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.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.NI - 网络和互联网体系结构 cs.PF - 计算性能 cs.PL - 编程语言 cs.RO - 机器人学 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.SY - 系统和控制 math.DG - 微分几何 math.DS - 动力系统 math.OC - 优化与控制 math.ST - 统计理论 physics.soc-ph - 物理学与社会 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]Inferred successor maps for better transfer learning
    • [cs.AI]Learning to Plan Hierarchically from Curriculum
    • [cs.AI]PACMAN: A Planner-Actor-Critic Architecture for Human-Centered Planning and Learning
    • [cs.AI]Subsumption-driven clause learning with DPLL+restarts
    • [cs.CL]A Structured Distributional Model of Sentence Meaning and Processing
    • [cs.CL]Attention Guided Graph Convolutional Networks for Relation Extraction
    • [cs.CL]Automatic learner summary assessment for reading comprehension
    • [cs.CL]Barack’s Wife Hillary: Using Knowledge-Graphs for Fact-Aware Language Modeling
    • [cs.CL]Constrained Decoding for Neural NLG from Compositional Representations in Task-Oriented Dialogue
    • [cs.CL]Curriculum Learning Strategies for Hindi-English Codemixed Sentiment Analysis
    • [cs.CL]Curriculum-based transfer learning for an effective end-to-end spoken language understanding and domain portability
    • [cs.CL]Distilling Translations with Visual Awareness
    • [cs.CL]Expressing Visual Relationships via Language
    • [cs.CL]Finding Your Voice: The Linguistic Development of Mental Health Counselors
    • [cs.CL]Generalizing Back-Translation in Neural Machine Translation
    • [cs.CL]Hyperintensional Reasoning based on Natural Language Knowledge Base
    • [cs.CL]Improving Sentiment Analysis with Multi-task Learning of Negation
    • [cs.CL]LTG-Oslo Hierarchical Multi-task Network: The importance of negation for document-level sentiment in Spanish
    • [cs.CL]Measuring Bias in Contextualized Word Representations
    • [cs.CL]Mimicking Human Process: Text Representation via Latent Semantic Clustering for Classification
    • [cs.CL]Modeling Semantic Relationship in Multi-turn Conversations with Hierarchical Latent Variables
    • [cs.CL]Multi-Graph Decoding for Code-Switching ASR
    • [cs.CL]Scheduled Sampling for Transformers
    • [cs.CL]State-of-the-Art Vietnamese Word Segmentation
    • [cs.CL]Tabula nearly rasa: Probing the Linguistic Knowledge of Character-Level Neural Language Models Trained on Unsegmented Text
    • [cs.CL]Text Readability Assessment for Second Language Learners
    • [cs.CL]Towards Robust Named Entity Recognition for Historic German
    • [cs.CL]Towards Transfer Learning for End-to-End Speech Synthesis from Deep Pre-Trained Language Models
    • [cs.CL]Transfer Learning for Causal Sentence Detection
    • [cs.CL]Uncovering Probabilistic Implications in Typological Knowledge Bases
    • [cs.CL]Yoga-Veganism: Correlation Mining of Twitter Health Data
    • [cs.CL]Zero-Shot Entity Linking by Reading Entity Descriptions
    • [cs.CR]Secure Architectures Implementing Trusted Coalitions for Blockchained Distributed Learning (TCLearn)
    • [cs.CV]3D Geometric salient patterns analysis on 3D meshes
    • [cs.CV]A One-step Pruning-recovery Framework for Acceleration of Convolutional Neural Networks
    • [cs.CV]A Weakly Supervised Learning Based Clustering Framework
    • [cs.CV]A sparse annotation strategy based on attention-guided active learning for 3D medical image segmentation
    • [cs.CV]ADA-Tucker: Compressing Deep Neural Networks via Adaptive Dimension Adjustment Tucker Decomposition
    • [cs.CV]Bicameral Structuring and Synthetic Imagery for Jointly Predicting Instance Boundaries and Nearby Occlusions from a Single Image
    • [cs.CV]Boosting CNN beyond Label in Inverse Problems
    • [cs.CV]Content-aware Density Map for Crowd Counting and Density Estimation
    • [cs.CV]DeepView: View Synthesis with Learned Gradient Descent
    • [cs.CV]Hardware Aware Neural Network Architectures using FbNet
    • [cs.CV]Impoved RPN for Single Targets Detection based on the Anchor Mask Net
    • [cs.CV]Learning with Average Precision: Training Image Retrieval with a Listwise Loss
    • [cs.CV]Locality Preserving Joint Transfer for Domain Adaptation
    • [cs.CV]Locate, Size and Count: Accurately Resolving People in Dense Crowds via Detection
    • [cs.CV]Neural Illumination: Lighting Prediction for Indoor Environments
    • [cs.CV]Neural Multi-Scale Self-Supervised Registration for Echocardiogram Dense Tracking
    • [cs.CV]Noisy-As-Clean: Learning Unsupervised Denoising from the Corrupted Image
    • [cs.CV]PolSAR Image Classification based on Polarimetric Scattering Coding and Sparse Support Matrix Machine
    • [cs.CV]Pose Guided Fashion Image Synthesis Using Deep Generative Model
    • [cs.CV]STAR: A Structure and Texture Aware Retinex Model
    • [cs.CV]Using Discriminative Methods to Learn Fashion Compatibility Across Datasets
    • [cs.CV]Using colorization as a tool for automatic makeup suggestion
    • [cs.CV]Weather Influence and Classification with Automotive Lidar Sensors
    • [cs.CY]Agriculture Commodity Arrival Prediction using Remote Sensing Data: Insights and Beyond
    • [cs.CY]Evaluation Pattern on Refugee Crisis
    • [cs.CY]On the needs for MaaS platforms to handle competition in ridesharing mobility
    • [cs.CY]Options of Different Rescue Periods on Transport Tools
    • [cs.CY]Wrist02 — Reliable Peripheral Oxygen Saturation Readings from Wrist-Worn Pulse Oximeters
    • [cs.DB]A Books Recommendation Approach Based on Online Bookstore Data
    • [cs.DB]Scalable Distributed Subtrajectory Clustering
    • [cs.DC]From Facility to Application Sensor Data: Modular, Continuous and Holistic Monitoring with DCDB
    • [cs.DC]The Workflow Trace Archive: Open-Access Data from Public and Private Computing Infrastructures — Technical Report
    • [cs.GR]Active Scene Understanding via Online Semantic Reconstruction
    • [cs.HC]Eye Gaze Metrics and Analysis of AOI for Indexing Working Memory towards Predicting ADHD
    • [cs.IR]Model Explanations under Calibration
    • [cs.IR]Query Generation for Patent Retrieval with Keyword Extraction based on Syntactic Features
    • [cs.IT]Asymptotic performance of metacyclic codes
    • [cs.IT]Energy Efficiency Maximization for Full-Duplex UAV Secrecy Communication
    • [cs.LG]A Study of the Learning Progress in Neural Architecture Search Techniques
    • [cs.LG]A gray-box approach for curriculum learning
    • [cs.LG]An IoT Based Framework For Activity Recognition Using Deep Learning Technique
    • [cs.LG]Analyzing privacy-aware mobility behavior using the evolution of spatio-temporal entropy
    • [cs.LG]Approximation power of random neural networks
    • [cs.LG]Data-Driven Malaria Prevalence Prediction in Large Densely-Populated Urban Holoendemic sub-Saharan West Africa: Harnessing Machine Learning Approaches and 22-years of Prospectively Collected Data
    • [cs.LG]Deep Active Learning for Anchor User Prediction
    • [cs.LG]Differentiable probabilistic models of scientific imaging with the Fourier slice theorem
    • [cs.LG]Equivariant neural networks and equivarification
    • [cs.LG]Estimating a Manifold from a Tangent Bundle Learner
    • [cs.LG]Evolutionary Reinforcement Learning for Sample-Efficient Multiagent Coordination
    • [cs.LG]From Clustering to Cluster Explanations via Neural Networks
    • [cs.LG]Gap-Increasing Policy Evaluation for Efficient and Noise-Tolerant Reinforcement Learning
    • [cs.LG]High-Performance Deep Learning via a Single Building Block
    • [cs.LG]Intrinsic dimension estimation for locally undersampled data
    • [cs.LG]Inverting Deep Generative models, One layer at a time
    • [cs.LG]Iterative Model-Based Reinforcement Learning Using Simulations in the Differentiable Neural Computer
    • [cs.LG]Language as an Abstraction for Hierarchical Deep Reinforcement Learning
    • [cs.LG]Learning Execution through Neural Code Fusion
    • [cs.LG]Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
    • [cs.LG]Learning Personalized Attribute Preference via Multi-task AUC Optimization
    • [cs.LG]Lower Bounds and Conditioning of Differentiable Games
    • [cs.LG]Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles
    • [cs.LG]Neurally-Guided Structure Inference
    • [cs.LG]Online Matrix Completion with Side Information
    • [cs.LG]Prune and Replace NAS
    • [cs.LG]RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration
    • [cs.LG]Robust Reinforcement Learning for Continuous Control with Model Misspecification
    • [cs.LG]Sample-efficient Adversarial Imitation Learning from Observation
    • [cs.LG]Simple Algorithms for Dueling Bandits
    • [cs.LG]The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers
    • [cs.LG]The Multiplicative Noise in Stochastic Gradient Descent: Data-Dependent Regularization, Continuous and Discrete Approximation
    • [cs.LG]TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial
    • [cs.LG]Towards White-box Benchmarks for Algorithm Control
    • [cs.LG]Unsupervised machine learning to analyse city logistics through Twitter
    • [cs.NI]MQTTg: An Android Implementation
    • [cs.PF]MultiCloud Resource Management using Apache Mesos with Apache Airavata
    • [cs.PL]The Mathematical Specification of the Statebox Language
    • [cs.RO]Chemotaxis Based Virtual Fence for Swarm Robots in Unbounded Environments
    • [cs.RO]Design and Characterization of the Dynamic Robotic Actuator Dyrac
    • [cs.RO]Heterogeneous Robot Teams for Informative Sampling
    • [cs.RO]Providentia — A Large Scale Sensing System for the Assistance of Autonomous Vehicles
    • [cs.RO]Visual Navigation by Generating Next Expected Observations
    • [cs.RO]Whole-Body Control with (Self) Collision Avoidance using Vector Field Inequalities
    • [cs.SE]Losing Confidence in Quality: Unspoken Evolution of Computer Vision Services
    • [cs.SE]Reputation Systems — Fair allocation of points to the editors in the collaborative community
    • [cs.SI]20 Years of Mobility Modeling & Prediction: Trends, Shortcomings & Perspectives
    • [cs.SI]DISCO: Influence Maximization Meets Network Embedding and Deep Learning
    • [cs.SI]Knowledge Network System (KNS) by Evolutionary Collective Intelligence (ECI): Model, Algorithm and Applications
    • [cs.SI]vGraph: A Generative Model for Joint Community Detection and Node Representation Learning
    • [eess.AS]A Unified Speaker Adaptation Method for Speech Synthesis using Transcribed and Untranscribed Speech with Backpropagation
    • [eess.AS]Combining Adversarial Training and Disentangled Speech Representation for Robust Zero-Resource Subword Modeling
    • [eess.AS]Margin Matters: Towards More Discriminative Deep Neural Network Embeddings for Speaker Recognition
    • [eess.IV]4D CNN for semantic segmentation of cardiac volumetric sequences
    • [eess.IV]A Conditional Random Field Model for Context Aware Cloud Detection in Sky Images
    • [eess.IV]An Attention-Guided Deep Regression Model for Landmark Detection in Cephalograms
    • [eess.IV]Cardiac Segmentation from LGE MRI Using Deep Neural Network Incorporating Shape and Spatial Priors
    • [eess.IV]Deep Learning Enhanced Extended Depth-of-Field for Thick Blood-Film Malaria High-Throughput Microscopy
    • [eess.IV]Multiclass segmentation as multitask learning for drusen segmentation in retinal optical coherence tomography
    • [eess.SY]Of Cores: A Partial-Exploration Framework for Markov Decision Processes
    • [math.DG]Curvature effects on the empirical mean in Riemannian and affine Manifolds: a non-asymptotic high concentration expansion in the small-sample regime
    • [math.DS]New Uniform Bounds for Almost Lossless Analog Compression
    • [math.OC]Escaping from saddle points on Riemannian manifolds
    • [math.OC]On linear convergence of two decentralized algorithms
    • [math.ST]Balakrishnan Alpha Skew Normal Distribution: Properties and Applications
    • [math.ST]Efficient computation of the cumulative distribution function of a linear mixture of independent random variables
    • [math.ST]Extended Plugin Densities for Curved Exponential Families
    • [math.ST]Improper vs finitely additive distributions as limits of countably additive probabilities
    • [math.ST]Nonparametric estimation in a regression model with additive and multiplicative noise
    • [math.ST]Testing goodness of fit for point processes via topological data analysis
    • [physics.soc-ph]Quantifying Dismantlement in Disconnected Networks
    • [quant-ph]Parameterized quantum circuits as machine learning models
    • [stat.AP]Template Independent Component Analysis: Targeted and Reliable Estimation of Subject-level Brain Networks using Big Data Population Priors
    • stat.CORFCDE: Random Forests for Conditional Density Estimation and Functional Data
    • [stat.CO]Variational Inference with Numerical Derivatives: variance reduction through coupling
    • [stat.ME]A Model-Based General Alternative to the Standardised Precipitation Index
    • [stat.ME]Blending the New Statistics with Mixture Modeling — A ROPE-based single-block Gibbs sampler for Bayesian t-tests
    • [stat.ME]Fast Converging and Robust Optimal Path Selection in Continuous-time Markov-switching GARCH Model
    • [stat.ME]Prediction properties of optimum response surface designs
    • [stat.ML]Bayesian Optimization with Binary Auxiliary Information
    • [stat.ML]Consistency of semi-supervised learning algorithms on graphs: Probit and one-hot methods
    • [stat.ML]Error Correcting Algorithms for Sparsely Correlated Regressors
    • [stat.ML]Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes
    • [stat.ML]Model selection for high-dimensional linear regression with dependent observations

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    • [cs.AI]Inferred successor maps for better transfer learning
    Tamas J. Madarasz
    http://arxiv.org/abs/1906.07663v1

    • [cs.AI]Learning to Plan Hierarchically from Curriculum
    Philippe Morere, Lionel Ott, Fabio Ramos
    http://arxiv.org/abs/1906.07371v1

    • [cs.AI]PACMAN: A Planner-Actor-Critic Architecture for Human-Centered Planning and Learning
    Daoming Lyu, Fangkai Yang, Bo Liu, Steven Gustafson
    http://arxiv.org/abs/1906.07268v1

    • [cs.AI]Subsumption-driven clause learning with DPLL+restarts
    Olivier Bailleux
    http://arxiv.org/abs/1906.07508v1

    • [cs.CL]A Structured Distributional Model of Sentence Meaning and Processing
    Emmanuele Chersoni, Enrico Santus, Ludovica Pannitto, Alessandro Lenci, Philippe Blache, Chu-Ren Huang
    http://arxiv.org/abs/1906.07280v1

    • [cs.CL]Attention Guided Graph Convolutional Networks for Relation Extraction
    Zhijiang Guo, Yan Zhang, Wei Lu
    http://arxiv.org/abs/1906.07510v1

    • [cs.CL]Automatic learner summary assessment for reading comprehension
    Menglin Xia, Ekaterina Kochmar, Ted Briscoe
    http://arxiv.org/abs/1906.07555v1

    • [cs.CL]Barack’s Wife Hillary: Using Knowledge-Graphs for Fact-Aware Language Modeling
    Logan, IV, Robert L., Liu, Nelson F., Peters, Matthew E., Gardner, Matt, Singh, Sameer
    http://arxiv.org/abs/1906.07241v1

    • [cs.CL]Constrained Decoding for Neural NLG from Compositional Representations in Task-Oriented Dialogue
    Anusha Balakrishnan, Jinfeng Rao, Kartikeya Upasani, Michael White, Rajen Subba
    http://arxiv.org/abs/1906.07220v1

    • [cs.CL]Curriculum Learning Strategies for Hindi-English Codemixed Sentiment Analysis
    Anirudh Dahiya, Neeraj Battan, Manish Shrivastava, Dipti Mishra Sharma
    http://arxiv.org/abs/1906.07382v1

    • [cs.CL]Curriculum-based transfer learning for an effective end-to-end spoken language understanding and domain portability
    Antoine Caubrière, Natalia Tomashenko, Antoine Laurent, Emmanuel Morin, Nathalie Camelin, Yannick Estève
    http://arxiv.org/abs/1906.07601v1

    • [cs.CL]Distilling Translations with Visual Awareness
    Julia Ive, Pranava Madhyastha, Lucia Specia
    http://arxiv.org/abs/1906.07701v1

    • [cs.CL]Expressing Visual Relationships via Language
    Hao Tan, Franck Dernoncourt, Zhe Lin, Trung Bui, Mohit Bansal
    http://arxiv.org/abs/1906.07689v1

    • [cs.CL]Finding Your Voice: The Linguistic Development of Mental Health Counselors
    Justine Zhang, Robert Filbin, Christine Morrison, Jaclyn Weiser, Cristian Danescu-Niculescu-Mizil
    http://arxiv.org/abs/1906.07194v1

    • [cs.CL]Generalizing Back-Translation in Neural Machine Translation
    Miguel Graça, Yunsu Kim, Julian Schamper, Shahram Khadivi, Hermann Ney
    http://arxiv.org/abs/1906.07286v1

    • [cs.CL]Hyperintensional Reasoning based on Natural Language Knowledge Base
    Marie Duží, Aleš Horák
    http://arxiv.org/abs/1906.07562v1

    • [cs.CL]Improving Sentiment Analysis with Multi-task Learning of Negation
    Jeremy Barnes, Erik Velldal, Lilja Øvrelid
    http://arxiv.org/abs/1906.07610v1

    • [cs.CL]LTG-Oslo Hierarchical Multi-task Network: The importance of negation for document-level sentiment in Spanish
    Jeremy Barnes
    http://arxiv.org/abs/1906.07599v1

    • [cs.CL]Measuring Bias in Contextualized Word Representations
    Keita Kurita, Nidhi Vyas, Ayush Pareek, Alan W Black, Yulia Tsvetkov
    http://arxiv.org/abs/1906.07337v1

    • [cs.CL]Mimicking Human Process: Text Representation via Latent Semantic Clustering for Classification
    Xiaoye Tan, Rui Yan, Chongyang Tao, Mingrui Wu
    http://arxiv.org/abs/1906.07525v1

    • [cs.CL]Modeling Semantic Relationship in Multi-turn Conversations with Hierarchical Latent Variables
    Lei Shen, Yang Feng, Haolan Zhan
    http://arxiv.org/abs/1906.07429v1

    • [cs.CL]Multi-Graph Decoding for Code-Switching ASR
    Emre Yılmaz, Samuel Cohen, Xianghu Yue, David van Leeuwen, Haizhou Li
    http://arxiv.org/abs/1906.07523v1

    • [cs.CL]Scheduled Sampling for Transformers
    Tsvetomila Mihaylova, André F. T. Martins
    http://arxiv.org/abs/1906.07651v1

    • [cs.CL]State-of-the-Art Vietnamese Word Segmentation
    Song Nguyen Duc Cong, Quoc Hung Ngo, Rachsuda Jiamthapthaksin
    http://arxiv.org/abs/1906.07662v1

    • [cs.CL]Tabula nearly rasa: Probing the Linguistic Knowledge of Character-Level Neural Language Models Trained on Unsegmented Text
    Michael Hahn, Marco Baroni
    http://arxiv.org/abs/1906.07285v1

    • [cs.CL]Text Readability Assessment for Second Language Learners
    Menglin Xia, Ekaterina Kochmar, Ted Briscoe
    http://arxiv.org/abs/1906.07580v1

    • [cs.CL]Towards Robust Named Entity Recognition for Historic German
    Stefan Schweter, Johannes Baiter
    http://arxiv.org/abs/1906.07592v1

    • [cs.CL]Towards Transfer Learning for End-to-End Speech Synthesis from Deep Pre-Trained Language Models
    Wei Fang, Yu-An Chung, James Glass
    http://arxiv.org/abs/1906.07307v1

    • [cs.CL]Transfer Learning for Causal Sentence Detection
    Manolis Kyriakakis, Ion Androutsopoulos, Joan Ginés i Ametllé, Artur Saudabayev
    http://arxiv.org/abs/1906.07544v1

    • [cs.CL]Uncovering Probabilistic Implications in Typological Knowledge Bases
    Johannes Bjerva, Yova Kementchedjhieva, Ryan Cotterell, Isabelle Augenstein
    http://arxiv.org/abs/1906.07389v1

    • [cs.CL]Yoga-Veganism: Correlation Mining of Twitter Health Data
    Tunazzina Islam
    http://arxiv.org/abs/1906.07668v1

    • [cs.CL]Zero-Shot Entity Linking by Reading Entity Descriptions
    Lajanugen Logeswaran, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, Jacob Devlin, Honglak Lee
    http://arxiv.org/abs/1906.07348v1

    • [cs.CR]Secure Architectures Implementing Trusted Coalitions for Blockchained Distributed Learning (TCLearn)
    Sebastien Lugan, Paul Desbordes, Luis Xavier Ramos Tormo, Axel Legay, Benoit Macq
    http://arxiv.org/abs/1906.07690v1

    • [cs.CV]3D Geometric salient patterns analysis on 3D meshes
    Alice Othmani, Fakhri Torkhani, Jean-Marie Favreau
    http://arxiv.org/abs/1906.07645v1

    • [cs.CV]A One-step Pruning-recovery Framework for Acceleration of Convolutional Neural Networks
    Dong Wang, Lei Zhou, Xiao Bai, Jun Zhou
    http://arxiv.org/abs/1906.07488v1

    • [cs.CV]A Weakly Supervised Learning Based Clustering Framework
    Mustafa Umit Oner, Hwee Kuan Lee, Wing-Kin Sung
    http://arxiv.org/abs/1906.07647v1

    • [cs.CV]A sparse annotation strategy based on attention-guided active learning for 3D medical image segmentation
    Zhenxi Zhang, Jie Li, Zhusi Zhong, Zhicheng Jiao, Xinbo Gao
    http://arxiv.org/abs/1906.07367v1

    • [cs.CV]ADA-Tucker: Compressing Deep Neural Networks via Adaptive Dimension Adjustment Tucker Decomposition
    Zhisheng Zhong, Fangyin Wei, Zhouchen Lin, Chao Zhang
    http://arxiv.org/abs/1906.07671v1

    • [cs.CV]Bicameral Structuring and Synthetic Imagery for Jointly Predicting Instance Boundaries and Nearby Occlusions from a Single Image
    Matthieu Grard, Liming Chen, Emmanuel Dellandréa
    http://arxiv.org/abs/1906.07480v1

    • [cs.CV]Boosting CNN beyond Label in Inverse Problems
    Eunju Cha, Jaeduck Jang, Junho Lee, Eunha Lee, Jong Chul Ye
    http://arxiv.org/abs/1906.07330v1

    • [cs.CV]Content-aware Density Map for Crowd Counting and Density Estimation
    Mahdi Maktabdar Oghaz, Anish R Khadka, Vasileios Argyriou, Paolo Remagnino
    http://arxiv.org/abs/1906.07258v1

    • [cs.CV]DeepView: View Synthesis with Learned Gradient Descent
    John Flynn, Michael Broxton, Paul Debevec, Matthew DuVall, Graham Fyffe, Ryan Overbeck, Noah Snavely, Richard Tucker
    http://arxiv.org/abs/1906.07316v1

    • [cs.CV]Hardware Aware Neural Network Architectures using FbNet
    Sai Vineeth Kalluru Srinivas, Harideep Nair, Vinay Vidyasagar
    http://arxiv.org/abs/1906.07214v1

    • [cs.CV]Impoved RPN for Single Targets Detection based on the Anchor Mask Net
    Mingjie Li, Youqian Feng, Zhonghai Yin, Cheng Zhou, Fanghao Dong
    http://arxiv.org/abs/1906.07527v1

    • [cs.CV]Learning with Average Precision: Training Image Retrieval with a Listwise Loss
    Jerome Revaud, Jon Almazan, Rafael Sampaio de Rezende, Cesar Roberto de Souza
    http://arxiv.org/abs/1906.07589v1

    • [cs.CV]Locality Preserving Joint Transfer for Domain Adaptation
    Li Jingjing, Jing Mengmeng, Lu Ke, Zhu Lei, Shen Heng Tao
    http://arxiv.org/abs/1906.07441v1

    • [cs.CV]Locate, Size and Count: Accurately Resolving People in Dense Crowds via Detection
    Deepak Babu Sam, Skand Vishwanath Peri, Mukuntha N. S., Amogh Kamath, R. Venkatesh Babu
    http://arxiv.org/abs/1906.07538v1

    • [cs.CV]Neural Illumination: Lighting Prediction for Indoor Environments
    Shuran Song, Thomas Funkhouser
    http://arxiv.org/abs/1906.07370v1

    • [cs.CV]Neural Multi-Scale Self-Supervised Registration for Echocardiogram Dense Tracking
    Wentao Zhu, Yufang Huang, Mani A Vannan, Shizhen Liu, Daguang Xu, Wei Fan, Zhen Qian, Xiaohui Xie
    http://arxiv.org/abs/1906.07357v1

    • [cs.CV]Noisy-As-Clean: Learning Unsupervised Denoising from the Corrupted Image
    Jun Xu, Yuan Huang, Li Liu, Fan Zhu, Xingsong Hou, Ling Shao
    http://arxiv.org/abs/1906.06878v2

    • [cs.CV]PolSAR Image Classification based on Polarimetric Scattering Coding and Sparse Support Matrix Machine
    Xu Liu, Licheng Jiao, Dan Zhang, Fang Liu
    http://arxiv.org/abs/1906.07176v1

    • [cs.CV]Pose Guided Fashion Image Synthesis Using Deep Generative Model
    Wei Sun, Jawadul H. Bappy, Shanglin Yang, Yi Xu, Tianfu Wu, Hui Zhou
    http://arxiv.org/abs/1906.07251v1

    • [cs.CV]STAR: A Structure and Texture Aware Retinex Model
    Jun Xu, Mengyang Yu, Li Liu, Fan Zhu, Dongwei Ren, Yingkun Hou, Haoqian Wang, Ling Shao
    http://arxiv.org/abs/1906.06690v2

    • [cs.CV]Using Discriminative Methods to Learn Fashion Compatibility Across Datasets
    Kedan Li, Chen Liu, Ranjitha Kumar, David Forsyth
    http://arxiv.org/abs/1906.07273v1

    • [cs.CV]Using colorization as a tool for automatic makeup suggestion
    Shreyank Narayana Gowda
    http://arxiv.org/abs/1906.07421v1

    • [cs.CV]Weather Influence and Classification with Automotive Lidar Sensors
    Robin Heinzler, Philipp Schindler, Jürgen Seekircher, Werner Ritter, Wilhelm Stork
    http://arxiv.org/abs/1906.07675v1

    • [cs.CY]Agriculture Commodity Arrival Prediction using Remote Sensing Data: Insights and Beyond
    Gautam Prasad, Upendra Reddy Vuyyuru, Mithun Das Gupta
    http://arxiv.org/abs/1906.07573v1

    • [cs.CY]Evaluation Pattern on Refugee Crisis
    Jiahui Chen, Mengjia Zhou, Bernie Liu
    http://arxiv.org/abs/1906.07408v1

    • [cs.CY]On the needs for MaaS platforms to handle competition in ridesharing mobility
    Venktesh Pandey, Julien Monteil, Claudio Gambella, Andrea Simonetto
    http://arxiv.org/abs/1906.07567v1

    • [cs.CY]Options of Different Rescue Periods on Transport Tools
    Mengjia Zhou, Jiahui Chen, Bernie Liu
    http://arxiv.org/abs/1906.07494v1

    • [cs.CY]Wrist02 — Reliable Peripheral Oxygen Saturation Readings from Wrist-Worn Pulse Oximeters
    Caleb Phillips, Daniyal Liaqat, Moshe Gabel, Eyal de Lara
    http://arxiv.org/abs/1906.07545v1

    • [cs.DB]A Books Recommendation Approach Based on Online Bookstore Data
    Xinyu Wei, Jiahui Chen, Jing Chen, Bernie Liu
    http://arxiv.org/abs/1906.06542v1

    • [cs.DB]Scalable Distributed Subtrajectory Clustering
    Panagiotis Tampakis, Nikos Pelekis, Christos Doulkeridis, Yannis Theodoridis
    http://arxiv.org/abs/1906.06956v2

    • [cs.DC]From Facility to Application Sensor Data: Modular, Continuous and Holistic Monitoring with DCDB
    Alessio Netti, Micha Mueller, Axel Auweter, Carla Guillen, Michael Ott, Daniele Tafani, Martin Schulz
    http://arxiv.org/abs/1906.07509v1

    • [cs.DC]The Workflow Trace Archive: Open-Access Data from Public and Private Computing Infrastructures — Technical Report
    Laurens Versluis, Roland Mathá, Sacheendra Talluri, Tim Hegeman, Radu Prodan, Ewa Deelman, Alexandru Iosup
    http://arxiv.org/abs/1906.07471v1

    • [cs.GR]Active Scene Understanding via Online Semantic Reconstruction
    Lintao Zheng, Chenyang Zhu, Jiazhao Zhang, Hang Zhao, Hui Huang, Matthias Niessner, Kai Xu
    http://arxiv.org/abs/1906.07409v1

    • [cs.HC]Eye Gaze Metrics and Analysis of AOI for Indexing Working Memory towards Predicting ADHD
    Gavindya Jayawardena, Anne Michalek, Sampath Jayarathna
    http://arxiv.org/abs/1906.07183v1

    • [cs.IR]Model Explanations under Calibration
    Rishabh Jain, Pranava Madhyastha
    http://arxiv.org/abs/1906.07622v1

    • [cs.IR]Query Generation for Patent Retrieval with Keyword Extraction based on Syntactic Features
    Julien Rossi, Matthias Wirth, Evangelos Kanoulas
    http://arxiv.org/abs/1906.07591v1

    • [cs.IT]Asymptotic performance of metacyclic codes
    Martino Borello, Pieter Moree, Patrick Solé
    http://arxiv.org/abs/1906.07446v1

    • [cs.IT]Energy Efficiency Maximization for Full-Duplex UAV Secrecy Communication
    Bin Duo, Qingqing Wu, Xiaojun Yuan, Rui Zhang
    http://arxiv.org/abs/1906.07346v1

    • [cs.LG]A Study of the Learning Progress in Neural Architecture Search Techniques
    Prabhant Singh, Tobias Jacobs, Sebastien Nicolas, Mischa Schmidt
    http://arxiv.org/abs/1906.07590v1

    • [cs.LG]A gray-box approach for curriculum learning
    Francesco Foglino, Matteo Leonetti, Simone Sagratella, Ruggiero Seccia
    http://arxiv.org/abs/1906.06812v1

    • [cs.LG]An IoT Based Framework For Activity Recognition Using Deep Learning Technique
    Ashwin Geet D’Sa, B. G. Prasad
    http://arxiv.org/abs/1906.07247v1

    • [cs.LG]Analyzing privacy-aware mobility behavior using the evolution of spatio-temporal entropy
    Arielle Moro, Benoît Garbinato, Valérie Chavez-Demoulin
    http://arxiv.org/abs/1906.07537v1

    • [cs.LG]Approximation power of random neural networks
    Bolton Bailey, Ziwei Ji, Matus Telgarsky, Ruicheng Xian
    http://arxiv.org/abs/1906.07709v1

    • [cs.LG]Data-Driven Malaria Prevalence Prediction in Large Densely-Populated Urban Holoendemic sub-Saharan West Africa: Harnessing Machine Learning Approaches and 22-years of Prospectively Collected Data
    Biobele J. Brown, Alexander A. Przybylski, Petru Manescu, Fabio Caccioli, Gbeminiyi Oyinloye, Muna Elmi, Michael J. Shaw, Vijay Pawar, Remy Claveau, John Shawe-Taylor, Mandayam A. Srinivasan, Nathaniel K. Afolabi, Adebola E. Orimadegun, Wasiu A. Ajetunmobi, Francis Akinkunmi, Olayinka Kowobari, Kikelomo Osinusi, Felix O. Akinbami, Samuel Omokhodion, Wuraola A. Shokunbi, Ikeoluwa Lagunju, Olugbemiro Sodeinde, Delmiro Fernandez-Reyes
    http://arxiv.org/abs/1906.07502v1

    • [cs.LG]Deep Active Learning for Anchor User Prediction
    Anfeng Cheng, Chuan Zhou, Hong Yang, Jia Wu, Lei Li, Jianlong Tan, Li Guo
    http://arxiv.org/abs/1906.07318v1

    • [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/1906.07582v1

    • [cs.LG]Equivariant neural networks and equivarification
    Erkao Bao, Linqi Song
    http://arxiv.org/abs/1906.07172v1

    • [cs.LG]Estimating a Manifold from a Tangent Bundle Learner
    Bharathkumar Ramachandra, Benjamin Dutton, Ranga Raju Vatsavai
    http://arxiv.org/abs/1906.07661v1

    • [cs.LG]Evolutionary Reinforcement Learning for Sample-Efficient Multiagent Coordination
    Shauharda Khadka, Somdeb Majumdar, Kagan Tumer
    http://arxiv.org/abs/1906.07315v1

    • [cs.LG]From Clustering to Cluster Explanations via Neural Networks
    Jacob Kauffmann, Malte Esders, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
    http://arxiv.org/abs/1906.07633v1

    • [cs.LG]Gap-Increasing Policy Evaluation for Efficient and Noise-Tolerant Reinforcement Learning
    Tadashi Kozuno, Dongqi Han, Kenji Doya
    http://arxiv.org/abs/1906.07586v1

    • [cs.LG]High-Performance Deep Learning via a Single Building Block
    Evangelos Georganas, Kunal Banerjee, Dhiraj Kalamkar, Sasikanth Avancha, Anand Venkat, Michael Anderson, Greg Henry, Hans Pabst, Alexander Heinecke
    http://arxiv.org/abs/1906.06440v2

    • [cs.LG]Intrinsic dimension estimation for locally undersampled data
    Vittorio Erba, Marco Gherardi, Pietro Rotondo
    http://arxiv.org/abs/1906.07670v1

    • [cs.LG]Inverting Deep Generative models, One layer at a time
    Qi Lei, Ajil Jalal, Inderjit S. Dhillon, Alexandros G. Dimakis
    http://arxiv.org/abs/1906.07437v1

    • [cs.LG]Iterative Model-Based Reinforcement Learning Using Simulations in the Differentiable Neural Computer
    Adeel Mufti, Svetlin Penkov, Subramanian Ramamoorthy
    http://arxiv.org/abs/1906.07248v1

    • [cs.LG]Language as an Abstraction for Hierarchical Deep Reinforcement Learning
    Yiding Jiang, Shixiang Gu, Kevin Murphy, Chelsea Finn
    http://arxiv.org/abs/1906.07343v1

    • [cs.LG]Learning Execution through Neural Code Fusion
    Zhan Shi, Kevin Swersky, Daniel Tarlow, Parthasarathy Ranganathan, Milad Hashemi
    http://arxiv.org/abs/1906.07181v1

    • [cs.LG]Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
    Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Arechiga, Tengyu Ma
    http://arxiv.org/abs/1906.07413v1

    • [cs.LG]Learning Personalized Attribute Preference via Multi-task AUC Optimization
    Zhiyong Yang, Qianqian Xu, Xiaochun Cao, Qingming Huang
    http://arxiv.org/abs/1906.07341v1

    • [cs.LG]Lower Bounds and Conditioning of Differentiable Games
    Adam Ibrahim, Waïss Azizian, Gauthier Gidel, Ioannis Mitliagkas
    http://arxiv.org/abs/1906.07300v1

    • [cs.LG]Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles
    Siddhartha Jain, Ge Liu, Jonas Mueller, David Gifford
    http://arxiv.org/abs/1906.07380v1

    • [cs.LG]Neurally-Guided Structure Inference
    Sidi Lu, Jiayuan Mao, Joshua B. Tenenbaum, Jiajun Wu
    http://arxiv.org/abs/1906.07304v1

    • [cs.LG]Online Matrix Completion with Side Information
    Mark Herbster, Stephen Pasteris, Lisa Tse
    http://arxiv.org/abs/1906.07255v1

    • [cs.LG]Prune and Replace NAS
    Kevin Alexander Laube, Andreas Zell
    http://arxiv.org/abs/1906.07528v1

    • [cs.LG]RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration
    Brahma S. Pavse, Faraz Torabi, Josiah P. Hanna, Garrett Warnell, Peter Stone
    http://arxiv.org/abs/1906.07372v1

    • [cs.LG]Robust Reinforcement Learning for Continuous Control with Model Misspecification
    Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Timothy Mann, Todd Hester, Martin Riedmiller
    http://arxiv.org/abs/1906.07516v1

    • [cs.LG]Sample-efficient Adversarial Imitation Learning from Observation
    Faraz Torabi, Sean Geiger, Garrett Warnell, Peter Stone
    http://arxiv.org/abs/1906.07374v1

    • [cs.LG]Simple Algorithms for Dueling Bandits
    Tyler Lekang, Andrew Lamperski
    http://arxiv.org/abs/1906.07611v1

    • [cs.LG]The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers
    Alex X. Lu, Amy X. Lu, Wiebke Schormann, David W. Andrews, Alan M. Moses
    http://arxiv.org/abs/1906.07282v1

    • [cs.LG]The Multiplicative Noise in Stochastic Gradient Descent: Data-Dependent Regularization, Continuous and Discrete Approximation
    Jingfeng Wu, Wenqing Hu, Haoyi Xiong, Jun Huan, Zhanxing Zhu
    http://arxiv.org/abs/1906.07405v1

    • [cs.LG]TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial
    Shaosheng Cao, Xinxing Yang, Cen Chen, Jun Zhou, Xiaolong Li, Yuan Qi
    http://arxiv.org/abs/1906.07407v1

    • [cs.LG]Towards White-box Benchmarks for Algorithm Control
    André Biedenkapp, H. Furkan Bozkurt, Frank Hutter, Marius Lindauer
    http://arxiv.org/abs/1906.07644v1

    • [cs.LG]Unsupervised machine learning to analyse city logistics through Twitter
    Simon Tamayo, François Combes, Gaudron Arthur
    http://arxiv.org/abs/1906.07529v1

    • [cs.NI]MQTTg: An Android Implementation
    Andrew Fisher, Gautam Srivastava, Robert Bryce
    http://arxiv.org/abs/1906.07162v1

    • [cs.PF]MultiCloud Resource Management using Apache Mesos with Apache Airavata
    Pankaj Saha, Madhusudhan Govindaraju, Suresh Marru, Marlon Pierce
    http://arxiv.org/abs/1906.07312v1

    • [cs.PL]The Mathematical Specification of the Statebox Language
    Statebox Team, Fabrizio Genovese
    http://arxiv.org/abs/1906.07629v1

    • [cs.RO]Chemotaxis Based Virtual Fence for Swarm Robots in Unbounded Environments
    Simon O. Obute, Mehmet R. Dogar, Jordan H. Boyle
    http://arxiv.org/abs/1906.07492v1

    • [cs.RO]Design and Characterization of the Dynamic Robotic Actuator Dyrac
    Manuel Aiple, Wouter Gregoor, Andre Schiele
    http://arxiv.org/abs/1906.07669v1

    • [cs.RO]Heterogeneous Robot Teams for Informative Sampling
    Travis Manderson, Sandeep Manjanna, Gregory Dudek
    http://arxiv.org/abs/1906.07208v1

    • [cs.RO]Providentia — A Large Scale Sensing System for the Assistance of Autonomous Vehicles
    Annkathrin Krämmer, Christoph Schöller, Dhiraj Gulati, Alois Knoll
    http://arxiv.org/abs/1906.06789v2

    • [cs.RO]Visual Navigation by Generating Next Expected Observations
    Qiaoyun Wu, Dinesh Manocha, Jun Wang, Kai Xu
    http://arxiv.org/abs/1906.07207v1

    • [cs.RO]Whole-Body Control with (Self) Collision Avoidance using Vector Field Inequalities
    Juan José Quiroz-Omaña, Bruno Vilhena Adorno
    http://arxiv.org/abs/1906.07322v1

    • [cs.SE]Losing Confidence in Quality: Unspoken Evolution of Computer Vision Services
    Alex Cummaudo, Rajesh Vasa, John Grundy, Mohamed Abdelrazek, Andrew Cain
    http://arxiv.org/abs/1906.07328v1

    • [cs.SE]Reputation Systems — Fair allocation of points to the editors in the collaborative community
    Shubhendra Pal Singhal
    http://arxiv.org/abs/1906.07339v1

    • [cs.SI]20 Years of Mobility Modeling & Prediction: Trends, Shortcomings & Perspectives
    Vaibhav Kulkarni, Benoit Garbinato
    http://arxiv.org/abs/1906.07451v1

    • [cs.SI]DISCO: Influence Maximization Meets Network Embedding and Deep Learning
    Hui Li, Mengting Xu, Sourav S Bhowmick, Changsheng Sun, Zhongyuan Jiang, Jiangtao Cui
    http://arxiv.org/abs/1906.07378v1

    • [cs.SI]Knowledge Network System (KNS) by Evolutionary Collective Intelligence (ECI): Model, Algorithm and Applications
    Tao Xiang, Ziliang Huang, Peng Bai, Congrui Ji, Zhiyong Liu
    http://arxiv.org/abs/1906.07358v1

    • [cs.SI]vGraph: A Generative Model for Joint Community Detection and Node Representation Learning
    Fan-Yun Sun, Meng Qu, Jordan Hoffmann, Chin-Wei Huang, Jian Tang
    http://arxiv.org/abs/1906.07159v1

    • [eess.AS]A Unified Speaker Adaptation Method for Speech Synthesis using Transcribed and Untranscribed Speech with Backpropagation
    Hieu-Thi Luong, Junichi Yamagishi
    http://arxiv.org/abs/1906.07414v1

    • [eess.AS]Combining Adversarial Training and Disentangled Speech Representation for Robust Zero-Resource Subword Modeling
    Siyuan Feng, Tan Lee, Zhiyuan Peng
    http://arxiv.org/abs/1906.07234v1

    • [eess.AS]Margin Matters: Towards More Discriminative Deep Neural Network Embeddings for Speaker Recognition
    Xu Xiang, Shuai Wang, Houjun Huang, Yanmin Qian, Kai Yu
    http://arxiv.org/abs/1906.07317v1

    • [eess.IV]4D CNN for semantic segmentation of cardiac volumetric sequences
    Andriy Myronenko, Dong Yang, Varun Buch, Daguang Xu, Alvin Ihsani, Sean Doyle, Mark Michalski, Neil Tenenholtz, Holger Roth
    http://arxiv.org/abs/1906.07295v1

    • [eess.IV]A Conditional Random Field Model for Context Aware Cloud Detection in Sky Images
    Vijai T. Jayadevan, Jeffrey J. Rodriguez, Alexander D. Cronin
    http://arxiv.org/abs/1906.07383v1

    • [eess.IV]An Attention-Guided Deep Regression Model for Landmark Detection in Cephalograms
    Zhusi Zhong, Jie Li, Zhenxi Zhang, Zhicheng Jiao, Xinbo Gao
    http://arxiv.org/abs/1906.07549v1

    • [eess.IV]Cardiac Segmentation from LGE MRI Using Deep Neural Network Incorporating Shape and Spatial Priors
    Qian Yue, Xinzhe Luo, Qing Ye, Lingchao Xu, Xiahai Zhuang
    http://arxiv.org/abs/1906.07347v1

    • [eess.IV]Deep Learning Enhanced Extended Depth-of-Field for Thick Blood-Film Malaria High-Throughput Microscopy
    Petru Manescu, Lydia Neary- Zajiczek, Michael J. Shaw, Muna Elmi, Remy Claveau, Vijay Pawar, John Shawe-Taylor, Iasonas Kokkinos, Mandayam A. Srinivasan, Ikeoluwa Lagunju, Olugbemiro Sodeinde, Biobele J. Brown, Delmiro Fernandez-Reyes
    http://arxiv.org/abs/1906.07496v1

    • [eess.IV]Multiclass segmentation as multitask learning for drusen segmentation in retinal optical coherence tomography
    Rhona Asgari, José Ignacio Orlando, Sebastian Waldstein, Ferdinand Schlanitz, Magdalena Baratsits, Ursula Schmidt-Erfurth, Hrvoje Bogunović
    http://arxiv.org/abs/1906.07679v1

    • [eess.SY]Of Cores: A Partial-Exploration Framework for Markov Decision Processes
    Jan Křetínský, Tobias Meggendorfer
    http://arxiv.org/abs/1906.06931v1

    • [math.DG]Curvature effects on the empirical mean in Riemannian and affine Manifolds: a non-asymptotic high concentration expansion in the small-sample regime
    Xavier Pennec
    http://arxiv.org/abs/1906.07418v1

    • [math.DS]New Uniform Bounds for Almost Lossless Analog Compression
    Yonatan Gutman, Adam Śpiewak
    http://arxiv.org/abs/1906.07620v1

    • [math.OC]Escaping from saddle points on Riemannian manifolds
    Yue Sun, Nicolas Flammarion, Maryam Fazel
    http://arxiv.org/abs/1906.07355v1

    • [math.OC]On linear convergence of two decentralized algorithms
    Yao Li, Ming Yan
    http://arxiv.org/abs/1906.07225v1

    • [math.ST]Balakrishnan Alpha Skew Normal Distribution: Properties and Applications
    P. J. Hazarika, S. Shah, S. Chakraborty
    http://arxiv.org/abs/1906.07424v1

    • [math.ST]Efficient computation of the cumulative distribution function of a linear mixture of independent random variables
    Thomas Pitschel
    http://arxiv.org/abs/1906.07186v1

    • [math.ST]Extended Plugin Densities for Curved Exponential Families
    Michiko Okudo, Fumiyasu Komaki
    http://arxiv.org/abs/1906.07514v1

    • [math.ST]Improper vs finitely additive distributions as limits of countably additive probabilities
    Pierre Druilhet, Erwan Saint Loubert Bié
    http://arxiv.org/abs/1906.07530v1

    • [math.ST]Nonparametric estimation in a regression model with additive and multiplicative noise
    Christophe Chesneau, Salima El Kolei, Junke Kou, Fabien Navarro
    http://arxiv.org/abs/1906.07695v1

    • [math.ST]Testing goodness of fit for point processes via topological data analysis
    Christophe Ange Napoléon Biscio, Nicolas Chenavier, Christian Hirsch, Anne Marie Svane
    http://arxiv.org/abs/1906.07608v1

    • [physics.soc-ph]Quantifying Dismantlement in Disconnected Networks
    Siddharth Patwardhan
    http://arxiv.org/abs/1906.06671v1

    • [quant-ph]Parameterized quantum circuits as machine learning models
    Marcello Benedetti, Erika Lloyd, Stefan Sack
    http://arxiv.org/abs/1906.07682v1

    • [stat.AP]Template Independent Component Analysis: Targeted and Reliable Estimation of Subject-level Brain Networks using Big Data Population Priors
    Amanda F. Mejia, Mary Beth Nebel, Yikai Wang, Brian S. Caffo, Ying Guo
    http://arxiv.org/abs/1906.07294v1

    • [stat.CO](f)RFCDE: Random Forests for Conditional Density Estimation and Functional Data
    Taylor Pospisil, Ann B. Lee
    http://arxiv.org/abs/1906.07177v1

    • [stat.CO]Variational Inference with Numerical Derivatives: variance reduction through coupling
    Alexander Immer, Guillaume P. Dehaene
    http://arxiv.org/abs/1906.06914v1

    • [stat.ME]A Model-Based General Alternative to the Standardised Precipitation Index
    Erick A. Chacón-Montalván, Luke Parry, Gemma Davies, Benjamin M. Taylor
    http://arxiv.org/abs/1906.07505v1

    • [stat.ME]Blending the New Statistics with Mixture Modeling — A ROPE-based single-block Gibbs sampler for Bayesian t-tests
    Riko Kelter
    http://arxiv.org/abs/1906.07524v1

    • [stat.ME]Fast Converging and Robust Optimal Path Selection in Continuous-time Markov-switching GARCH Model
    Yinan Li, Fang Liu
    http://arxiv.org/abs/1906.07313v1

    • [stat.ME]Prediction properties of optimum response surface designs
    Heloisa M. de Oliveira, Cesar B. A. de Oliveira, Steven G. Gilmour, Luzia A. Trinca
    http://arxiv.org/abs/1906.07500v1

    • [stat.ML]Bayesian Optimization with Binary Auxiliary Information
    Yehong Zhang, Zhongxiang Dai, Kian Hsiang Low
    http://arxiv.org/abs/1906.07277v1

    • [stat.ML]Consistency of semi-supervised learning algorithms on graphs: Probit and one-hot methods
    Franca Hoffmann, Bamdad Hosseini, Zhi Ren, Andrew M. Stuart
    http://arxiv.org/abs/1906.07658v1

    • [stat.ML]Error Correcting Algorithms for Sparsely Correlated Regressors
    Andrés Corrada-Emmanuel, Edward Zahrebelski, Edward Pantridge
    http://arxiv.org/abs/1906.07291v1

    • [stat.ML]Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes
    James Requeima, Jonathan Gordon, John Bronskill, Sebastian Nowozin, Richard E. Turner
    http://arxiv.org/abs/1906.07697v1

    • [stat.ML]Model selection for high-dimensional linear regression with dependent observations
    Ching-Kang Ing
    http://arxiv.org/abs/1906.07395v1