydrological variables
Christian Rohrbeck, Jonathan A Tawn
http://arxiv.org/abs/1906.08522v1
• [stat.ME]Causal Inference from Possibly Unbalanced Split-Plot Designs: A Randomization-based Perspective
Rahul Mukerjee, Tirthankar Dasgupta
http://arxiv.org/abs/1906.08420v1
• [stat.ME]Improving estimation of the volume under the ROC surface when data are missing not at random
Duc-Khanh To, Gianfranco Adimari, Monica Chiogna
http://arxiv.org/abs/1906.08735v1
• [stat.ME]Improving the Accuracy of Confidence Intervals and Regions in Multivariate Random-effects Meta-analysis
Tsubasa Ito, Shonosuke Sugasawa
http://arxiv.org/abs/1906.08428v1
• [stat.ME]M-type penalized splines with auxiliary scale estimation
Ioannis Kalogridis, Stefan Van Aelst
http://arxiv.org/abs/1906.08577v1
• [stat.ME]Model-free posterior inference on the area under the receiver operating characteristic curve
Zhe Wang, Ryan Martin
http://arxiv.org/abs/1906.08296v1
• [stat.ME]On application of a response propensity model to estimation from web samples
Vladislav Beresovsky
http://arxiv.org/abs/1906.08444v1
• [stat.ME]Regression Analysis of Dependent Binary Data for Estimating Disease Etiology from Case-Control Studies
Zhenke Wu, Irena Chen
http://arxiv.org/abs/1906.08436v1
• [stat.ML]Active Linear Regression
Xavier Fontaine, Pierre Perrault, Vianney Perchet
http://arxiv.org/abs/1906.08509v1
• [stat.ML]Adversarial Self-Paced Learning for Mixture Models of Hawkes Processes
Dixin Luo, Hongteng Xu, Lawrence Carin
http://arxiv.org/abs/1906.08397v1
• [stat.ML]Data Cleansing for Models Trained with SGD
Satoshi Hara, Atsushi Nitanda, Takanori Maehara
http://arxiv.org/abs/1906.08473v1
• [stat.ML]Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup
Sebastian Goldt, Madhu S. Advani, Andrew M. Saxe, Florent Krzakala, Lenka Zdeborová
http://arxiv.org/abs/1906.08632v1
• [stat.ML]Efficient data augmentation using graph imputation neural networks
Indro Spinelli, Simone Scardapane, Michele Scarpiniti, Aurelio Uncini
http://arxiv.org/abs/1906.08502v1
• [stat.ML]Generalization error bounds for kernel matrix completion and extrapolation
Pere Giménez-Febrer, Alba Pagès-Zamora, Georgios B. Giannakis
http://arxiv.org/abs/1906.08770v1
• [stat.ML]Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities
Wei Qian, Yuqian Zhang, Yudong Chen
http://arxiv.org/abs/1906.06776v2
• [stat.ML]More Efficient Policy Learning via Optimal Retargeting
Nathan Kallus
http://arxiv.org/abs/1906.08611v1
• [stat.ML]Multi-resolution Multi-task Gaussian Processes
Oliver Hamelijnck, Theodoros Damoulas, Kangrui Wang, Mark Girolami
http://arxiv.org/abs/1906.08344v1
• [stat.ML]Screening Sinkhorn Algorithm for Regularized Optimal Transport
Mokhtar Z. Alaya, Maxime Bérar, Gilles Gasso, Alain Rakotomamonjy
http://arxiv.org/abs/1906.08540v1
• [stat.ML]Sequential Experimental Design for Transductive Linear Bandits
Tanner Fiez, Lalit Jain, Kevin Jamieson, Lillian Ratliff
http://arxiv.org/abs/1906.08399v1
• [stat.OT]Frequentist Inference without Repeated Sampling
Paul Vos, Don Holbert
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