cond-mat.stat-mech - 统计数学

    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.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.GR - 计算机图形学 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.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SD - 声音处理 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 econ.GN - 一般经济学 eess.IV - 图像与视频处理 eess.SP - 信号处理 math-ph - 数学物理 math.CO - 组合数学 math.OC - 优化与控制 math.ST - 统计理论 nlin.AO - 适应和自组织系统 physics.comp-ph - 计算物理学 q-bio.GN - 基因组学 q-bio.NC - 神经元与认知 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

    • [cond-mat.stat-mech]Learning Clustered Representation for Complex Free Energy Landscapes
    • [cs.AI]CoAPI: An Efficient Two-Phase Algorithm Using Core-Guided Over-Approximate Cover for Prime Compilation of Non-Clausal Formulae
    • [cs.AI]Exponential-Binary State-Space Search
    • [cs.AI]Zooming Cautiously: Linear-Memory Heuristic Search With Node Expansion Guarantees
    • [cs.CL]A Wind of Change: Detecting and Evaluating Lexical Semantic Change across Times and Domains
    • [cs.CL]Building a Production Model for Retrieval-Based Chatbots
    • [cs.CL]Compositional Questions Do Not Necessitate Multi-hop Reasoning
    • [cs.CL]Data-to-text Generation with Entity Modeling
    • [cs.CL]Improving Relation Extraction by Pre-trained Language Representations
    • [cs.CL]Learning Word Embeddings with Domain Awareness
    • [cs.CL]Matching the Blanks: Distributional Similarity for Relation Learning
    • [cs.CL]Multi-hop Reading Comprehension through Question Decomposition and Rescoring
    • [cs.CL]On the Compositionality Prediction of Noun Phrases using Poincaré Embeddings
    • [cs.CL]Preference-based Interactive Multi-Document Summarisation
    • [cs.CL]RankQA: Neural Question Answering with Answer Re-Ranking
    • [cs.CL]Semi-supervised Stochastic Multi-Domain Learning using Variational Inference
    • [cs.CL]Shared-Private Bilingual Word Embeddings for Neural Machine Translation
    • [cs.CL]Visually Grounded Neural Syntax Acquisition
    • [cs.CL]Word Embeddings for the Armenian Language: Intrinsic and Extrinsic Evaluation
    • [cs.CL]Word-based Domain Adaptation for Neural Machine Translation
    • [cs.CR]Privacy-Preserving Classification of Personal Text Messages with Secure Multi-Party Computation: An Application to Hate-Speech Detection
    • [cs.CV]An Artificial Intelligence-Based System for Nutrient Intake Assessment of Hospitalised Patients
    • [cs.CV]Anytime Lane-Level Intersection Estimation Based on Trajectories
    • [cs.CV]Conditional Neural Style Transfer with Peer-Regularized Feature Transform
    • [cs.CV]Context-driven Active and Incremental Activity Recognition
    • [cs.CV]Deep Spherical Quantization for Image Search
    • [cs.CV]Does Generative Face Completion Help Face Recognition?
    • [cs.CV]Ego-Pose Estimation and Forecasting as Real-Time PD Control
    • [cs.CV]Evolving Losses for Unlabeled Video Representation Learning
    • [cs.CV]Extracting Visual Knowledge from the Internet: Making Sense of Image Data
    • [cs.CV]Figure Captioning with Reasoning and Sequence-Level Training
    • [cs.CV]HPILN: A feature learning framework for cross-modality person re-identification
    • [cs.CV]Learning Classifier Synthesis for Generalized Few-Shot Learning
    • [cs.CV]Multi-scale guided attention for medical image segmentation
    • [cs.CV]Multimodal End-to-End Autonomous Driving
    • [cs.CV]NICO: A Dataset Towards Non-I.I.D. Image Classification
    • [cs.CV]OutdoorSent: Can Semantic Features Help Deep Learning in Sentiment Analysis of Outdoor Images?
    • [cs.CV]PseudoEdgeNet: Nuclei Segmentation only with Point Annotations
    • [cs.CV]Recognizing American Sign Language Manual Signs from RGB-D Videos
    • [cs.CV]Risky Action Recognition in Lane Change Video Clips using Deep Spatiotemporal Networks with Segmentation Mask Transfer
    • [cs.CV]Seeing Behind Things: Extending Semantic Segmentation to Occluded Regions
    • [cs.CV]Visual Person Understanding through Multi-Task and Multi-Dataset Learning
    • [cs.CY]Analyzing Social Media Data to Understand Consumers’ Information Needs on Dietary Supplements
    • [cs.CY]Prediction of Workplace Injuries
    • [cs.CY]Sidewalk and Toronto: Critical Systems Heuristics and the Smart City
    • [cs.CY]Unsupervised Temporal Clustering to Monitor the Performance of Alternative Fueling Infrastructure
    • [cs.CY]Updating the Wassenaar Debate Once Again: Surveillance, Intrusion Software, and Ambiguity
    • [cs.DB]A Tree Pattern Matching Algorithm for XML Queries with Structural Preferences
    • [cs.DC]Chauffeuring a Crashed Robot from a Disk
    • [cs.DC]Lightweight Parallel Foundations: a model-compliant communication layer
    • [cs.DC]Mr and Professor
    • [cs.DC]Tensor Processing Units for Financial Monte Carlo
    • [cs.DC]The Architectural Implications of Facebook’s DNN-based Personalized Recommendation
    • [cs.DC]The server is dead, long live the server: Rise of Serverless Computing, Overview of Current State and Future Trends in Research and Industry
    • [cs.DC]pCAMP: Performance Comparison of Machine Learning Packages on the Edges
    • [cs.GR]Coherent Point Drift Networks: Unsupervised Learning of Non-Rigid Point Set Registration
    • [cs.IR]Collaborating with Users in Proximity for Decentralized Mobile Recommender Systems
    • [cs.IR]Comprehensive Personalized Ranking Using One-Bit Comparison Data
    • [cs.IR]Context Attentive Document Ranking and Query Suggestion
    • [cs.IR]Cross-Modal Interaction Networks for Query-Based Moment Retrieval in Videos
    • [cs.IR]Learning to Recommend Third-Party Library Migration Opportunities at the API Level
    • [cs.IR]Quaternion Collaborative Filtering for Recommendation
    • [cs.IT]Active Deep Decoding of Linear Codes
    • [cs.IT]Beamforming Optimization for Wireless Network Aided by Intelligent Reflecting Surface with Discrete Phase Shifts
    • [cs.IT]Coding Theorems for Asynchronous Slepian-Wolf Coding Systems
    • [cs.IT]Joint Optimization of Cooperative Communication and Computation in Two-Way Relay MEC Systems
    • [cs.IT]Non-Linear Estimation of Convolutionally Encoded Sequences
    • [cs.IT]On typical encodings of multivariate ergodic sources
    • [cs.IT]Symbol Message Passing Decoding of Nonbinary Low-Density Parity-Check Codes
    • [cs.IT]Uniform Minors in Maximally Recoverable Codes
    • [cs.LG]A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation
    • [cs.LG]A cryptographic approach to black box adversarial machine learning
    • [cs.LG]A novel approach to model exploration for value function learning
    • [cs.LG]An Extensible Interactive Interface for Agent Design
    • [cs.LG]AutoGrow: Automatic Layer Growing in Deep Convolutional Networks
    • [cs.LG]Class-Conditional Compression and Disentanglement: Bridging the Gap between Neural Networks and Naive Bayes Classifiers
    • [cs.LG]Compressing RNNs for IoT devices by 15-38x using Kronecker Products
    • [cs.LG]Distributed Learning with Random Features
    • [cs.LG]Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms
    • [cs.LG]Early detection of sepsis utilizing deep learning on electronic health record event sequences
    • [cs.LG]Fighting Quantization Bias With Bias
    • [cs.LG]Globally-Aware Multiple Instance Classifier for Breast Cancer Screening
    • [cs.LG]Importance Weighted Adversarial Variational Autoencoders for Spike Inference from Calcium Imaging Data
    • [cs.LG]Inductive Bias of Gradient Descent based Adversarial Training on Separable Data
    • [cs.LG]Intention-aware Long Horizon Trajectory Prediction of Surrounding Vehicles using Dual LSTM Networks
    • [cs.LG]Labeled Graph Generative Adversarial Networks
    • [cs.LG]Learning Representations of Graph Data — A Survey
    • [cs.LG]Localizing Catastrophic Forgetting in Neural Networks
    • [cs.LG]Machine Learning and Visualization in Clinical Decision Support: Current State and Future Directions
    • [cs.LG]Mixed Strategy Game Model Against Data Poisoning Attacks
    • [cs.LG]Multi-modal Active Learning From Human Data: A Deep Reinforcement Learning Approach
    • [cs.LG]One-Shot Neural Architecture Search via Compressive Sensing
    • [cs.LG]Rectifying Classifier Chains for Multi-Label Classification
    • [cs.LG]Reinforcement Learning under Drift
    • [cs.LG]Relaxed Weight Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series
    • [cs.LG]Reliable Classification Explanations via Adversarial Attacks on Robust Networks
    • [cs.LG]Reliable Estimation of Individual Treatment Effect with Causal Information Bottleneck
    • [cs.LG]Resampling-based Assessment of Robustness to Distribution Shift for Deep Neural Networks
    • [cs.LG]Selfie: Self-supervised Pretraining for Image Embedding
    • [cs.LG]Worst-Case Regret Bounds for Exploration via Randomized Value Functions
    • [cs.NE]Deep Reinforcement Learning for Multi-objective Optimization
    • [cs.NE]Evolution of Hierarchical Structure & Reuse in iGEM Synthetic DNA Sequences
    • [cs.NE]Introducing languid particle dynamics to a selection of PSO variants
    • [cs.NE]Non-Differentiable Supervised Learning with Evolution Strategies and Hybrid Methods
    • [cs.NE]Stochasticity and Robustness in Spiking Neural Networks
    • [cs.NE]Training large-scale ANNs on simulated resistive crossbar arrays
    • [cs.NI]Optimized Deployment of Millimeter Wave Networks for In-venue Regions with Stochastic Users’ Orientation
    • [cs.RO]Active inference body perception and action for humanoid robots
    • [cs.RO]Combining Parameter Identification and Trajectory Optimization: Real-time Planning for Information Gain
    • [cs.RO]EVDodge: Embodied AI For High-Speed Dodging On A Quadrotor Using Event Cameras
    • [cs.RO]Key Ingredients of Self-Driving Cars
    • [cs.RO]Kinematic & Dynamic Analysis of the Human Upper Limb Using the Theory of Screws
    • [cs.RO]Object-Agnostic Suction Grasp Affordance Detection in Dense Cluster Using Self-Supervised Learning.docx
    • [cs.RO]Planning With Uncertain Specifications (PUnS)
    • [cs.RO]Towards navigation without precise localization: Weakly supervised learning of goal-directed navigation cost map
    • [cs.RO]Visual-Inertial Navigation: A Concise Review
    • [cs.SD]Audio tagging with noisy labels and minimal supervision
    • [cs.SI]A Statistical Density-Based Analysis of Graph Clustering Algorithm Performance
    • [cs.SI]Approximate Identification of the Optimal Epidemic Source in Complex Networks
    • [cs.SI]Degree-based Outlier Detection within IP Traffic Modelled as a Link Stream
    • [cs.SI]Diffusion on dynamic contact networks with indirect transmission links
    • [cs.SI]Indirect interactions influence contact network structure and diffusion dynamics
    • [cs.SI]Multidimensional Outlier Detection in Temporal Interaction Networks: An Application to Political Communication on Twitter
    • [cs.SI]Self-Activation Influence Maximization
    • [cs.SI]Towards Business Partnership Recommendation Using User Opinion on Facebook
    • [cs.SI]Zorro: A Model Agnostic System to Price Consumer Data
    • [econ.EM]A long short-term memory stochastic volatility model
    • [econ.GN]Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?
    • [eess.IV]A deep learning approach for automated detection of geographic atrophy from color fundus photographs
    • [eess.IV]Decompose-and-Integrate Learning for Multi-class Segmentation in Medical Images
    • [eess.IV]Deep Angular Embedding and Feature Correlation Attention for Breast MRI Cancer Analysis
    • [eess.IV]Deep Learning based Cephalometric Landmark Identification using Landmark-dependent Multi-scale Patches
    • [eess.IV]DeepBundle: Fiber Bundle Parcellation with Graph Convolution Neural Networks
    • [eess.SP]Deep Learning For Experimental Hybrid Terrestrial and Satellite Interference Management
    • [eess.SP]Intelligent Reflecting Surface Assisted Multi-User MISO Communication
    • [math-ph]Ihara Zeta Entropy
    • [math.CO]The ${[46,9,20]_2}$ code is unique
    • [math.OC]A Non-Asymptotic Analysis of Network Independence for Distributed Stochastic Gradient Descent
    • [math.ST]A novel characterization and new simple tests of multivariate independence using copulas
    • [math.ST]Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation
    • [math.ST]Correlation bounds, mixing and m-dependence under random time-varying network distances with an application to Cox-Processes
    • [math.ST]Enhancing Multi-model Inference with Natural Selection
    • [math.ST]Estimation with informative missing data in the low-rank model with random effects
    • [math.ST]Laws of large numbers for stochastic orders
    • [math.ST]Nonparametric volatility change detection
    • [math.ST]On the definition of informative vs. ignorable nuisance process
    • [math.ST]Robust subgaussian estimation of a mean vector in nearly linear time
    • [math.ST]Robustness and Tractability for Non-convex M-estimators
    • [math.ST]Transfer Learning for Nonparametric Classification: Minimax Rate and Adaptive Classifier
    • [nlin.AO]A method for the classification of chimera states of coupled oscillators and its application for creating a neural network information converter
    • [nlin.AO]Mutual Information and the Edge of Chaos in Reservoir Computers
    • [physics.comp-ph]Machine Learning Prediction of Accurate Atomization Energies of Organic Molecules from Low-Fidelity Quantum Chemical Calculations
    • [q-bio.GN]DOT: Gene-set analysis by combining decorrelated association statistics
    • [q-bio.NC]Association Between Intelligence and Cortical Thickness in Adolescents: Evidence from the ABCD Study
    • [q-bio.NC]Non-uniqueness phenomenon of object representation in modelling IT cortex by deep convolutional neural network (DCNN)
    • [quant-ph]Quantum Distributed Algorithm for the All-Pairs Shortest Path Problem in the CONGEST-CLIQUE Model
    • [stat.AP]A Bayesian approach for the analysis of error rate studies in forensic science
    • [stat.AP]An Inverse Optimization Approach to Measuring Clinical Pathway Concordance
    • [stat.AP]Fast Multi-resolution Segmentation for Nonstationary Hawkes Process Using Cumulants
    • [stat.AP]Modelling the spatial extent and severity of extreme European windstorms
    • [stat.AP]Probabilistic Structure Learning for EEG/MEG Source Imaging with Hierarchical Graph Prior
    • [stat.AP]Reconciling Hierarchical Forecasts via Bayes’ Rule
    • [stat.AP]Selecting Biomarkers for building optimal treatment selection rules using Kernel Machines
    • [stat.AP]The Political Significance of Social Penumbras
    • [stat.ME]Bayesian Wavelet-packet Historical Functional Linear Models
    • [stat.ME]Deep Compositional Spatial Models
    • [stat.ME]Inferring phenotypic trait evolution on large trees with many incomplete measurements
    • [stat.ME]Multivariate Conditional Transformation Models
    • [stat.ME]Robust real-time monitoring of high-dimensional data streams
    • [stat.ML]Automatic Reparameterisation of Probabilistic Programs
    • [stat.ML]Computing Exact Guarantees for Differential Privacy
    • [stat.ML]Detecting Out-of-Distribution Inputs to Deep Generative Models Using a Test for Typicality
    • [stat.ML]Disentangled State Space Representations
    • [stat.ML]Ensemble Pruning via Margin Maximization
    • [stat.ML]Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations
    • [stat.ML]Kernelized Capsule Networks
    • [stat.ML]Likelihood Ratios for Out-of-Distribution Detection
    • [stat.ML]On the Current State of Research in Explaining Ensemble Performance Using Margins
    • [stat.ML]One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers
    • [stat.ML]Online Graph-Based Change-Point Detection for High Dimensional Data
    • [stat.ML]Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP
    • [stat.ML]Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations
    • [stat.ML]Ranking and synchronization from pairwise measurements via SVD
    • [stat.ML]Recurrent Kernel Networks
    • [stat.ML]Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models
    • [stat.ML]Structured Variational Inference in Continuous Cox Process Models
    • [stat.ML]The Normalization Method for Alleviating Pathological Sharpness in Wide Neural Networks
    • [stat.ML]Vertex Classification on Weighted Networks

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

    • [cond-mat.stat-mech]Learning Clustered Representation for Complex Free Energy Landscapes
    Jun Zhang, Yao-Kun Lei, Xing Che, Zhen Zhang, Yi Isaac Yang, Yi Qin Gao
    http://arxiv.org/abs/1906.02852v1

    • [cs.AI]CoAPI: An Efficient Two-Phase Algorithm Using Core-Guided Over-Approximate Cover for Prime Compilation of Non-Clausal Formulae
    Weilin Luo, Hai Wan, Hongzhen Zhong, Ou Wei
    http://arxiv.org/abs/1906.03085v1

    • [cs.AI]Exponential-Binary State-Space Search
    Nathan Sturtevant, Malte Helmert
    http://arxiv.org/abs/1906.02912v1

    • [cs.AI]Zooming Cautiously: Linear-Memory Heuristic Search With Node Expansion Guarantees
    Laurent Orseau, Levi H. S. Lelis, Tor Lattimore
    http://arxiv.org/abs/1906.03242v1

    • [cs.CL]A Wind of Change: Detecting and Evaluating Lexical Semantic Change across Times and Domains
    Dominik Schlechtweg, Anna Hätty, Marco del Tredici, Sabine Schulte im Walde
    http://arxiv.org/abs/1906.02979v1

    • [cs.CL]Building a Production Model for Retrieval-Based Chatbots
    Kyle Swanson, Lili Yu, Christopher Fox, Jeremy Wohlwend, Tao Lei
    http://arxiv.org/abs/1906.03209v1

    • [cs.CL]Compositional Questions Do Not Necessitate Multi-hop Reasoning
    Sewon Min, Eric Wallace, Sameer Singh, Matt Gardner, Hannaneh Hajishirzi, Luke Zettlemoyer
    http://arxiv.org/abs/1906.02900v1

    • [cs.CL]Data-to-text Generation with Entity Modeling
    Ratish Puduppully, Li Dong, Mirella Lapata
    http://arxiv.org/abs/1906.03221v1

    • [cs.CL]Improving Relation Extraction by Pre-trained Language Representations
    Christoph Alt, Marc Hübner, Leonhard Hennig
    http://arxiv.org/abs/1906.03088v1

    • [cs.CL]Learning Word Embeddings with Domain Awareness
    Guoyin Wang, Yan Song, Dong Yu
    http://arxiv.org/abs/1906.03249v1

    • [cs.CL]Matching the Blanks: Distributional Similarity for Relation Learning
    Livio Baldini Soares, Nicholas FitzGerald, Jeffrey Ling, Tom Kwiatkowski
    http://arxiv.org/abs/1906.03158v1

    • [cs.CL]Multi-hop Reading Comprehension through Question Decomposition and Rescoring
    Sewon Min, Victor Zhong, Luke Zettlemoyer, Hannaneh Hajishirzi
    http://arxiv.org/abs/1906.02916v1

    • [cs.CL]On the Compositionality Prediction of Noun Phrases using Poincaré Embeddings
    Abhik Jana, Dmitry Puzyrev, Alexander Panchenko, Pawan Goyal, Chris Biemann, Animesh Mukherjee
    http://arxiv.org/abs/1906.03007v1

    • [cs.CL]Preference-based Interactive Multi-Document Summarisation
    Yang Gao, Christian M. Meyer, Iryna Gurevych
    http://arxiv.org/abs/1906.02923v1

    • [cs.CL]RankQA: Neural Question Answering with Answer Re-Ranking
    Bernhard Kratzwald, Anna Eigenmann, Stefan Feuerriegel
    http://arxiv.org/abs/1906.03008v1

    • [cs.CL]Semi-supervised Stochastic Multi-Domain Learning using Variational Inference
    Yitong Li, Timothy Baldwin, Trevor Cohn
    http://arxiv.org/abs/1906.02897v1

    • [cs.CL]Shared-Private Bilingual Word Embeddings for Neural Machine Translation
    Xuebo Liu, Derek F. Wong, Yang Liu, Lidia S. Chao, Tong Xiao, Jingbo Zhu
    http://arxiv.org/abs/1906.03100v1

    • [cs.CL]Visually Grounded Neural Syntax Acquisition
    Haoyue Shi, Jiayuan Mao, Kevin Gimpel, Karen Livescu
    http://arxiv.org/abs/1906.02890v1

    • [cs.CL]Word Embeddings for the Armenian Language: Intrinsic and Extrinsic Evaluation
    Karen Avetisyan, Tsolak Ghukasyan
    http://arxiv.org/abs/1906.03134v1

    • [cs.CL]Word-based Domain Adaptation for Neural Machine Translation
    Shen Yan, Leonard Dahlmann, Pavel Petrushkov, Sanjika Hewavitharana, Shahram Khadivi
    http://arxiv.org/abs/1906.03129v1

    • [cs.CR]Privacy-Preserving Classification of Personal Text Messages with Secure Multi-Party Computation: An Application to Hate-Speech Detection
    Martine De Cock, Rafael Dowsley, Anderson C. A. Nascimento, Devin Reich, Ariel Todoki
    http://arxiv.org/abs/1906.02325v1

    • [cs.CV]An Artificial Intelligence-Based System for Nutrient Intake Assessment of Hospitalised Patients
    Ya Lu, Thomai Stathopoulou, Maria F. Vasiloglou, Stergios Christodoulidis, Beat Blum, Thomas Walser, Vinzenz Meier, Zeno Stanga, Stavroula G. Mougiakakou
    http://arxiv.org/abs/1906.02990v1

    • [cs.CV]Anytime Lane-Level Intersection Estimation Based on Trajectories
    Annika Meyer, Jonas Walter, Martin Lauer, Christoph Stiller
    http://arxiv.org/abs/1906.02495v1

    • [cs.CV]Conditional Neural Style Transfer with Peer-Regularized Feature Transform
    Jan Svoboda, Asha Anoosheh, Christian Osendorfer, Jonathan Masci
    http://arxiv.org/abs/1906.02913v1

    • [cs.CV]Context-driven Active and Incremental Activity Recognition
    Gabriele Civitarese, Riccardo Presotto, Claudio Bettini
    http://arxiv.org/abs/1906.03033v1

    • [cs.CV]Deep Spherical Quantization for Image Search
    Sepehr Eghbali, Ladan Tahvildari
    http://arxiv.org/abs/1906.02865v1

    • [cs.CV]Does Generative Face Completion Help Face Recognition?
    Joe Mathai, Iacopo Masi, Wael AbdAlmageed
    http://arxiv.org/abs/1906.02858v1

    • [cs.CV]Ego-Pose Estimation and Forecasting as Real-Time PD Control
    Ye Yuan, Kris Kitani
    http://arxiv.org/abs/1906.03173v1

    • [cs.CV]Evolving Losses for Unlabeled Video Representation Learning
    AJ Piergiovanni, Anelia Angelova, Michael S. Ryoo
    http://arxiv.org/abs/1906.03248v1

    • [cs.CV]Extracting Visual Knowledge from the Internet: Making Sense of Image Data
    Yazhou Yao, Jian Zhang, Xiansheng Hua, Fumin Shen, Zhenmin Tang
    http://arxiv.org/abs/1906.03219v1

    • [cs.CV]Figure Captioning with Reasoning and Sequence-Level Training
    Charles Chen, Ruiyi Zhang, Eunyee Koh, Sungchul Kim, Scott Cohen, Tong Yu, Ryan Rossi, Razvan Bunescu
    http://arxiv.org/abs/1906.02850v1

    • [cs.CV]HPILN: A feature learning framework for cross-modality person re-identification
    Jian-Wu Lin, Hao Li
    http://arxiv.org/abs/1906.03142v1

    • [cs.CV]Learning Classifier Synthesis for Generalized Few-Shot Learning
    Han-Jia Ye, Hexiang Hu, De-Chuan Zhan, Fei Sha
    http://arxiv.org/abs/1906.02944v1

    • [cs.CV]Multi-scale guided attention for medical image segmentation
    Ashish Sinha, Jose Dolz
    http://arxiv.org/abs/1906.02849v1

    • [cs.CV]Multimodal End-to-End Autonomous Driving
    Yi Xiao, Felipe Codevilla, Akhil Gurram, Onay Urfalioglu, Antonio M. López
    http://arxiv.org/abs/1906.03199v1

    • [cs.CV]NICO: A Dataset Towards Non-I.I.D. Image Classification
    Yue He, Zheyan Shen, Peng Cui
    http://arxiv.org/abs/1906.02899v1

    • [cs.CV]OutdoorSent: Can Semantic Features Help Deep Learning in Sentiment Analysis of Outdoor Images?
    Wyverson B. de Oliveira, Leyza B. Dorini, Rodrigo Minetto, Thiago H. Silva
    http://arxiv.org/abs/1906.02331v1

    • [cs.CV]PseudoEdgeNet: Nuclei Segmentation only with Point Annotations
    Inwan Yoo, Donggeun Yoo, Kyunghyun Paeng
    http://arxiv.org/abs/1906.02924v1

    • [cs.CV]Recognizing American Sign Language Manual Signs from RGB-D Videos
    Longlong Jing, Elahe Vahdani, Matt Huenerfauth, Yingli Tian
    http://arxiv.org/abs/1906.02851v1

    • [cs.CV]Risky Action Recognition in Lane Change Video Clips using Deep Spatiotemporal Networks with Segmentation Mask Transfer
    Ekim Yurtsever, Yongkang Liu, Jacob Lambert, Chiyomi Miyajima, Eijiro Takeuchi, Kazuya Takeda, John H. L. Hansen
    http://arxiv.org/abs/1906.02859v1

    • [cs.CV]Seeing Behind Things: Extending Semantic Segmentation to Occluded Regions
    Pulak Purkait, Christopher Zach, Ian Reid
    http://arxiv.org/abs/1906.02885v1

    • [cs.CV]Visual Person Understanding through Multi-Task and Multi-Dataset Learning
    Kilian Pfeiffer, Alexander Hermans, István Sárándi, Mark Weber, Bastian Leibe
    http://arxiv.org/abs/1906.03019v1

    • [cs.CY]Analyzing Social Media Data to Understand Consumers’ Information Needs on Dietary Supplements
    Rubina F. Rizvi, Yefeng Wang, Thao Nguyen, Jake Vasilakes, Jiang Bian, Zhe He, Rui Zhang
    http://arxiv.org/abs/1906.03171v1

    • [cs.CY]Prediction of Workplace Injuries
    Mehdi Sadeqi, Azin Asgarian, Ariel Sibilia
    http://arxiv.org/abs/1906.03080v1

    • [cs.CY]Sidewalk and Toronto: Critical Systems Heuristics and the Smart City
    Curtis McCord, Christoph Becker
    http://arxiv.org/abs/1906.02266v1

    • [cs.CY]Unsupervised Temporal Clustering to Monitor the Performance of Alternative Fueling Infrastructure
    Kalai Ramea
    http://arxiv.org/abs/1906.03077v1

    • [cs.CY]Updating the Wassenaar Debate Once Again: Surveillance, Intrusion Software, and Ambiguity
    Jukka Ruohonen, Kai Kimppa
    http://arxiv.org/abs/1906.02235v1

    • [cs.DB]A Tree Pattern Matching Algorithm for XML Queries with Structural Preferences
    Maurice Tchoupé Tchendji, Lionel Tadonfouet, Thomas Tébougang Tchendji
    http://arxiv.org/abs/1906.03053v1

    • [cs.DC]Chauffeuring a Crashed Robot from a Disk
    Debasish Pattanayak, H. Ramesh, Partha Sarathi Mandal
    http://arxiv.org/abs/1906.03024v1

    • [cs.DC]Lightweight Parallel Foundations: a model-compliant communication layer
    Wijnand Suijlen, A. N. Yzelman
    http://arxiv.org/abs/1906.03196v1

    • [cs.DC]Mr and Professor
    Tosin P. Adewumi, Marcus Liwicki
    http://arxiv.org/abs/1906.02770v1

    • [cs.DC]Tensor Processing Units for Financial Monte Carlo
    Francois Belletti, Davis King, Kun Yang, Roland Nelet, Yusef Shafi, Yi-Fan Chen, John Anderson
    http://arxiv.org/abs/1906.02818v1

    • [cs.DC]The Architectural Implications of Facebook’s DNN-based Personalized Recommendation
    Udit Gupta, Xiaodong Wang, Maxim Naumov, Carole-Jean Wu, Brandon Reagen, David Brooks, Bradford Cottel, Kim Hazelwood, Bill Jia, Hsien-Hsin S. Lee, Andrey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, Xuan Zhang
    http://arxiv.org/abs/1906.03109v1

    • [cs.DC]The server is dead, long live the server: Rise of Serverless Computing, Overview of Current State and Future Trends in Research and Industry
    Paul Castro, Vatche Ishakian, Vinod Muthusamy, Aleksander Slominski
    http://arxiv.org/abs/1906.02888v1

    • [cs.DC]pCAMP: Performance Comparison of Machine Learning Packages on the Edges
    Xingzhou Zhang, Yifan Wang, Weisong Shi
    http://arxiv.org/abs/1906.01878v2

    • [cs.GR]Coherent Point Drift Networks: Unsupervised Learning of Non-Rigid Point Set Registration
    Lingjing Wang, Yi Fang
    http://arxiv.org/abs/1906.03039v1

    • [cs.IR]Collaborating with Users in Proximity for Decentralized Mobile Recommender Systems
    Felix Beierle, Tobias Eichinger
    http://arxiv.org/abs/1906.03114v1

    • [cs.IR]Comprehensive Personalized Ranking Using One-Bit Comparison Data
    Aria Ameri, Arindam Bose, Mojtaba Soltanalian
    http://arxiv.org/abs/1906.02408v1

    • [cs.IR]Context Attentive Document Ranking and Query Suggestion
    Wasi Uddin Ahmad, Kai-Wei Chang, Hongning Wang
    http://arxiv.org/abs/1906.02329v1

    • [cs.IR]Cross-Modal Interaction Networks for Query-Based Moment Retrieval in Videos
    Zhu Zhang, Zhijie Lin, Zhou Zhao, Zhenxin Xiao
    http://arxiv.org/abs/1906.02497v1

    • [cs.IR]Learning to Recommend Third-Party Library Migration Opportunities at the API Level
    Hussein Alrubaye, Mohamed Wiem Mkaouer, Igor Khokhlov, Leon Reznik, Ali Ouni, Jason Mcgoff
    http://arxiv.org/abs/1906.02882v1

    • [cs.IR]Quaternion Collaborative Filtering for Recommendation
    Shuai Zhang, Lina Yao, Lucas Vinh Tran, Aston Zhang, Yi Tay
    http://arxiv.org/abs/1906.02594v1

    • [cs.IT]Active Deep Decoding of Linear Codes
    Ishay Be’ery, Nir Raviv, Tomer Raviv, Yair Be’ery
    http://arxiv.org/abs/1906.02778v1

    • [cs.IT]Beamforming Optimization for Wireless Network Aided by Intelligent Reflecting Surface with Discrete Phase Shifts
    Qingqing Wu, Rui Zhang
    http://arxiv.org/abs/1906.03165v1

    • [cs.IT]Coding Theorems for Asynchronous Slepian-Wolf Coding Systems
    Tetsunao Matsuta, Tomohiko Uyematsu
    http://arxiv.org/abs/1906.02929v1

    • [cs.IT]Joint Optimization of Cooperative Communication and Computation in Two-Way Relay MEC Systems
    Biyuan Xie, Qi Zhang, Jiayin Qin
    http://arxiv.org/abs/1906.02450v1

    • [cs.IT]Non-Linear Estimation of Convolutionally Encoded Sequences
    Masato Tajima
    http://arxiv.org/abs/1906.02377v1

    • [cs.IT]On typical encodings of multivariate ergodic sources
    Michal Kupsa
    http://arxiv.org/abs/1906.02570v1

    • [cs.IT]Symbol Message Passing Decoding of Nonbinary Low-Density Parity-Check Codes
    Francisco Lázaro, Alexandre Graell i Amat, Gianluigi Liva, Balázs Matuz
    http://arxiv.org/abs/1906.02537v1

    • [cs.IT]Uniform Minors in Maximally Recoverable Codes
    Matthias Grezet, Thomas Westerbäck, Ragnar Freij-Hollanti, Camilla Hollanti
    http://arxiv.org/abs/1906.02423v1

    • [cs.LG]A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation
    Varun Khare, Divyat Mahajan, Homanga Bharadhwaj, Vinay Verma, Piyush Rai
    http://arxiv.org/abs/1906.03038v1

    • [cs.LG]A cryptographic approach to black box adversarial machine learning
    Kevin Shi, Daniel Hsu, Allison Bishop
    http://arxiv.org/abs/1906.03231v1

    • [cs.LG]A novel approach to model exploration for value function learning
    Zlatan Ajanovic, Halil Beglerovic, Bakir Lacevic
    http://arxiv.org/abs/1906.02789v1

    • [cs.LG]An Extensible Interactive Interface for Agent Design
    Matthew Rahtz, James Fang, Anca D. Dragan, Dylan Hadfield-Menell
    http://arxiv.org/abs/1906.02641v1

    • [cs.LG]AutoGrow: Automatic Layer Growing in Deep Convolutional Networks
    Wei Wen, Feng Yan, Hai Li
    http://arxiv.org/abs/1906.02909v1

    • [cs.LG]Class-Conditional Compression and Disentanglement: Bridging the Gap between Neural Networks and Naive Bayes Classifiers
    Rana Ali Amjad, Bernhard C. Geiger
    http://arxiv.org/abs/1906.02576v1

    • [cs.LG]Compressing RNNs for IoT devices by 15-38x using Kronecker Products
    Urmish Thakker, Jesse Beu, Dibakar Gope, Chu Zhou, Igor Fedorov, Ganesh Dasika, Matthew Mattina
    http://arxiv.org/abs/1906.02876v1

    • [cs.LG]Distributed Learning with Random Features
    Jian Li, Yong Liu, Weiping Wang
    http://arxiv.org/abs/1906.03155v1

    • [cs.LG]Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms
    Xiangyi Chen, Tiancong Chen, Haoran Sun, Zhiwei Steven Wu, Mingyi Hong
    http://arxiv.org/abs/1906.01736v2

    • [cs.LG]Early detection of sepsis utilizing deep learning on electronic health record event sequences
    Simon Meyer Lauritsen, Mads Ellersgaard Kalør, Emil Lund Kongsgaard, Katrine Meyer Lauritsen, Marianne Johansson Jørgensen, Jeppe Lange, Bo Thiesson
    http://arxiv.org/abs/1906.02956v1

    • [cs.LG]Fighting Quantization Bias With Bias
    Alexander Finkelstein, Uri Almog, Mark Grobman
    http://arxiv.org/abs/1906.03193v1

    • [cs.LG]Globally-Aware Multiple Instance Classifier for Breast Cancer Screening
    Yiqiu Shen, Nan Wu, Jason Phang, Jungkyu Park, Gene Kim, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras
    http://arxiv.org/abs/1906.02846v1

    • [cs.LG]Importance Weighted Adversarial Variational Autoencoders for Spike Inference from Calcium Imaging Data
    Daniel Jiwoong Im, Sridhama Prakhya, Jinyao Yan, Srinivas Turaga, Kristin Branson
    http://arxiv.org/abs/1906.03214v1

    • [cs.LG]Inductive Bias of Gradient Descent based Adversarial Training on Separable Data
    Yan Li, Ethan X. Fang, Huan Xu, Tuo Zhao
    http://arxiv.org/abs/1906.02931v1

    • [cs.LG]Intention-aware Long Horizon Trajectory Prediction of Surrounding Vehicles using Dual LSTM Networks
    Long Xin, Pin Wang, Ching-Yao Chan, Jianyu Chen, Shengbo Eben Li, Bo Cheng
    http://arxiv.org/abs/1906.02815v1

    • [cs.LG]Labeled Graph Generative Adversarial Networks
    Shuangfei Fan, Bert Huang
    http://arxiv.org/abs/1906.03220v1

    • [cs.LG]Learning Representations of Graph Data — A Survey
    Mital Kinderkhedia
    http://arxiv.org/abs/1906.02989v1

    • [cs.LG]Localizing Catastrophic Forgetting in Neural Networks
    Felix Wiewel, Bin Yang
    http://arxiv.org/abs/1906.02568v1

    • [cs.LG]Machine Learning and Visualization in Clinical Decision Support: Current State and Future Directions
    Gal Levy-Fix, Gilad J. Kuperman, Noémie Elhadad
    http://arxiv.org/abs/1906.02664v1

    • [cs.LG]Mixed Strategy Game Model Against Data Poisoning Attacks
    Yifan Ou, Reza Samavi
    http://arxiv.org/abs/1906.02872v1

    • [cs.LG]Multi-modal Active Learning From Human Data: A Deep Reinforcement Learning Approach
    Ognjen Rudovic, Meiru Zhang, Bjorn Schuller, Rosalind W. Picard
    http://arxiv.org/abs/1906.03098v1

    • [cs.LG]One-Shot Neural Architecture Search via Compressive Sensing
    Minsu Cho, Mohammadreza Soltani, Chinmay Hegde
    http://arxiv.org/abs/1906.02869v1

    • [cs.LG]Rectifying Classifier Chains for Multi-Label Classification
    Robin Senge, Juan José del Coz, Eyke Hüllermeier
    http://arxiv.org/abs/1906.02915v1

    • [cs.LG]Reinforcement Learning under Drift
    Wang Chi Cheung, David Simchi-Levi, Ruihao Zhu
    http://arxiv.org/abs/1906.02922v1

    • [cs.LG]Relaxed Weight Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series
    Jeeheh Oh, Jiaxuan Wang, Shengpu Tang, Michael Sjoding, Jenna Wiens
    http://arxiv.org/abs/1906.02898v1

    • [cs.LG]Reliable Classification Explanations via Adversarial Attacks on Robust Networks
    Walt Woods, Jack Chen, Christof Teuscher
    http://arxiv.org/abs/1906.02896v1

    • [cs.LG]Reliable Estimation of Individual Treatment Effect with Causal Information Bottleneck
    Sungyub Kim, Yongsu Baek, Sung Ju Hwang, Eunho Yang
    http://arxiv.org/abs/1906.03118v1

    • [cs.LG]Resampling-based Assessment of Robustness to Distribution Shift for Deep Neural Networks
    Xudong Sun, Yu Wang, Alexej Gossmann, Bernd Bischl
    http://arxiv.org/abs/1906.02972v1

    • [cs.LG]Selfie: Self-supervised Pretraining for Image Embedding
    Trieu H. Trinh, Minh-Thang Luong, Quoc V. Le
    http://arxiv.org/abs/1906.02940v1

    • [cs.LG]Worst-Case Regret Bounds for Exploration via Randomized Value Functions
    Daniel Russo
    http://arxiv.org/abs/1906.02870v1

    • [cs.NE]Deep Reinforcement Learning for Multi-objective Optimization
    Kaiwen Li, Tao Zhang, Rui Wang
    http://arxiv.org/abs/1906.02386v1

    • [cs.NE]Evolution of Hierarchical Structure & Reuse in iGEM Synthetic DNA Sequences
    Payam Siyari, Bistra Dilkina, Constantine Dovrolis
    http://arxiv.org/abs/1906.02446v1

    • [cs.NE]Introducing languid particle dynamics to a selection of PSO variants
    Siniša Družeta, Stefan Ivić, Luka Grbčić, Ivana Lučin
    http://arxiv.org/abs/1906.02474v1

    • [cs.NE]Non-Differentiable Supervised Learning with Evolution Strategies and Hybrid Methods
    Karel Lenc, Erich Elsen, Tom Schaul, Karen Simonyan
    http://arxiv.org/abs/1906.03139v1

    • [cs.NE]Stochasticity and Robustness in Spiking Neural Networks
    Wilkie Olin-Ammentorp, Karsten Beckmann, Catherine D. Schuman, James S. Plank, Nathaniel C. Cady
    http://arxiv.org/abs/1906.02796v1

    • [cs.NE]Training large-scale ANNs on simulated resistive crossbar arrays
    Malte J. Rasch, Tayfun Gokmen, Wilfried Haensch
    http://arxiv.org/abs/1906.02698v1

    • [cs.NI]Optimized Deployment of Millimeter Wave Networks for In-venue Regions with Stochastic Users’ Orientation
    Mehdi Naderi Soorki, Walid Saad, Mehdi Bennis
    http://arxiv.org/abs/1906.02491v1

    • [cs.RO]Active inference body perception and action for humanoid robots
    Guillermo Oliver, Pablo Lanillos, Gordon Cheng
    http://arxiv.org/abs/1906.03022v1

    • [cs.RO]Combining Parameter Identification and Trajectory Optimization: Real-time Planning for Information Gain
    Keenan Albee, Monica Ekal, Rodrigo Ventura, Richard Linares
    http://arxiv.org/abs/1906.02758v1

    • [cs.RO]EVDodge: Embodied AI For High-Speed Dodging On A Quadrotor Using Event Cameras
    Nitin J. Sanket, Chethan M. Parameshwara, Chahat Deep Singh, Ashwin V. Kuruttukulam, Cornelia Fermüller, Davide Scaramuzza, Yiannis Aloimonos
    http://arxiv.org/abs/1906.02919v1

    • [cs.RO]Key Ingredients of Self-Driving Cars
    Rui Fan, Jianhao Jiao, Haoyang Ye, Yang Yu, Ioannis Pitas, Ming Liu
    http://arxiv.org/abs/1906.02939v1

    • [cs.RO]Kinematic & Dynamic Analysis of the Human Upper Limb Using the Theory of Screws
    Amir Ziai
    http://arxiv.org/abs/1906.02458v1

    • [cs.RO]Object-Agnostic Suction Grasp Affordance Detection in Dense Cluster Using Self-Supervised Learning.docx
    Mingshuo Han, Wenhai Liu., Zhenyu Pan, Teng Xue, Quanquan Shao, Jin Ma, Weiming Wang
    http://arxiv.org/abs/1906.02995v1

    • [cs.RO]Planning With Uncertain Specifications (PUnS)
    Ankit Shah, Shen Li, Julie Shah
    http://arxiv.org/abs/1906.03218v1

    • [cs.RO]Towards navigation without precise localization: Weakly supervised learning of goal-directed navigation cost map
    Huifang Ma, Yue Wang, Li Tang, Sarath Kodagoda, Rong Xiong
    http://arxiv.org/abs/1906.02468v1

    • [cs.RO]Visual-Inertial Navigation: A Concise Review
    Guoquan Huang
    http://arxiv.org/abs/1906.02650v1

    • [cs.SD]Audio tagging with noisy labels and minimal supervision
    Eduardo Fonseca, Manoj Plakal, Frederic Font, Daniel P. W. Ellis, Xavier Serra
    http://arxiv.org/abs/1906.02975v1

    • [cs.SI]A Statistical Density-Based Analysis of Graph Clustering Algorithm Performance
    Pierre Miasnikof, Alexander Y. Shestopaloff, Anthony J. Bonner, Yuri Lawryshyn, Panos M. Pardalos
    http://arxiv.org/abs/1906.02366v1

    • [cs.SI]Approximate Identification of the Optimal Epidemic Source in Complex Networks
    S. Jalil Kazemitabar, Arash A. Amini
    http://arxiv.org/abs/1906.03052v1

    • [cs.SI]Degree-based Outlier Detection within IP Traffic Modelled as a Link Stream
    Audrey Wilmet, Tiphaine Viard, Matthieu Latapy, Robin Lamarche-Perrin
    http://arxiv.org/abs/1906.02524v1

    • [cs.SI]Diffusion on dynamic contact networks with indirect transmission links
    Md Shahzamal
    http://arxiv.org/abs/1906.02856v1

    • [cs.SI]Indirect interactions influence contact network structure and diffusion dynamics
    Md Shahzamal, Raja Jurdak, Bernard Mans, Frank de Hoog
    http://arxiv.org/abs/1906.02405v1

    • [cs.SI]Multidimensional Outlier Detection in Temporal Interaction Networks: An Application to Political Communication on Twitter
    Audrey Wilmet, Robin Lamarche-Perrin
    http://arxiv.org/abs/1906.02541v1

    • [cs.SI]Self-Activation Influence Maximization
    Lichao Sun, Albert Chen, Philip S. Yu, Wei Chen
    http://arxiv.org/abs/1906.02296v1

    • [cs.SI]Towards Business Partnership Recommendation Using User Opinion on Facebook
    Diego P. Tsutsumi, Amanda Fenerich, Thiago H. Silva
    http://arxiv.org/abs/1906.02338v1

    • [cs.SI]Zorro: A Model Agnostic System to Price Consumer Data
    Anish Agarwal, Munther Dahleh Devavrat Shah, Dyland Sleeper, Andrew Tsai, Madeline Wong
    http://arxiv.org/abs/1906.02420v1

    • [econ.EM]A long short-term memory stochastic volatility model
    Nghia Nguyen, Minh-Ngoc Tran, David Gunawan, R. Kohn
    http://arxiv.org/abs/1906.02884v1

    • [econ.GN]Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?
    Michael Allan Ribers, Hannes Ullrich
    http://arxiv.org/abs/1906.03044v1

    • [eess.IV]A deep learning approach for automated detection of geographic atrophy from color fundus photographs
    Tiarnan D. Keenan, Shazia Dharssi, Yifan Peng, Qingyu Chen, Elvira Agrón, Wai T. Wong, Zhiyong Lu, Emily Y. Chew
    http://arxiv.org/abs/1906.03153v1

    • [eess.IV]Decompose-and-Integrate Learning for Multi-class Segmentation in Medical Images
    Yizhe Zhang, Michael T. C. Ying, Danny Z. Chen
    http://arxiv.org/abs/1906.02901v1

    • [eess.IV]Deep Angular Embedding and Feature Correlation Attention for Breast MRI Cancer Analysis
    Luyang Luo, Hao Chen, Xi Wang, Qi Dou, Huangjin Lin, Juan Zhou, Gongjie Li, Pheng-Ann Heng
    http://arxiv.org/abs/1906.02999v1

    • [eess.IV]Deep Learning based Cephalometric Landmark Identification using Landmark-dependent Multi-scale Patches
    Chonho Lee, Chihiro Tanikawa, Jae-Yeon Lim, Takashi Yamashiro
    http://arxiv.org/abs/1906.02961v1

    • [eess.IV]DeepBundle: Fiber Bundle Parcellation with Graph Convolution Neural Networks
    Feihong Liu, Jun Feng, Geng Chen, Ye Wu, Yoonmi Hong, Pew-Thian Yap, Dinggang Shen
    http://arxiv.org/abs/1906.03051v1

    • [eess.SP]Deep Learning For Experimental Hybrid Terrestrial and Satellite Interference Management
    Pol Henarejos, Miguel Ángel Vázquez, Ana Isabel Pérez-Neira
    http://arxiv.org/abs/1906.03012v1

    • [eess.SP]Intelligent Reflecting Surface Assisted Multi-User MISO Communication
    Qurrat-Ul-Ain Nadeem, Abla Kammoun, Anas Chaaban, Merouane Debbah, Mohamed-Slim Alouini
    http://arxiv.org/abs/1906.02360v1

    • [math-ph]Ihara Zeta Entropy
    Supriyo Dutta, Partha Guha
    http://arxiv.org/abs/1906.02514v1

    • [math.CO]The ${[46,9,20]2}$ code is unique**
    _Sascha Kurz
    http://arxiv.org/abs/1906.02621v1

    • [math.OC]A Non-Asymptotic Analysis of Network Independence for Distributed Stochastic Gradient Descent
    Alex Olshevsky, Ioannis Ch. Paschalidis, Shi Pu
    http://arxiv.org/abs/1906.02702v1

    • [math.ST]A novel characterization and new simple tests of multivariate independence using copulas
    José M. González-Barrios, Eduardo Gutiérrez-Peña, Juan D. Nieves, Raúl Rueda
    http://arxiv.org/abs/1906.02196v1

    • [math.ST]Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation
    Mark Bun, Thomas Steinke
    http://arxiv.org/abs/1906.02830v1

    • [math.ST]Correlation bounds, mixing and m-dependence under random time-varying network distances with an application to Cox-Processes
    Alexander Kreiss
    http://arxiv.org/abs/1906.03179v1

    • [math.ST]Enhancing Multi-model Inference with Natural Selection
    Ching-Wei Cheng, Guang Cheng
    http://arxiv.org/abs/1906.02389v1

    • [math.ST]Estimation with informative missing data in the low-rank model with random effects
    Aude Sportisse, Claire Boyer, Julie Josse
    http://arxiv.org/abs/1906.02493v1

    • [math.ST]Laws of large numbers for stochastic orders
    Xiaosheng Mu, Luciano Pomatto, Philipp Strack, Omer Tamuz
    http://arxiv.org/abs/1906.02838v1

    • [math.ST]Nonparametric volatility change detection
    Maria Mohr, Natalie Neumeyer
    http://arxiv.org/abs/1906.02996v1

    • [math.ST]On the definition of informative vs. ignorable nuisance process
    Daniel Bonnery, Joseph Sedransk
    http://arxiv.org/abs/1906.02733v1

    • [math.ST]Robust subgaussian estimation of a mean vector in nearly linear time
    Guillaume Lecué, Jules Depersin
    http://arxiv.org/abs/1906.03058v1

    • [math.ST]Robustness and Tractability for Non-convex M-estimators
    Ruizhi Zhang, Yajun Mei, Jianjun Shi, Huan Xu
    http://arxiv.org/abs/1906.02272v1

    • [math.ST]Transfer Learning for Nonparametric Classification: Minimax Rate and Adaptive Classifier
    T. Tony Cai, Hongji Wei
    http://arxiv.org/abs/1906.02903v1

    • [nlin.AO]A method for the classification of chimera states of coupled oscillators and its application for creating a neural network information converter
    Andrei Velichko
    http://arxiv.org/abs/1906.02680v1

    • [nlin.AO]Mutual Information and the Edge of Chaos in Reservoir Computers
    Thomas L. Carroll
    http://arxiv.org/abs/1906.03186v1

    • [physics.comp-ph]Machine Learning Prediction of Accurate Atomization Energies of Organic Molecules from Low-Fidelity Quantum Chemical Calculations
    Logan Ward, Ben Blaiszik, Ian Foster, Rajeev S. Assary, Badri Narayanan, Larry Curtiss
    http://arxiv.org/abs/1906.03233v1

    • [q-bio.GN]DOT: Gene-set analysis by combining decorrelated association statistics
    Olga A Vsevolozhskaya, Min Shi, Fengjiao Hu, Dmitri V Zaykin
    http://arxiv.org/abs/1906.02321v1

    • [q-bio.NC]Association Between Intelligence and Cortical Thickness in Adolescents: Evidence from the ABCD Study
    Qi Zhao, Lingli Zhang, Chun Shen, Wei Cheng, Jianfeng Feng
    http://arxiv.org/abs/1906.02863v1

    • [q-bio.NC]Non-uniqueness phenomenon of object representation in modelling IT cortex by deep convolutional neural network (DCNN)
    Qiulei Dong, Bo Liu, Zhanyi Hu
    http://arxiv.org/abs/1906.02487v1

    • [quant-ph]Quantum Distributed Algorithm for the All-Pairs Shortest Path Problem in the CONGEST-CLIQUE Model
    Taisuke Izumi, François Le Gall
    http://arxiv.org/abs/1906.02456v1

    • [stat.AP]A Bayesian approach for the analysis of error rate studies in forensic science
    Jessie Hendricks, Cedric Neumann
    http://arxiv.org/abs/1906.02638v1

    • [stat.AP]An Inverse Optimization Approach to Measuring Clinical Pathway Concordance
    Timothy C. Y. Chan, Maria Eberg, Katharina Forster, Claire Holloway, Luciano Ieraci, Yusuf Shalaby, Nasrin Yousefi
    http://arxiv.org/abs/1906.02636v1

    • [stat.AP]Fast Multi-resolution Segmentation for Nonstationary Hawkes Process Using Cumulants
    Feng Zhou, Zhidong Li, Xuhui Fan, Yang Wang, Arcot Sowmya, Fang Chen
    http://arxiv.org/abs/1906.02438v1

    • [stat.AP]Modelling the spatial extent and severity of extreme European windstorms
    Paul Sharkey, Jonathan A. Tawn, Simon J. Brown
    http://arxiv.org/abs/1906.03178v1

    • [stat.AP]Probabilistic Structure Learning for EEG/MEG Source Imaging with Hierarchical Graph Prior
    Feng Liu, Li Wang, Yifei Lou, Rencang Li, Patrick Purdon
    http://arxiv.org/abs/1906.02252v1

    • [stat.AP]Reconciling Hierarchical Forecasts via Bayes’ Rule
    Giorgio Corani, Dario Azzimonti, Marco Zaffalon
    http://arxiv.org/abs/1906.03105v1

    • [stat.AP]Selecting Biomarkers for building optimal treatment selection rules using Kernel Machines
    Sayan Dasgupta, Ying Huang
    http://arxiv.org/abs/1906.02384v1

    • [stat.AP]The Political Significance of Social Penumbras
    Andrew Gelman, Yotam Margalit
    http://arxiv.org/abs/1906.02822v1

    • [stat.ME]Bayesian Wavelet-packet Historical Functional Linear Models
    Mark J. Meyer, Elizabeth J. Malloy, Brent A. Coull
    http://arxiv.org/abs/1906.02269v1

    • [stat.ME]Deep Compositional Spatial Models
    Andrew Zammit-Mangion, Tin Lok James Ng, Quan Vu, Maurizio Filippone
    http://arxiv.org/abs/1906.02840v1

    • [stat.ME]Inferring phenotypic trait evolution on large trees with many incomplete measurements
    Gabriel Hassler, Max R. Tolkoff, William L. Allen, Lam Si Tung Ho, Philippe Lemey, Marc A. Suchard
    http://arxiv.org/abs/1906.03222v1

    • [stat.ME]Multivariate Conditional Transformation Models
    Nadja Klein, Torsten Hothorn, Thomas Kneib
    http://arxiv.org/abs/1906.03151v1

    • [stat.ME]Robust real-time monitoring of high-dimensional data streams
    Ruizhi Zhang, Yajun Mei, Jianjun Shi
    http://arxiv.org/abs/1906.02265v1

    • [stat.ML]Automatic Reparameterisation of Probabilistic Programs
    Maria I. Gorinova, Dave Moore, Matthew D. Hoffman
    http://arxiv.org/abs/1906.03028v1

    • [stat.ML]Computing Exact Guarantees for Differential Privacy
    Antti Koskela, Joonas Jälkö, Antti Honkela
    http://arxiv.org/abs/1906.03049v1

    • [stat.ML]Detecting Out-of-Distribution Inputs to Deep Generative Models Using a Test for Typicality
    Eric Nalisnick, Akihiro Matsukawa, Yee Whye Teh, Balaji Lakshminarayanan
    http://arxiv.org/abs/1906.02994v1

    • [stat.ML]Disentangled State Space Representations
    Đorđe Miladinović, Muhammad Waleed Gondal, Bernhard Schölkopf, Joachim M. Buhmann, Stefan Bauer
    http://arxiv.org/abs/1906.03255v1

    • [stat.ML]Ensemble Pruning via Margin Maximization
    Waldyn Martinez
    http://arxiv.org/abs/1906.03247v1

    • [stat.ML]Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations
    Wu Lin, Mohammad Emtiyaz Khan, Mark Schmidt
    http://arxiv.org/abs/1906.02914v1

    • [stat.ML]Kernelized Capsule Networks
    Taylor Killian, Justin Goodwin, Olivia Brown, Sung-Hyun Son
    http://arxiv.org/abs/1906.03164v1

    • [stat.ML]Likelihood Ratios for Out-of-Distribution Detection
    Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark A. DePristo, Joshua V. Dillon, Balaji Lakshminarayanan
    http://arxiv.org/abs/1906.02845v1

    • [stat.ML]On the Current State of Research in Explaining Ensemble Performance Using Margins
    Waldyn Martinez, J. Brian Gray
    http://arxiv.org/abs/1906.03123v1

    • [stat.ML]One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers
    Ari S. Morcos, Haonan Yu, Michela Paganini, Yuandong Tian
    http://arxiv.org/abs/1906.02773v1

    • [stat.ML]Online Graph-Based Change-Point Detection for High Dimensional Data
    Yang-Wen Sun, Katerina Papagiannouli, Vladmir Spokoiny
    http://arxiv.org/abs/1906.03001v1

    • [stat.ML]Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP
    Haonan Yu, Sergey Edunov, Yuandong Tian, Ari S. Morcos
    http://arxiv.org/abs/1906.02768v1

    • [stat.ML]Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations
    Debraj Basu, Deepesh Data, Can Karakus, Suhas Diggavi
    http://arxiv.org/abs/1906.02367v1

    • [stat.ML]Ranking and synchronization from pairwise measurements via SVD
    Alexandre d’Aspremont, Mihai Cucuringu, Hemant Tyagi
    http://arxiv.org/abs/1906.02746v1

    • [stat.ML]Recurrent Kernel Networks
    Dexiong Chen, Laurent Jacob, Julien Mairal
    http://arxiv.org/abs/1906.03200v1

    • [stat.ML]Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models
    Alexander Terenin, Måns Magnusson, Leif Jonsson
    http://arxiv.org/abs/1906.02416v1

    • [stat.ML]Structured Variational Inference in Continuous Cox Process Models
    Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps
    http://arxiv.org/abs/1906.03161v1

    • [stat.ML]The Normalization Method for Alleviating Pathological Sharpness in Wide Neural Networks
    Ryo Karakida, Shotaro Akaho, Shun-ichi Amari
    http://arxiv.org/abs/1906.02926v1

    • [stat.ML]Vertex Classification on Weighted Networks
    Hayden Helm, Joshua Vogelstein, Carey Priebe
    http://arxiv.org/abs/1906.02881v1