cs.AI - 人工智能

    cs.CC - 计算复杂度 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.DM - 离散数学 cs.DS - 数据结构与算法 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.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.OC - 优化与控制 math.ST - 统计理论 physics.data-an - 数据分析、 统计和概率 q-bio.GN - 基因组学 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]A Computational-Hermeneutic Approach for Conceptual Explicitation
    • [cs.AI]A new approach to forecasting service parts demand by integrating user preferences into multi-objective optimization
    • [cs.AI]Efficient predicate invention using shared “NeMuS”
    • [cs.AI]Self-organized inductive reasoning with NeMuS
    • [cs.AI]Towards Empathetic Planning
    • [cs.CC]Running Time Analysis of the (1+1)-EA for Robust Linear Optimization
    • [cs.CL]”My Way of Telling a Story”: Persona based Grounded Story Generation
    • [cs.CL]A Hierarchical Attention Based Seq2seq Model for Chinese Lyrics Generation
    • [cs.CL]A weakly supervised sequence tagging and grammar induction approach to semantic frame slot filling
    • [cs.CL]Adversarial Training for Multilingual Acoustic Modeling
    • [cs.CL]An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis
    • [cs.CL]Avoiding Reasoning Shortcuts: Adversarial Evaluation, Training, and Model Development for Multi-Hop QA
    • [cs.CL]BERE: An accurate distantly supervised biomedical entity relation extraction network
    • [cs.CL]Can neural networks understand monotonicity reasoning?
    • [cs.CL]Context is Key: Grammatical Error Detection with Contextual Word Representations
    • [cs.CL]Context-aware Embedding for Targeted Aspect-based Sentiment Analysis
    • [cs.CL]Correlating Twitter Language with Community-Level Health Outcomes
    • [cs.CL]Coupling Retrieval and Meta-Learning for Context-Dependent Semantic Parsing
    • [cs.CL]Improving Background Based Conversation with Context-aware Knowledge Pre-selection
    • [cs.CL]Interconnected Question Generation with Coreference Alignment and Conversation Flow Modeling
    • [cs.CL]Making Fast Graph-based Algorithms with Graph Metric Embeddings
    • [cs.CL]Manipulating the Difficulty of C-Tests
    • [cs.CL]Multi-Hop Paragraph Retrieval for Open-Domain Question Answering
    • [cs.CL]Multi-Level Matching and Aggregation Network for Few-Shot Relation Classification
    • [cs.CL]Neural Decipherment via Minimum-Cost Flow: from Ugaritic to Linear B
    • [cs.CL]Open Domain Event Extraction Using Neural Latent Variable Models
    • [cs.CL]Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good
    • [cs.CL]Practical User Feedback-driven Internal Search Using Online Learning to Rank
    • [cs.CL]Principled Frameworks for Evaluating Ethics in NLP Systems
    • [cs.CL]Recursive Style Breach Detection with Multifaceted Ensemble Learning
    • [cs.CL]Robust Zero-Shot Cross-Domain Slot Filling with Example Values
    • [cs.CL]Scalable Syntax-Aware Language Models Using Knowledge Distillation
    • [cs.CL]Tagged Back-Translation
    • [cs.CL]Theoretical Limitations of Self-Attention in Neural Sequence Models
    • [cs.CL]Towards Integration of Statistical Hypothesis Tests into Deep Neural Networks
    • [cs.CL]Using Automatically Extracted Minimum Spans to Disentangle Coreference Evaluation from Boundary Detection
    • [cs.CR]A Secure Consensus Protocol for Sidechains
    • [cs.CR]Physical Integrity Attack Detection of Surveillance Camera with Deep Learning Based Video Frame Interpolation
    • [cs.CV]A Temporal Sequence Learning for Action Recognition and Prediction
    • [cs.CV]Back-Projection based Fidelity Term for Ill-Posed Linear Inverse Problems
    • [cs.CV]Beyond Product Quantization: Deep Progressive Quantization for Image Retrieval
    • [cs.CV]Boosting Supervision with Self-Supervision for Few-shot Learning
    • [cs.CV]Deep Recurrent Quantization for Generating Sequential Binary Codes
    • [cs.CV]DeepMOT: A Differentiable Framework for Training Multiple Object Trackers
    • [cs.CV]Defending Against Adversarial Attacks Using Random Forests
    • [cs.CV]Delving into 3D Action Anticipation from Streaming Videos
    • [cs.CV]Detecting Bias with Generative Counterfactual Face Attribute Augmentation
    • [cs.CV]EXTD: Extremely Tiny Face Detector via Iterative Filter Reuse
    • [cs.CV]Efficient Neural Network Approaches for Leather Defect Classification
    • [cs.CV]EnlightenGAN: Deep Light Enhancement without Paired Supervision
    • [cs.CV]Exemplar Guided Face Image Super-Resolution without Facial Landmarks
    • [cs.CV]Fixing the train-test resolution discrepancy
    • [cs.CV]Floors are Flat: Leveraging Semantics for Real-Time Surface Normal Prediction
    • [cs.CV]Hallucinated Adversarial Learning for Robust Visual Tracking
    • [cs.CV]Hierarchical Back Projection Network for Image Super-Resolution
    • [cs.CV]IMP: Instance Mask Projection for High Accuracy Semantic Segmentation of Things
    • [cs.CV]Image Captioning with Integrated Bottom-Up and Multi-level Residual Top-Down Attention for Game Scene Understanding
    • [cs.CV]Image-based 3D Object Reconstruction: State-of-the-Art and Trends in the Deep Learning Era
    • [cs.CV]Improving temporal action proposal generation by using high performance computing
    • [cs.CV]Learning Part Generation and Assembly for Structure-aware Shape Synthesis
    • [cs.CV]MMDetection: Open MMLab Detection Toolbox and Benchmark
    • [cs.CV]MV-C3D: A Spatial Correlated Multi-View 3D Convolutional Neural Networks
    • [cs.CV]Machine-Assisted Map Editing
    • [cs.CV]Mask Based Unsupervised Content Transfer
    • [cs.CV]Mixture separability loss in a deep convolutional network for image classification
    • [cs.CV]Multi-Scale Convolutions for Learning Context Aware Feature Representations
    • [cs.CV]Multi-task Learning For Detecting and Segmenting Manipulated Facial Images and Videos
    • [cs.CV]NLH: A Blind Pixel-level Non-local Method for Real-world Image Denoising
    • [cs.CV]Noisy-As-Clean: Learning Unsupervised Denoising from the Corrupted Image
    • [cs.CV]On the Self-Similarity of Natural Stochastic Textures
    • [cs.CV]On training deep networks for satellite image super-resolution
    • [cs.CV]Panoptic Image Annotation with a Collaborative Assistant
    • [cs.CV]ParNet: Position-aware Aggregated Relation Network for Image-Text matching
    • [cs.CV]RECAL: Reuse of Established CNN classifer Apropos unsupervised Learning paradigm
    • [cs.CV]REMAP: Multi-layer entropy-guided pooling of dense CNN features for image retrieval
    • [cs.CV]Realistic Speech-Driven Facial Animation with GANs
    • [cs.CV]STAR: A Structure and Texture Aware Retinex Model
    • [cs.CV]Semi-Supervised Semantic Mapping through Label Propagation with Semantic Texture Meshes
    • [cs.CV]Spatio-Temporal Fusion Networks for Action Recognition
    • [cs.CV]Three-Dimensional Fourier Scattering Transform and Classification of Hyperspectral Images
    • [cs.CV]Towards Real-Time Action Recognition on Mobile Devices Using Deep Models
    • [cs.CV]Uncovering Why Deep Neural Networks Lack Robustness: Representation Metrics that Link to Adversarial Attacks
    • [cs.CV]VRED: A Position-Velocity Recurrent Encoder-Decoder for Human Motion Prediction
    • [cs.CY]A multi-layered blockchain framework for smart mobility data-markets
    • [cs.CY]AI Ethics — Too Principled to Fail?
    • [cs.DB]Distributed Subtrajectory Clustering
    • [cs.DC]Accelerating Concurrent Heap on GPUs
    • [cs.DC]Near Optimal Coflow Scheduling in Networks
    • [cs.DC]Self-Stabilizing Snapshot Objects for Asynchronous Fail-Prone Network Systems
    • [cs.DC]Service Placement with Provable Guarantees in Heterogeneous Edge Computing Systems
    • [cs.DM]A concise guide to existing and emerging vehicle routing problem variants
    • [cs.DS]A New Family of Tractable Ising Models
    • [cs.DS]Monotonically relaxing concurrent data-structure semantics for performance: An efficient 2D design framework
    • [cs.GR]A Statistical View on Synthetic Aperture Imaging for Occlusion Removal
    • [cs.IR]A Multi-Task Architecture on Relevance-based Neural Query Translation
    • [cs.IR]A Strategy for Expert Recommendation From Open Data Available on the Lattes Platform
    • [cs.IR]A formal approach for customization of schema.org based on SHACL
    • [cs.IR]A/B Testing Measurement Framework for Recommendation Models Based on Expected Revenue
    • [cs.IR]ConTrOn: Continuously Trained Ontology based on Technical Data Sheets and Wikidata
    • [cs.IR]Relevance Feedback with Latent Variables in Riemann spaces
    • [cs.IR]SEntNet: Source-aware Recurrent Entity Network for Dialogue Response Selection
    • [cs.IT]An End-to-End Block Autoencoder For Physical Layer Based On Neural Networks
    • [cs.IT]Constructions and necessities of some permutation polynomials
    • [cs.IT]Covert Communication Over a Compound Channel
    • [cs.IT]Density Evolution Analysis of Partially Information Coupled Turbo Codes on the Erasure Channel
    • [cs.IT]Distributed Source Simulation With No Communication
    • [cs.IT]Large Intelligent Surface/Antennas (LISA): Making Reflective Radios Smart
    • [cs.IT]Lattice Coding for Downlink Multiuser Transmission
    • [cs.IT]On the Performance of Low-Altitude UAV-Enabled Secure AF Relaying with Cooperative Jamming and SWIPT
    • [cs.IT]Optimal Power Control for Over-the-Air Computation in Fading Channels
    • [cs.IT]Performance Analysis of Blockchain Systems with Wireless Mobile Miners
    • [cs.IT]Uplink Non-Orthogonal Multiple Access for UAV Communications
    • [cs.LG]A Closer Look at Double Backpropagation
    • [cs.LG]A General Interpretation of Deep Learning by Affine Transform and Region Dividing without Mutual Interference
    • [cs.LG]A Provably Correct and Robust Algorithm for Convolutive Nonnegative Matrix Factorization
    • [cs.LG]A Survey of Optimization Methods from a Machine Learning Perspective
    • [cs.LG]ASAC: Active Sensing using Actor-Critic models
    • [cs.LG]Active Generative Adversarial Network for Image Classification
    • [cs.LG]Active Learning by Greedy Split and Label Exploration
    • [cs.LG]Adversarial attacks on Copyright Detection Systems
    • [cs.LG]Asymptotic Risk of Bezier Simplex Fitting
    • [cs.LG]Attributed Graph Clustering: A Deep Attentional Embedding Approach
    • [cs.LG]Characterizing the Exact Behaviors of Temporal Difference Learning Algorithms Using Markov Jump Linear System Theory
    • [cs.LG]CheckNet: Secure Inference on Untrusted Devices
    • [cs.LG]Conditional Computation for Continual Learning
    • [cs.LG]Dataset shift quantification for credit card fraud detection
    • [cs.LG]Dealing with the database variability problem in learning from medical data: an ensemble-based approach using convolutional neural networks and a case of study applied to automatic sleep scoring
    • [cs.LG]Deep Learning of Preconditioners for Conjugate Gradient Solvers in Urban Water Related Problems
    • [cs.LG]Deep Set Prediction Networks
    • [cs.LG]Exact and Consistent Interpretation of Piecewise Linear Models Hidden behind APIs: A Closed Form Solution
    • [cs.LG]Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias
    • [cs.LG]Fixing Gaussian Mixture VAEs for Interpretable Text Generation
    • [cs.LG]Generating Diverse and Informative Natural Language Fashion Feedback
    • [cs.LG]Global optimization via inverse distance weighting
    • [cs.LG]Hierarchical Soft Actor-Critic: Adversarial Exploration via Mutual Information Optimization
    • [cs.LG]High-Performance Deep Learning via a Single Building Block
    • [cs.LG]Improving Black-box Adversarial Attacks with a Transfer-based Prior
    • [cs.LG]Injecting Prior Knowledge for Transfer Learning into Reinforcement Learning Algorithms using Logic Tensor Networks
    • [cs.LG]Is the Policy Gradient a Gradient?
    • [cs.LG]Joint Visual-Textual Embedding for Multimodal Style Search
    • [cs.LG]LPaintB: Learning to Paint from Self-SupervisionLPaintB: Learning to Paint from Self-Supervision
    • [cs.LG]Learning Interpretable Models Using an Oracle
    • [cs.LG]Learning Restricted Boltzmann Machines with Arbitrary External Fields
    • [cs.LG]Learning-Driven Exploration for Reinforcement Learning
    • [cs.LG]LioNets: Local Interpretation of Neural Networks through Penultimate Layer Decoding
    • [cs.LG]MixUp as Directional Adversarial Training
    • [cs.LG]Model Compression by Entropy Penalized Reparameterization
    • [cs.LG]MoËT: Interpretable and Verifiable Reinforcement Learning via Mixture of Expert Trees
    • [cs.LG]Multi-Adversarial Variational Autoencoder Networks
    • [cs.LG]Neural Theorem Provers Do Not Learn Rules Without Exploration
    • [cs.LG]Normalizing flows for novelty detection in industrial time series data
    • [cs.LG]One Epoch Is All You Need
    • [cs.LG]Personalized Apprenticeship Learning from Heterogeneous Decision-Makers
    • [cs.LG]Reconciling Utility and Membership Privacy via Knowledge Distillation
    • [cs.LG]Recovering the parameters underlying the Lorenz-96 chaotic dynamics
    • [cs.LG]Reinforcement Learning Driven Heuristic Optimization
    • [cs.LG]Robust Federated Learning in a Heterogeneous Environment
    • [cs.LG]Robust or Private? Adversarial Training Makes Models More Vulnerable to Privacy Attacks
    • [cs.LG]Sample-Efficient Neural Architecture Search by Learning Action Space
    • [cs.LG]Scrubbing Sensitive PHI Data from Medical Records made Easy by SpaCy — A Scalable Model Implementation Comparisons
    • [cs.LG]Solution of Two-Player Zero-Sum Game by Successive Relaxation
    • [cs.LG]Structured Pruning of Recurrent Neural Networks through Neuron Selection
    • [cs.LG]The Attack Generator: A Systematic Approach Towards Constructing Adversarial Attacks
    • [cs.NE]Accelerating Neural ODEs with Spectral Elements
    • [cs.NE]Rapid online learning and robust recall in a neuromorphic olfactory circuit
    • [cs.NI]Supporting Web Archiving via Web Packaging
    • [cs.RO]A Fast and Stable Omnidirectional Walking Engine for the Nao Humanoid Robot
    • [cs.RO]Combining Safe Interval Path Planning and Constrained Path Following Control: Preliminary Results
    • [cs.RO]DeepTemporalSeg: Temporally Consistent Semantic Segmentation of 3D LiDAR Scans
    • [cs.RO]Designing, 3D Printing of a Quadruped Robot and Choice of Materials for Fabrication
    • [cs.RO]Embracing Contact: Pushing Multiple Objects with Robot’s Forearm
    • [cs.RO]Exploiting Physical Contacts for Robustness Improvement of a Dot-Painting Mission by a Micro Air Vehicle
    • [cs.RO]Providentia — A Large Scale Sensing System for the Assistance of Autonomous Vehicles
    • [cs.RO]Reinforcement Learning with Non-uniform State Representations for Adaptive Search
    • [cs.RO]Robotic Navigation using Entropy-Based Exploration
    • [cs.RO]Simple Swarm Foraging Algorithm Based on Gradient Computation
    • [cs.RO]Trajectory Tracking for Quadrotors with Attitude Control on $\mathcal{S}^2 \times \mathcal{S}^1$
    • [cs.RO]Understanding Natural Language Instructions for Fetching Daily Objects Using GAN-Based Multimodal Target-Source Classification
    • [cs.RO]Usability Squared: Principles for doing good systems research in robotics
    • [cs.RO]ViTa-SLAM: A Bio-inspired Visuo-Tactile SLAM for Navigation while Interacting with Aliased Environments
    • [cs.SD]Modeling Consonance and its Relationships with Temperament, Harmony, and Electronic Amplification
    • [cs.SD]Modeling Music Modality with a Key-Class Invariant Pitch Chroma CNN
    • [cs.SD]Multi-scale Embedded CNN for Music Tagging (MsE-CNN)
    • [cs.SE]Machine Learning Software Engineering in Practice: An Industrial Case Study
    • [cs.SI]Homogeneous Network Embedding for Massive Graphs via Personalized PageRank
    • [cs.SI]Interactive health communication and the construction of the identity of the person with low vision in social media
    • [cs.SI]Linear-time Hierarchical Community Detection
    • [cs.SI]Media Environment, Dual Process and Polarization: A Computational Approach
    • [cs.SI]Supracentrality Analysis of Temporal Networks with Directed Interlayer Coupling
    • [econ.EM]Posterior Average Effects
    • [eess.IV]4D X-Ray CT Reconstruction using Multi-Slice Fusion
    • [eess.IV]A Fusion Adversarial Network for Underwater Image Enhancement
    • [eess.IV]Differentiated Backprojection Domain Deep Learning for Conebeam Artifact Removal
    • [eess.IV]Particle Swarm Optimization for Great Enhancement in Semi-Supervised Retinal Vessel Segmentation with Generative Adversarial Networks
    • [eess.IV]Single Image Super-resolution via Dense Blended Attention Generative Adversarial Network for Clinical Diagnosis
    • [eess.IV]Speeding up VP9 Intra Encoder with Hierarchical Deep Learning Based Partition Prediction
    • [eess.SP]Beam Entropy of 5G Cellular Millimetre Wave Channels
    • [eess.SP]Deep Recurrent Adversarial Learning for Privacy-Preserving Smart Meter Data Release
    • [math.OC]An efficient Lagrangian-based heuristic to solve a multi-objective sustainable supply chain problem
    • [math.OC]Productivity equation and the m distributions of information processing in workflows
    • [math.ST]Community Detection Based on the $L_\infty$ convergence of eigenvectors in DCBM
    • [math.ST]Designing Test Information and Test Information in Design
    • [math.ST]Minimax Density Estimation on Sobolev Spaces With Dominating Mixed Smoothness
    • [math.ST]On the Locally Lipschitz Robustness of Bayesian Inverse Problems
    • [physics.data-an]Detecting new signals under background mismodelling
    • [q-bio.GN]Nested partitions from hierarchical clustering statistical validation
    • [stat.AP]Bayesian Finite Population Modeling for Spatial Process Settings
    • [stat.AP]Bayesian spatial extreme value analysis of maximum temperatures in County Dublin, Ireland
    • [stat.AP]Identifying and characterizing extrapolation in multivariateresponse data
    • [stat.AP]Linear regression with stationary errors : the R package slm
    • [stat.AP]Parametric and non-parametric estimation of extreme earthquake event: the joint tail inference for mainshocks and aftershocks
    • [stat.CO]A tunable multiresolution smoother for scattered data with application to particle filtering
    • [stat.CO]lpdensity: Local Polynomial Density Estimation and Inference
    • [stat.ME]Adaptive Variable Selection for Sequential Prediction in Multivariate Dynamic Models
    • [stat.ME]An Optimal Test for the Additive Model with Discrete or Categorical Predictors
    • [stat.ME]Depth-based Weighted Jackknife Empirical Likelihood for Non-smooth U-structure Equations
    • [stat.ME]From Incomplete, Dynamic Data to Bayesian Networks
    • [stat.ME]Hierarchical Total Variations and Doubly Penalized ANOVA Modeling for Multivariate Nonparametric Regression
    • [stat.ME]Linear Aggregation in Tree-based Estimators
    • [stat.ME]Non parametric estimation of Joint entropy and Shannon mutual information, Asymptotic limits: Application to statistic tests
    • [stat.ME]Probabilistic Diffusion MRI Fiber Tracking Using a Directed Acyclic Graph Auto-Regressive Model of Positive Definite Matrices
    • [stat.ME]Sample Size Calculations for SMARTs
    • [stat.ML]A Bayesian Solution to the M-Bias Problem
    • [stat.ML]Automatic Relevance Determination Bayesian Neural Networks for Credit Card Default Modelling
    • [stat.ML]Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities
    • [stat.ML]Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Accuracy
    • [stat.ML]Metric on random dynamical systems with vector-valued reproducing kernel Hilbert spaces
    • [stat.ML]Replacing the do-calculus with Bayes rule
    • [stat.ML]Sampler for Composition Ratio by Markov Chain Monte Carlo
    • [stat.ML]Smooth function approximation by deep neural networks with general activation functions
    • [stat.ML]Stacked Capsule Autoencoders
    • [stat.ML]The Price of Local Fairness in Multistage Selection
    • [stat.ML]The True Sample Complexity of Identifying Good Arms

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

    • [cs.AI]A Computational-Hermeneutic Approach for Conceptual Explicitation
    David Fuenmayor, Christoph Benzmüller
    http://arxiv.org/abs/1906.06582v1

    • [cs.AI]A new approach to forecasting service parts demand by integrating user preferences into multi-objective optimization
    Wenli Ouyang
    http://arxiv.org/abs/1906.06816v1

    • [cs.AI]Efficient predicate invention using shared “NeMuS”
    Edjard Mota, Jacob M. Howe, Ana Schramm, Artur d’Avila Garcez
    http://arxiv.org/abs/1906.06455v1

    • [cs.AI]Self-organized inductive reasoning with NeMuS
    Leonardo Barreto, Edjard Mota
    http://arxiv.org/abs/1906.06761v1

    • [cs.AI]Towards Empathetic Planning
    Maayan Shvo, Sheila A. McIlraith
    http://arxiv.org/abs/1906.06436v1

    • [cs.CC]Running Time Analysis of the (1+1)-EA for Robust Linear Optimization
    Chao Bian, Chao Qian, Ke Tang
    http://arxiv.org/abs/1906.06873v1

    • [cs.CL]“My Way of Telling a Story”: Persona based Grounded Story Generation
    Shrimai Prabhumoye, Khyathi Raghavi Chandu, Ruslan Salakhutdinov, Alan W Black
    http://arxiv.org/abs/1906.06401v1

    • [cs.CL]A Hierarchical Attention Based Seq2seq Model for Chinese Lyrics Generation
    Haoshen Fan, Jie Wang, Bojin Zhuang, Shaojun Wang, Jing Xiao
    http://arxiv.org/abs/1906.06481v1

    • [cs.CL]A weakly supervised sequence tagging and grammar induction approach to semantic frame slot filling
    Janneke van de Loo, Guy De Pauw, Walter Daelemans
    http://arxiv.org/abs/1906.06493v1

    • [cs.CL]Adversarial Training for Multilingual Acoustic Modeling
    Ke Hu, Hasim Sak, Hank Liao
    http://arxiv.org/abs/1906.07093v1

    • [cs.CL]An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis
    Ruidan He, Wee Sun Lee, Hwee Tou Ng, Daniel Dahlmeier
    http://arxiv.org/abs/1906.06906v1

    • [cs.CL]Avoiding Reasoning Shortcuts: Adversarial Evaluation, Training, and Model Development for Multi-Hop QA
    Yichen Jiang, Mohit Bansal
    http://arxiv.org/abs/1906.07132v1

    • [cs.CL]BERE: An accurate distantly supervised biomedical entity relation extraction network
    Lixiang Hong, JinJian Lin, Jiang Tao, Jianyang Zeng
    http://arxiv.org/abs/1906.06916v1

    • [cs.CL]Can neural networks understand monotonicity reasoning?
    Hitomi Yanaka, Koji Mineshima, Daisuke Bekki, Kentaro Inui, Satoshi Sekine, Lasha Abzianidze, Johan Bos
    http://arxiv.org/abs/1906.06448v1

    • [cs.CL]Context is Key: Grammatical Error Detection with Contextual Word Representations
    Samuel Bell, Helen Yannakoudakis, Marek Rei
    http://arxiv.org/abs/1906.06593v1

    • [cs.CL]Context-aware Embedding for Targeted Aspect-based Sentiment Analysis
    Bin Liang, Jiachen Du, Ruifeng Xu, Binyang Li, Hejiao Huang
    http://arxiv.org/abs/1906.06945v1

    • [cs.CL]Correlating Twitter Language with Community-Level Health Outcomes
    Arno Schneuwly, Ralf Grubenmann, Mark Cieliebak, Martin Jaggi
    http://arxiv.org/abs/1906.06465v1

    • [cs.CL]Coupling Retrieval and Meta-Learning for Context-Dependent Semantic Parsing
    Daya Guo, Duyu Tang, Nan Duan, Ming Zhou, Jian Yin
    http://arxiv.org/abs/1906.07108v1

    • [cs.CL]Improving Background Based Conversation with Context-aware Knowledge Pre-selection
    Yangjun Zhang, Pengjie Ren, Maarten de Rijke
    http://arxiv.org/abs/1906.06685v1

    • [cs.CL]Interconnected Question Generation with Coreference Alignment and Conversation Flow Modeling
    Yifan Gao, Piji Li, Irwin King, Michael R. Lyu
    http://arxiv.org/abs/1906.06893v1

    • [cs.CL]Making Fast Graph-based Algorithms with Graph Metric Embeddings
    Andrey Kutuzov, Mohammad Dorgham, Oleksiy Oliynyk, Chris Biemann, Alexander Panchenko
    http://arxiv.org/abs/1906.07040v1

    • [cs.CL]Manipulating the Difficulty of C-Tests
    Ji-Ung Lee, Erik Schwan, Christian M. Meyer
    http://arxiv.org/abs/1906.06905v1

    • [cs.CL]Multi-Hop Paragraph Retrieval for Open-Domain Question Answering
    Yair Feldman, Ran El-Yaniv
    http://arxiv.org/abs/1906.06606v1

    • [cs.CL]Multi-Level Matching and Aggregation Network for Few-Shot Relation Classification
    Zhi-Xiu Ye, Zhen-Hua Ling
    http://arxiv.org/abs/1906.06678v1

    • [cs.CL]Neural Decipherment via Minimum-Cost Flow: from Ugaritic to Linear B
    Jiaming Luo, Yuan Cao, Regina Barzilay
    http://arxiv.org/abs/1906.06718v1

    • [cs.CL]Open Domain Event Extraction Using Neural Latent Variable Models
    Xiao Liu, Heyan Huang, Yue Zhang
    http://arxiv.org/abs/1906.06947v1

    • [cs.CL]Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good
    Xuewei Wang, Weiyan Shi, Richard Kim, Yoojung Oh, Sijia Yang, Jingwen Zhang, Zhou Yu
    http://arxiv.org/abs/1906.06725v1

    • [cs.CL]Practical User Feedback-driven Internal Search Using Online Learning to Rank
    Rajhans Samdani, Pierre Rappolt, Ankit Goyal, Pratyus Patnaik
    http://arxiv.org/abs/1906.06581v1

    • [cs.CL]Principled Frameworks for Evaluating Ethics in NLP Systems
    Shrimai Prabhumoye, Elijah Mayfield, Alan W Black
    http://arxiv.org/abs/1906.06425v1

    • [cs.CL]Recursive Style Breach Detection with Multifaceted Ensemble Learning
    Daniel Kopev, Dimitrina Zlatkova, Kristiyan Mitov, Atanas Atanasov, Momchil Hardalov, Ivan Koychev, Preslav Nakov
    http://arxiv.org/abs/1906.06917v1

    • [cs.CL]Robust Zero-Shot Cross-Domain Slot Filling with Example Values
    Darsh J Shah, Raghav Gupta, Amir A Fayazi, Dilek Hakkani-Tur
    http://arxiv.org/abs/1906.06870v1

    • [cs.CL]Scalable Syntax-Aware Language Models Using Knowledge Distillation
    Adhiguna Kuncoro, Chris Dyer, Laura Rimell, Stephen Clark, Phil Blunsom
    http://arxiv.org/abs/1906.06438v1

    • [cs.CL]Tagged Back-Translation
    Isaac Caswell, Ciprian Chelba, David Grangier
    http://arxiv.org/abs/1906.06442v1

    • [cs.CL]Theoretical Limitations of Self-Attention in Neural Sequence Models
    Michael Hahn
    http://arxiv.org/abs/1906.06755v1

    • [cs.CL]Towards Integration of Statistical Hypothesis Tests into Deep Neural Networks
    Ahmad Aghaebrahimian, Mark Cieliebak
    http://arxiv.org/abs/1906.06550v1

    • [cs.CL]Using Automatically Extracted Minimum Spans to Disentangle Coreference Evaluation from Boundary Detection
    Nafise Sadat Moosavi, Leo Born, Massimo Poesio, Michael Strube
    http://arxiv.org/abs/1906.06703v1

    • [cs.CR]A Secure Consensus Protocol for Sidechains
    Fangyu Gai, Cesar Grajales, Jianyu Niu, Chen Feng
    http://arxiv.org/abs/1906.06490v1

    • [cs.CR]Physical Integrity Attack Detection of Surveillance Camera with Deep Learning Based Video Frame Interpolation
    Jonathan Pan
    http://arxiv.org/abs/1906.06475v1

    • [cs.CV]A Temporal Sequence Learning for Action Recognition and Prediction
    Sangwoo Cho, Hassan Foroosh
    http://arxiv.org/abs/1906.06813v1

    • [cs.CV]Back-Projection based Fidelity Term for Ill-Posed Linear Inverse Problems
    Tom Tirer, Raja Giryes
    http://arxiv.org/abs/1906.06794v1

    • [cs.CV]Beyond Product Quantization: Deep Progressive Quantization for Image Retrieval
    Lianli Gao, Xiaosu Zhu, Jingkuan Song, Zhou Zhao, Heng Tao Shen
    http://arxiv.org/abs/1906.06698v1

    • [cs.CV]Boosting Supervision with Self-Supervision for Few-shot Learning
    Jong-Chyi Su, Subhransu Maji, Bharath Hariharan
    http://arxiv.org/abs/1906.07079v1

    • [cs.CV]Deep Recurrent Quantization for Generating Sequential Binary Codes
    Jingkuan Song, Xiaosu Zhu, Lianli Gao, Xin-Shun Xu, Wu Liu, Heng Tao Shen
    http://arxiv.org/abs/1906.06699v1

    • [cs.CV]DeepMOT: A Differentiable Framework for Training Multiple Object Trackers
    Yihong Xu, Yutong Ban, Xavier Alameda-Pineda, Radu Horaud
    http://arxiv.org/abs/1906.06618v1

    • [cs.CV]Defending Against Adversarial Attacks Using Random Forests
    Yifan Ding, Liqiang Wang, Huan Zhang, Jinfeng Yi, Deliang Fan, Boqing Gong
    http://arxiv.org/abs/1906.06765v1

    • [cs.CV]Delving into 3D Action Anticipation from Streaming Videos
    Hongsong Wang, Jiashi Feng
    http://arxiv.org/abs/1906.06521v1

    • [cs.CV]Detecting Bias with Generative Counterfactual Face Attribute Augmentation
    Emily Denton, Ben Hutchinson, Margaret Mitchell, Timnit Gebru
    http://arxiv.org/abs/1906.06439v1

    • [cs.CV]EXTD: Extremely Tiny Face Detector via Iterative Filter Reuse
    YoungJoon Yoo, Dongyoon Han, Sangdoo Yun
    http://arxiv.org/abs/1906.06579v1

    • [cs.CV]Efficient Neural Network Approaches for Leather Defect Classification
    Sze-Teng Liong, Y. S. Gan, Kun-Hong Liu, Tran Quang Binh, Cong Tue Le, Chien An Wu, Cheng-Yan Yang, Yen-Chang Huang
    http://arxiv.org/abs/1906.06446v1

    • [cs.CV]EnlightenGAN: Deep Light Enhancement without Paired Supervision
    Yifan Jiang, Xinyu Gong, Ding Liu, Yu Cheng, Chen Fang, Xiaohui Shen, Jianchao Yang, Pan Zhou, Zhangyang Wang
    http://arxiv.org/abs/1906.06972v1

    • [cs.CV]Exemplar Guided Face Image Super-Resolution without Facial Landmarks
    Berk Dogan, Shuhang Gu, Radu Timofte
    http://arxiv.org/abs/1906.07078v1

    • [cs.CV]Fixing the train-test resolution discrepancy
    Hugo Touvron, Andrea Vedaldi, Matthijs Douze, Hervé Jégou
    http://arxiv.org/abs/1906.06423v1

    • [cs.CV]Floors are Flat: Leveraging Semantics for Real-Time Surface Normal Prediction
    Steven Hickson, Karthik Raveendran, Alireza Fathi, Kevin Murphy, Irfan Essa
    http://arxiv.org/abs/1906.06792v1

    • [cs.CV]Hallucinated Adversarial Learning for Robust Visual Tracking
    Qiangqiang Wu, Zhihui Chen, Lin Cheng, Yan Yan, Bo Li, Hanzi Wang
    http://arxiv.org/abs/1906.07008v1

    • [cs.CV]Hierarchical Back Projection Network for Image Super-Resolution
    Zhi-Song Liu, Li-Wen Wang, Chu-Tak Li, Wan-Chi Siu
    http://arxiv.org/abs/1906.06874v1

    • [cs.CV]IMP: Instance Mask Projection for High Accuracy Semantic Segmentation of Things
    Cheng-Yang Fu, Tamara L. Berg, Alexander C. Berg
    http://arxiv.org/abs/1906.06597v1

    • [cs.CV]Image Captioning with Integrated Bottom-Up and Multi-level Residual Top-Down Attention for Game Scene Understanding
    Jian Zheng, Sudha Krishnamurthy, Ruxin Chen, Min-Hung Chen, Zhenhao Ge, Xiaohua Li
    http://arxiv.org/abs/1906.06632v1

    • [cs.CV]Image-based 3D Object Reconstruction: State-of-the-Art and Trends in the Deep Learning Era
    Xian-Feng Han, Hamid Laga, Mohammed Bennamoun
    http://arxiv.org/abs/1906.06543v1

    • [cs.CV]Improving temporal action proposal generation by using high performance computing
    Tian Wang, Shiye Lei, Youyou Jiang, Zihang Deng, Xin Su, Hichem Snoussi, Chang Choi
    http://arxiv.org/abs/1906.06496v1

    • [cs.CV]Learning Part Generation and Assembly for Structure-aware Shape Synthesis
    Jun Li, Chengjie Niu, Kai Xu
    http://arxiv.org/abs/1906.06693v1

    • [cs.CV]MMDetection: Open MMLab Detection Toolbox and Benchmark
    Kai Chen, Jiaqi Wang, Jiangmiao Pang, Yuhang Cao, Yu Xiong, Xiaoxiao Li, Shuyang Sun, Wansen Feng, Ziwei Liu, Jiarui Xu, Zheng Zhang, Dazhi Cheng, Chenchen Zhu, Tianheng Cheng, Qijie Zhao, Buyu Li, Xin Lu, Rui Zhu, Yue Wu, Jifeng Dai, Jingdong Wang, Jianping Shi, Wanli Ouyang, Chen Change Loy, Dahua Lin
    http://arxiv.org/abs/1906.07155v1

    • [cs.CV]MV-C3D: A Spatial Correlated Multi-View 3D Convolutional Neural Networks
    Qi Xuan, Fuxian Li, Yi Liu, Yun Xiang
    http://arxiv.org/abs/1906.06538v1

    • [cs.CV]Machine-Assisted Map Editing
    Favyen Bastani, Songtao He, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Sam Madden
    http://arxiv.org/abs/1906.07138v1

    • [cs.CV]Mask Based Unsupervised Content Transfer
    Ron Mokady, Sagie Benaim, Lior Wolf, Amit Bermano
    http://arxiv.org/abs/1906.06558v1

    • [cs.CV]Mixture separability loss in a deep convolutional network for image classification
    Trung Dung Do, Cheng-Bin Jin, Hakil Kim, Van Huan Nguyen
    http://arxiv.org/abs/1906.06633v1

    • [cs.CV]Multi-Scale Convolutions for Learning Context Aware Feature Representations
    Nikolai Ufer, Kam To Lui, Katja Schwarz, Paul Warkentin, Björn Ommer
    http://arxiv.org/abs/1906.06978v1

    • [cs.CV]Multi-task Learning For Detecting and Segmenting Manipulated Facial Images and Videos
    Huy H. Nguyen, Fuming Fang, Junichi Yamagishi, Isao Echizen
    http://arxiv.org/abs/1906.06876v1

    • [cs.CV]NLH: A Blind Pixel-level Non-local Method for Real-world Image Denoising
    Yingkun Hou, Jun Xu, Mingxia Liu, Guanghai Liu, Li Liu, Fan Zhu, Ling Shao
    http://arxiv.org/abs/1906.06834v1

    • [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/1906.06878v1

    • [cs.CV]On the Self-Similarity of Natural Stochastic Textures
    Samah Khawaled, Yehoshua Y. Zeevi
    http://arxiv.org/abs/1906.06768v1

    • [cs.CV]On training deep networks for satellite image super-resolution
    Michal Kawulok, Szymon Piechaczek, Krzysztof Hrynczenko, Pawel Benecki, Daniel Kostrzewa, Jakub Nalepa
    http://arxiv.org/abs/1906.06697v1

    • [cs.CV]Panoptic Image Annotation with a Collaborative Assistant
    Jasper R. R. Uijlings, Mykhaylo Andriluka, Vittorio Ferrari
    http://arxiv.org/abs/1906.06798v1

    • [cs.CV]ParNet: Position-aware Aggregated Relation Network for Image-Text matching
    Yaxian Xia, Lun Huang, Wenmin Wang, Xiaoyong Wei, Wenmin Wang
    http://arxiv.org/abs/1906.06892v1

    • [cs.CV]RECAL: Reuse of Established CNN classifer Apropos unsupervised Learning paradigm
    Jayasree Saha, Jayanta Mukhopadhyay
    http://arxiv.org/abs/1906.06480v1

    • [cs.CV]REMAP: Multi-layer entropy-guided pooling of dense CNN features for image retrieval
    Syed Sameed Husain, Miroslaw Bober
    http://arxiv.org/abs/1906.06626v1

    • [cs.CV]Realistic Speech-Driven Facial Animation with GANs
    Konstantinos Vougioukas, Stavros Petridis, Maja Pantic
    http://arxiv.org/abs/1906.06337v1

    • [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/1906.06690v1

    • [cs.CV]Semi-Supervised Semantic Mapping through Label Propagation with Semantic Texture Meshes
    Radu Alexandru Rosu, Jan Quenzel, Sven Behnke
    http://arxiv.org/abs/1906.07029v1

    • [cs.CV]Spatio-Temporal Fusion Networks for Action Recognition
    Sangwoo Cho, Hassan Foroosh
    http://arxiv.org/abs/1906.06822v1

    • [cs.CV]Three-Dimensional Fourier Scattering Transform and Classification of Hyperspectral Images
    Ilya Kavalerov, Weilin Li, Wojciech Czaja, Rama Chellappa
    http://arxiv.org/abs/1906.06804v1

    • [cs.CV]Towards Real-Time Action Recognition on Mobile Devices Using Deep Models
    Chen-Lin Zhang, Xin-Xin Liu, Jianxin Wu
    http://arxiv.org/abs/1906.07052v1

    • [cs.CV]Uncovering Why Deep Neural Networks Lack Robustness: Representation Metrics that Link to Adversarial Attacks
    Danilo Vasconcellos Vargas, Shashank Kotyan, Moe Matsuki
    http://arxiv.org/abs/1906.06627v1

    • [cs.CV]VRED: A Position-Velocity Recurrent Encoder-Decoder for Human Motion Prediction
    Hongsong Wang, Jiashi Feng
    http://arxiv.org/abs/1906.06514v1

    • [cs.CY]A multi-layered blockchain framework for smart mobility data-markets
    David Lopez, Bilal Farooq
    http://arxiv.org/abs/1906.06435v1

    • [cs.CY]AI Ethics — Too Principled to Fail?
    Brent Mittelstadt
    http://arxiv.org/abs/1906.06668v1

    • [cs.DB]Distributed Subtrajectory Clustering
    Panagiotis Tampakis, Nikos Pelekis, Christos Doulkeridis, Yannis Theodoridis
    http://arxiv.org/abs/1906.06956v1

    • [cs.DC]Accelerating Concurrent Heap on GPUs
    Yanhao Chen, Fei Hua, Chaozhang Huang, Jeremy Bierema, Chi Zhang, Eddy Z. Zhang
    http://arxiv.org/abs/1906.06504v1

    • [cs.DC]Near Optimal Coflow Scheduling in Networks
    Mosharaf Chowdhury, Samir Khuller, Manish Purohit, Sheng Yang, Jie You
    http://arxiv.org/abs/1906.06851v1

    • [cs.DC]Self-Stabilizing Snapshot Objects for Asynchronous Fail-Prone Network Systems
    Chryssis Georgiou, Oskar Lundström, Elad Michael Schiller
    http://arxiv.org/abs/1906.06420v1

    • [cs.DC]Service Placement with Provable Guarantees in Heterogeneous Edge Computing Systems
    Stephen Pasteris, Shiqiang Wang, Mark Herbster, Ting He
    http://arxiv.org/abs/1906.07055v1

    • [cs.DM]A concise guide to existing and emerging vehicle routing problem variants
    Thibaut Vidal, Gilbert Laporte, Piotr Matl
    http://arxiv.org/abs/1906.06750v1

    • [cs.DS]A New Family of Tractable Ising Models
    Valerii Likhosherstov, Yury Maximov, Michael Chertkov
    http://arxiv.org/abs/1906.06431v1

    • [cs.DS]Monotonically relaxing concurrent data-structure semantics for performance: An efficient 2D design framework
    Adones Rukundo, Aras Atalar, Philippas Tsigas
    http://arxiv.org/abs/1906.07105v1

    • [cs.GR]A Statistical View on Synthetic Aperture Imaging for Occlusion Removal
    Indrajit Kurmi, David C. Schedl, Oliver Bimber
    http://arxiv.org/abs/1906.06600v1

    • [cs.IR]A Multi-Task Architecture on Relevance-based Neural Query Translation
    Sheikh Muhammad Sarwar, Hamed Bonab, James Allan
    http://arxiv.org/abs/1906.06849v1

    • [cs.IR]A Strategy for Expert Recommendation From Open Data Available on the Lattes Platform
    Sérgio José de Sousa, Thiago Magela Rodrigues Dias, Adilson Luiz Pinto
    http://arxiv.org/abs/1906.06437v1

    • [cs.IR]A formal approach for customization of schema.org based on SHACL
    Umutcan Şimşek, Kevin Angele, Elias Kärle, Oleksandra Panasiuk, Dieter Fensel
    http://arxiv.org/abs/1906.06492v1

    • [cs.IR]A/B Testing Measurement Framework for Recommendation Models Based on Expected Revenue
    Meisam Hejazinia, Majid Hosseini, Bryant Sih
    http://arxiv.org/abs/1906.06390v1

    • [cs.IR]ConTrOn: Continuously Trained Ontology based on Technical Data Sheets and Wikidata
    Kobkaew Opasjumruskit, Diana Peters, Sirko Schindler
    http://arxiv.org/abs/1906.06752v1

    • [cs.IR]Relevance Feedback with Latent Variables in Riemann spaces
    Simone Santini
    http://arxiv.org/abs/1906.06526v1

    • [cs.IR]SEntNet: Source-aware Recurrent Entity Network for Dialogue Response Selection
    Jiahuan Pei, Arent Stienstra, Julia Kiseleva, Maarten de Rijke
    http://arxiv.org/abs/1906.06788v1

    • [cs.IT]An End-to-End Block Autoencoder For Physical Layer Based On Neural Networks
    Tianjie Mu, Xiaohui Chen, Li Chen, Huarui Yin, Weidong Wang
    http://arxiv.org/abs/1906.06563v1

    • [cs.IT]Constructions and necessities of some permutation polynomials
    Xiaogang Liu
    http://arxiv.org/abs/1906.06453v1

    • [cs.IT]Covert Communication Over a Compound Channel
    Sadaf Salehkalaibar, Mohammad Hossein Yassaee, Vincent Y. F. Tan
    http://arxiv.org/abs/1906.06675v1

    • [cs.IT]Density Evolution Analysis of Partially Information Coupled Turbo Codes on the Erasure Channel
    Min Qiu, Xiaowei Wu, Yixuan Xie, Jinhong Yuan
    http://arxiv.org/abs/1906.06649v1

    • [cs.IT]Distributed Source Simulation With No Communication
    Tomer Berg, Ofer Shayevitz, Young-Han Kim, Lele Wang
    http://arxiv.org/abs/1906.06970v1

    • [cs.IT]Large Intelligent Surface/Antennas (LISA): Making Reflective Radios Smart
    Ying-Chang Liang, Ruizhe Long, Qianqian Zhang, Jie Chen, Hei Victor Cheng, Huayan Guo
    http://arxiv.org/abs/1906.06578v1

    • [cs.IT]Lattice Coding for Downlink Multiuser Transmission
    Min Qiu
    http://arxiv.org/abs/1906.06651v1

    • [cs.IT]On the Performance of Low-Altitude UAV-Enabled Secure AF Relaying with Cooperative Jamming and SWIPT
    Milad Tatar Mamaghani, Yi Hong
    http://arxiv.org/abs/1906.06867v1

    • [cs.IT]Optimal Power Control for Over-the-Air Computation in Fading Channels
    Xiaowen Cao, Guangxu Zhu, Jie Xu, Kaibin Huang
    http://arxiv.org/abs/1906.06858v1

    • [cs.IT]Performance Analysis of Blockchain Systems with Wireless Mobile Miners
    Gilsoo Lee, Jihong Park, Walid Saad, Mehdi Bennis
    http://arxiv.org/abs/1906.06759v1

    • [cs.IT]Uplink Non-Orthogonal Multiple Access for UAV Communications
    Xidong Mu, Yuanwei Liu, Li Guo, Jiaru Lin
    http://arxiv.org/abs/1906.06523v1

    • [cs.LG]A Closer Look at Double Backpropagation
    Christian Etmann
    http://arxiv.org/abs/1906.06637v1

    • [cs.LG]A General Interpretation of Deep Learning by Affine Transform and Region Dividing without Mutual Interference
    Changcun Huang
    http://arxiv.org/abs/1906.06706v1

    • [cs.LG]A Provably Correct and Robust Algorithm for Convolutive Nonnegative Matrix Factorization
    Anthony Degleris, Nicolas Gillis
    http://arxiv.org/abs/1906.06899v1

    • [cs.LG]A Survey of Optimization Methods from a Machine Learning Perspective
    Shiliang Sun, Zehui Cao, Han Zhu, Jing Zhao
    http://arxiv.org/abs/1906.06821v1

    • [cs.LG]ASAC: Active Sensing using Actor-Critic models
    Jinsung Yoon, James Jordon, Mihaela van der Schaar
    http://arxiv.org/abs/1906.06796v1

    • [cs.LG]Active Generative Adversarial Network for Image Classification
    Quan Kong, Bin Tong, Martin Klinkigt, Yuki Watanabe, Naoto Akira, Tomokazu Murakami
    http://arxiv.org/abs/1906.07133v1

    • [cs.LG]Active Learning by Greedy Split and Label Exploration
    Alyssa Herbst, Bert Huang
    http://arxiv.org/abs/1906.07046v1

    • [cs.LG]Adversarial attacks on Copyright Detection Systems
    Parsa Saadatpanah, Ali Shafahi, Tom Goldstein
    http://arxiv.org/abs/1906.07153v1

    • [cs.LG]Asymptotic Risk of Bezier Simplex Fitting
    Akinori Tanaka, Akiyoshi Sannai, Ken Kobayashi, Naoki Hamada
    http://arxiv.org/abs/1906.06924v1

    • [cs.LG]Attributed Graph Clustering: A Deep Attentional Embedding Approach
    Chun Wang, Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Chengqi Zhang
    http://arxiv.org/abs/1906.06532v1

    • [cs.LG]Characterizing the Exact Behaviors of Temporal Difference Learning Algorithms Using Markov Jump Linear System Theory
    Bin Hu, Usman Ahmed Syed
    http://arxiv.org/abs/1906.06781v1

    • [cs.LG]CheckNet: Secure Inference on Untrusted Devices
    Marcus Comiter, Surat Teerapittayanon, H. T. Kung
    http://arxiv.org/abs/1906.07148v1

    • [cs.LG]Conditional Computation for Continual Learning
    Min Lin, Jie Fu, Yoshua Bengio
    http://arxiv.org/abs/1906.06635v1

    • [cs.LG]Dataset shift quantification for credit card fraud detection
    Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Sylvie Calabretto, Liyun He-Guelton, Frederic Oblé, Michael Granitzer
    http://arxiv.org/abs/1906.06977v1

    • [cs.LG]Dealing with the database variability problem in learning from medical data: an ensemble-based approach using convolutional neural networks and a case of study applied to automatic sleep scoring
    Diego Alvarez-Estevez, Isaac Fernández-Varela
    http://arxiv.org/abs/1906.06666v1

    • [cs.LG]Deep Learning of Preconditioners for Conjugate Gradient Solvers in Urban Water Related Problems
    Johannes Sappl, Laurent Seiler, Matthias Harders, Wolfgang Rauch
    http://arxiv.org/abs/1906.06925v1

    • [cs.LG]Deep Set Prediction Networks
    Yan Zhang, Jonathon Hare, Adam Prügel-Bennett
    http://arxiv.org/abs/1906.06565v1

    • [cs.LG]Exact and Consistent Interpretation of Piecewise Linear Models Hidden behind APIs: A Closed Form Solution
    Zicun Cong, Lingyang Chu, Lanjun Wang, Xia Hu, Jian Pei
    http://arxiv.org/abs/1906.06857v1

    • [cs.LG]Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias
    Stéphane d’Ascoli, Levent Sagun, Joan Bruna, Giulio Biroli
    http://arxiv.org/abs/1906.06766v1

    • [cs.LG]Fixing Gaussian Mixture VAEs for Interpretable Text Generation
    Wenxian Shi, Hao Zhou, Ning Miao, Shenjian Zhao, Lei Li
    http://arxiv.org/abs/1906.06719v1

    • [cs.LG]Generating Diverse and Informative Natural Language Fashion Feedback
    Gil Sadeh, Lior Fritz, Gabi Shalev, Eduard Oks
    http://arxiv.org/abs/1906.06619v1

    • [cs.LG]Global optimization via inverse distance weighting
    Alberto Bemporad
    http://arxiv.org/abs/1906.06498v1

    • [cs.LG]Hierarchical Soft Actor-Critic: Adversarial Exploration via Mutual Information Optimization
    Ari Azarafrooz, John Brock
    http://arxiv.org/abs/1906.07122v1

    • [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/1906.06440v1

    • [cs.LG]Improving Black-box Adversarial Attacks with a Transfer-based Prior
    Shuyu Cheng, Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu
    http://arxiv.org/abs/1906.06919v1

    • [cs.LG]Injecting Prior Knowledge for Transfer Learning into Reinforcement Learning Algorithms using Logic Tensor Networks
    Samy Badreddine, Michael Spranger
    http://arxiv.org/abs/1906.06576v1

    • [cs.LG]Is the Policy Gradient a Gradient?
    Chris Nota, Philip S. Thomas
    http://arxiv.org/abs/1906.07073v1

    • [cs.LG]Joint Visual-Textual Embedding for Multimodal Style Search
    Gil Sadeh, Lior Fritz, Gabi Shalev, Eduard Oks
    http://arxiv.org/abs/1906.06620v1

    • [cs.LG]LPaintB: Learning to Paint from Self-SupervisionLPaintB: Learning to Paint from Self-Supervision
    Biao Jia, Jonathan Brandt, Radomir Mech, Byungmoon Kim, Dinesh Manocha
    http://arxiv.org/abs/1906.06841v1

    • [cs.LG]Learning Interpretable Models Using an Oracle
    Abhishek Ghose, Balaraman Ravindran
    http://arxiv.org/abs/1906.06852v1

    • [cs.LG]Learning Restricted Boltzmann Machines with Arbitrary External Fields
    Surbhi Goel
    http://arxiv.org/abs/1906.06595v1

    • [cs.LG]Learning-Driven Exploration for Reinforcement Learning
    Muhammad Usama, Dong Eui Chang
    http://arxiv.org/abs/1906.06890v1

    • [cs.LG]LioNets: Local Interpretation of Neural Networks through Penultimate Layer Decoding
    Ioannis Mollas, Nikolaos Bassiliades, Grigorios Tsoumakas
    http://arxiv.org/abs/1906.06566v1

    • [cs.LG]MixUp as Directional Adversarial Training
    Guillaume P. Archambault, Yongyi Mao, Hongyu Guo, Richong Zhang
    http://arxiv.org/abs/1906.06875v1

    • [cs.LG]Model Compression by Entropy Penalized Reparameterization
    Deniz Oktay, Johannes Ballé, Saurabh Singh, Abhinav Shrivastava
    http://arxiv.org/abs/1906.06624v1

    • [cs.LG]MoËT: Interpretable and Verifiable Reinforcement Learning via Mixture of Expert Trees
    Marko Vasic, Andrija Petrovic, Kaiyuan Wang, Mladen Nikolic, Rishabh Singh, Sarfraz Khurshid
    http://arxiv.org/abs/1906.06717v1

    • [cs.LG]Multi-Adversarial Variational Autoencoder Networks
    Abdullah-Al-Zubaer Imran, Demetri Terzopoulos
    http://arxiv.org/abs/1906.06430v1

    • [cs.LG]Neural Theorem Provers Do Not Learn Rules Without Exploration
    Michiel de Jong, Fei Sha
    http://arxiv.org/abs/1906.06805v1

    • [cs.LG]Normalizing flows for novelty detection in industrial time series data
    Maximilian Schmidt, Marko Simic
    http://arxiv.org/abs/1906.06904v1

    • [cs.LG]One Epoch Is All You Need
    Aran Komatsuzaki
    http://arxiv.org/abs/1906.06669v1

    • [cs.LG]Personalized Apprenticeship Learning from Heterogeneous Decision-Makers
    Rohan Paleja, Andrew Silva, Matthew Gombolay
    http://arxiv.org/abs/1906.06397v1

    • [cs.LG]Reconciling Utility and Membership Privacy via Knowledge Distillation
    Virat Shejwalkar, Amir Houmansadr
    http://arxiv.org/abs/1906.06589v1

    • [cs.LG]Recovering the parameters underlying the Lorenz-96 chaotic dynamics
    Soukayna Mouatadid, Pierre Gentine, Wei Yu, Steve Easterbrook
    http://arxiv.org/abs/1906.06786v1

    • [cs.LG]Reinforcement Learning Driven Heuristic Optimization
    Qingpeng Cai, Will Hang, Azalia Mirhoseini, George Tucker, Jingtao Wang, Wei Wei
    http://arxiv.org/abs/1906.06639v1

    • [cs.LG]Robust Federated Learning in a Heterogeneous Environment
    Avishek Ghosh, Justin Hong, Dong Yin, Kannan Ramchandran
    http://arxiv.org/abs/1906.06629v1

    • [cs.LG]Robust or Private? Adversarial Training Makes Models More Vulnerable to Privacy Attacks
    Felipe A. Mejia, Paul Gamble, Zigfried Hampel-Arias, Michael Lomnitz, Nina Lopatina, Lucas Tindall, Maria Alejandra Barrios
    http://arxiv.org/abs/1906.06449v1

    • [cs.LG]Sample-Efficient Neural Architecture Search by Learning Action Space
    Linnan Wang, Saining Xie, Teng Li, Rodrigo Fonseca, Yuandong Tian
    http://arxiv.org/abs/1906.06832v1

    • [cs.LG]Scrubbing Sensitive PHI Data from Medical Records made Easy by SpaCy — A Scalable Model Implementation Comparisons
    Rashmi Jain, Dinah Samuel Anand, Vijayalakshmi Janakiraman
    http://arxiv.org/abs/1906.06968v1

    • [cs.LG]Solution of Two-Player Zero-Sum Game by Successive Relaxation
    Raghuram Bharadwaj Diddigi, Chandramouli Kamanchi, Shalabh Bhatnagar
    http://arxiv.org/abs/1906.06659v1

    • [cs.LG]Structured Pruning of Recurrent Neural Networks through Neuron Selection
    Liangjiang Wen, Xueyang Zhang, Haoli Bai, Zenglin Xu
    http://arxiv.org/abs/1906.06847v1

    • [cs.LG]The Attack Generator: A Systematic Approach Towards Constructing Adversarial Attacks
    Felix Assion, Peter Schlicht, Florens Greßner, Wiebke Günther, Fabian Hüger, Nico Schmidt, Umair Rasheed
    http://arxiv.org/abs/1906.07077v1

    • [cs.NE]Accelerating Neural ODEs with Spectral Elements
    Alessio Quaglino, Marco Gallieri, Jonathan Masci, Jan Koutník
    http://arxiv.org/abs/1906.07038v1

    • [cs.NE]Rapid online learning and robust recall in a neuromorphic olfactory circuit
    Nabil Imam, Thomas A. Cleland
    http://arxiv.org/abs/1906.07067v1

    • [cs.NI]Supporting Web Archiving via Web Packaging
    Sawood Alam, Michele C. Weigle, Michael L. Nelson, Martin Klein, Herbert Van de Sompel
    http://arxiv.org/abs/1906.07104v1

    • [cs.RO]A Fast and Stable Omnidirectional Walking Engine for the Nao Humanoid Robot
    Mohammadreza Kasaei, Nuno Lau, Artur Pereira
    http://arxiv.org/abs/1906.06932v1

    • [cs.RO]Combining Safe Interval Path Planning and Constrained Path Following Control: Preliminary Results
    Konstantin Yakovlev, Anton Andreychuk, Juliya Belinskaya, Dmitry Makarov
    http://arxiv.org/abs/1906.06911v1

    • [cs.RO]DeepTemporalSeg: Temporally Consistent Semantic Segmentation of 3D LiDAR Scans
    Ayush Dewan, Wolfram Burgard
    http://arxiv.org/abs/1906.06962v1

    • [cs.RO]Designing, 3D Printing of a Quadruped Robot and Choice of Materials for Fabrication
    Akash Maity, Koustav Roy, Dhrubajyoti Gupta
    http://arxiv.org/abs/1906.06502v1

    • [cs.RO]Embracing Contact: Pushing Multiple Objects with Robot’s Forearm
    Akansel Cosgun, Luke Ditria, Shayne D’Lima, Tom Drummond
    http://arxiv.org/abs/1906.06866v1

    • [cs.RO]Exploiting Physical Contacts for Robustness Improvement of a Dot-Painting Mission by a Micro Air Vehicle
    Thomas Chaffre, Kevin Tudal, Sylvain Bertrand, Lionel Prevost
    http://arxiv.org/abs/1906.06515v1

    • [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/1906.06789v1

    • [cs.RO]Reinforcement Learning with Non-uniform State Representations for Adaptive Search
    Sandeep Manjanna, Herke van Hoof, Gregory Dudek
    http://arxiv.org/abs/1906.06588v1

    • [cs.RO]Robotic Navigation using Entropy-Based Exploration
    Muhammad Usama, Dong Eui Chang
    http://arxiv.org/abs/1906.06969v1

    • [cs.RO]Simple Swarm Foraging Algorithm Based on Gradient Computation
    Simon O. Obute, Mehmet R. Dogar, Jordan H. Boyle
    http://arxiv.org/abs/1906.07030v1

    • [cs.RO]Trajectory Tracking for Quadrotors with Attitude Control on $\mathcal{S}^2 \times \mathcal{S}^1$
    Dave Kooijman, Angela P. Schoellig, Duarte J. Antunes
    http://arxiv.org/abs/1906.06926v1

    • [cs.RO]Understanding Natural Language Instructions for Fetching Daily Objects Using GAN-Based Multimodal Target-Source Classification
    Aly Magassouba, Komei Sugiura, Anh Trinh Quoc, Hisashi Kawai
    http://arxiv.org/abs/1906.06830v1

    • [cs.RO]Usability Squared: Principles for doing good systems research in robotics
    Soham Sankaran, Ross A. Knepper
    http://arxiv.org/abs/1906.06775v1

    • [cs.RO]ViTa-SLAM: A Bio-inspired Visuo-Tactile SLAM for Navigation while Interacting with Aliased Environments
    Oliver Struckmeier, Kshitij Tiwari, Mohammed Salman, Martin J. Pearson, Ville Kyrki
    http://arxiv.org/abs/1906.06422v1

    • [cs.SD]Modeling Consonance and its Relationships with Temperament, Harmony, and Electronic Amplification
    Luciano da Fontoura Costa
    http://arxiv.org/abs/1906.06559v1

    • [cs.SD]Modeling Music Modality with a Key-Class Invariant Pitch Chroma CNN
    Anders Elowsson, Anders Friberg
    http://arxiv.org/abs/1906.07145v1

    • [cs.SD]Multi-scale Embedded CNN for Music Tagging (MsE-CNN)
    Nima Hamidi, Mohsen Vahidzadeh, Stephen Baek
    http://arxiv.org/abs/1906.06746v1

    • [cs.SE]Machine Learning Software Engineering in Practice: An Industrial Case Study
    Md Saidur Rahman, Emilio Rivera, Foutse Khomh, Yann-Gaël Guéhéneuc, Bernd Lehnert
    http://arxiv.org/abs/1906.07154v1

    • [cs.SI]Homogeneous Network Embedding for Massive Graphs via Personalized PageRank
    Renchi Yang, Jieming Shi, Xiaokui Xiao, Sourav S. Bhowmick, Yin Yang
    http://arxiv.org/abs/1906.06826v1

    • [cs.SI]Interactive health communication and the construction of the identity of the person with low vision in social media
    Gustavo Caran, Ronaldo Araujo, Crispulo Travieso-Rodriguez
    http://arxiv.org/abs/1906.06545v1

    • [cs.SI]Linear-time Hierarchical Community Detection
    Ryan A. Rossi, Nesreen K. Ahmed, Eunyee Koh, Sungchul Kim
    http://arxiv.org/abs/1906.06432v1

    • [cs.SI]Media Environment, Dual Process and Polarization: A Computational Approach
    In-Ho Yi
    http://arxiv.org/abs/1906.06531v1

    • [cs.SI]Supracentrality Analysis of Temporal Networks with Directed Interlayer Coupling
    Dane Taylor, Mason A. Porter, Peter J. Mucha
    http://arxiv.org/abs/1906.06366v1

    • [econ.EM]Posterior Average Effects
    Stéphane Bonhomme, Martin Weidner
    http://arxiv.org/abs/1906.06360v1

    • [eess.IV]4D X-Ray CT Reconstruction using Multi-Slice Fusion
    Soumendu Majee, Thilo Balke, Craig A. J. Kemp, Gregery T. Buzzard, Charles A. Bouman
    http://arxiv.org/abs/1906.06601v1

    • [eess.IV]A Fusion Adversarial Network for Underwater Image Enhancement
    Jingjing Li, Hanyu Li
    http://arxiv.org/abs/1906.06819v1

    • [eess.IV]Differentiated Backprojection Domain Deep Learning for Conebeam Artifact Removal
    Yoseob Han, Junyoung Kim, Jong Chul Ye
    http://arxiv.org/abs/1906.06854v1

    • [eess.IV]Particle Swarm Optimization for Great Enhancement in Semi-Supervised Retinal Vessel Segmentation with Generative Adversarial Networks
    Qiang Huo
    http://arxiv.org/abs/1906.07084v1

    • [eess.IV]Single Image Super-resolution via Dense Blended Attention Generative Adversarial Network for Clinical Diagnosis
    Kewen Liu, Yuan Ma, Hongxia Xiong, Zejun Yan, Zhijun Zhou, Chaoyang Liu, Panpan Fang, Xiaojun Li, Yalei Chen
    http://arxiv.org/abs/1906.06575v1

    • [eess.IV]Speeding up VP9 Intra Encoder with Hierarchical Deep Learning Based Partition Prediction
    Somdyuti Paul, Andrey Norkin, Alan C. Bovik
    http://arxiv.org/abs/1906.06476v1

    • [eess.SP]Beam Entropy of 5G Cellular Millimetre Wave Channels
    Krishan Kumar Tiwari, Eckhard Grass, John S. Thompson, Rolf Kraemer
    http://arxiv.org/abs/1906.07012v1

    • [eess.SP]Deep Recurrent Adversarial Learning for Privacy-Preserving Smart Meter Data Release
    Mohammadhadi Shateri, Francisco Messina, Pablo Piantanida, Fabrice Labeau
    http://arxiv.org/abs/1906.06427v1

    • [math.OC]An efficient Lagrangian-based heuristic to solve a multi-objective sustainable supply chain problem
    Camila P. S. Tautenhain, Ana Paula Barbosa-Povoa, Bruna Mota, Mariá C. V. Nascimento
    http://arxiv.org/abs/1906.06375v1

    • [math.OC]Productivity equation and the m distributions of information processing in workflows
    Charles Roberto Telles
    http://arxiv.org/abs/1906.06997v1

    • [math.ST]Community Detection Based on the $L_\infty$ convergence of eigenvectors in DCBM
    Yan Liu, Zhiqiang Hou, Zhigang Yao, Zhidong Bai, Jiang Hu, Shurong Zheng
    http://arxiv.org/abs/1906.06713v1

    • [math.ST]Designing Test Information and Test Information in Design
    David E. Jones, Xiao-Li Meng
    http://arxiv.org/abs/1906.06749v1

    • [math.ST]Minimax Density Estimation on Sobolev Spaces With Dominating Mixed Smoothness
    Galatia Cleanthous, Athanasios G. Georgiadis, Emilio Porcu
    http://arxiv.org/abs/1906.06835v1

    • [math.ST]On the Locally Lipschitz Robustness of Bayesian Inverse Problems
    Björn Sprungk
    http://arxiv.org/abs/1906.07120v1

    • [physics.data-an]Detecting new signals under background mismodelling
    Sara Algeri
    http://arxiv.org/abs/1906.06615v1

    • [q-bio.GN]Nested partitions from hierarchical clustering statistical validation
    Christian Bongiorno, Salvatore Miccichè, Rosario N. Mantegna
    http://arxiv.org/abs/1906.06908v1

    • [stat.AP]Bayesian Finite Population Modeling for Spatial Process Settings
    Alec M. Chan-Golston, Sudipto Banerjee, Mark S. Handcock
    http://arxiv.org/abs/1906.06714v1

    • [stat.AP]Bayesian spatial extreme value analysis of maximum temperatures in County Dublin, Ireland
    John O’Sullivan, Conor Sweeney, Andrew C. Parnell
    http://arxiv.org/abs/1906.06744v1

    • [stat.AP]Identifying and characterizing extrapolation in multivariateresponse data
    Meridith L Bartley, Ephraim M Hanks, Erin M Schliep, Patricia A Soranno, Tyler Wagner
    http://arxiv.org/abs/1906.07036v1

    • [stat.AP]Linear regression with stationary errors : the R package slm
    Emmanuel Caron, Jérôme Dedecker, Michel Bertrand
    http://arxiv.org/abs/1906.06583v1

    • [stat.AP]Parametric and non-parametric estimation of extreme earthquake event: the joint tail inference for mainshocks and aftershocks
    Juan-Juan Cai, Phyllis Wan, Gamze Ozel
    http://arxiv.org/abs/1906.06882v1

    • [stat.CO]A tunable multiresolution smoother for scattered data with application to particle filtering
    Gregor A. Robinson, Ian G. Grooms
    http://arxiv.org/abs/1906.06722v1

    • [stat.CO]lpdensity: Local Polynomial Density Estimation and Inference
    Matias D. Cattaneo, Michael Jansson, Xinwei Ma
    http://arxiv.org/abs/1906.06529v1

    • [stat.ME]Adaptive Variable Selection for Sequential Prediction in Multivariate Dynamic Models
    Isaac Lavine, Michael Lindon, Mike West
    http://arxiv.org/abs/1906.06580v1

    • [stat.ME]An Optimal Test for the Additive Model with Discrete or Categorical Predictors
    Abhijit Mandal
    http://arxiv.org/abs/1906.06828v1

    • [stat.ME]Depth-based Weighted Jackknife Empirical Likelihood for Non-smooth U-structure Equations
    Yongli Sang, Xin Dang, Yichuan Zhao
    http://arxiv.org/abs/1906.06742v1

    • [stat.ME]From Incomplete, Dynamic Data to Bayesian Networks
    Marco Scutari
    http://arxiv.org/abs/1906.06513v1

    • [stat.ME]Hierarchical Total Variations and Doubly Penalized ANOVA Modeling for Multivariate Nonparametric Regression
    Ting Yang, Zhiqiang Tan
    http://arxiv.org/abs/1906.06729v1

    • [stat.ME]Linear Aggregation in Tree-based Estimators
    Sören R. Künzel, Theo F. Saarinen, Edward W. Liu, Jasjeet S. Sekhon
    http://arxiv.org/abs/1906.06463v1

    • [stat.ME]Non parametric estimation of Joint entropy and Shannon mutual information, Asymptotic limits: Application to statistic tests
    Amadou Diadie Ba, Gane Samb Lo
    http://arxiv.org/abs/1906.06484v1

    • [stat.ME]Probabilistic Diffusion MRI Fiber Tracking Using a Directed Acyclic Graph Auto-Regressive Model of Positive Definite Matrices
    Zhou Lan, Brian J Reich
    http://arxiv.org/abs/1906.06459v1

    • [stat.ME]Sample Size Calculations for SMARTs
    Eric J. Rose, Eric B. Laber, Marie Davidian, Anastasios A. Tsiatis, Ying-Qi Zhao, Michael R. Kosorok
    http://arxiv.org/abs/1906.06646v1

    • [stat.ML]A Bayesian Solution to the M-Bias Problem
    David Rohde
    http://arxiv.org/abs/1906.07136v1

    • [stat.ML]Automatic Relevance Determination Bayesian Neural Networks for Credit Card Default Modelling
    Rendani Mbuvha, Illyes Boulkaibet, Tshilidzi Marwala
    http://arxiv.org/abs/1906.06382v1

    • [stat.ML]Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities
    Wei Qian, Yuqian Zhang, Yudong Chen
    http://arxiv.org/abs/1906.06776v1

    • [stat.ML]Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Accuracy
    Alex Lamb, Vikas Verma, Juho Kannala, Yoshua Bengio
    http://arxiv.org/abs/1906.06784v1

    • [stat.ML]Metric on random dynamical systems with vector-valued reproducing kernel Hilbert spaces
    Isao Ishikawa, Akinori Tanaka, Masahiro Ikeda, Yoshinobu Kawahara
    http://arxiv.org/abs/1906.06957v1

    • [stat.ML]Replacing the do-calculus with Bayes rule
    Finnian Lattimore, David Rohde
    http://arxiv.org/abs/1906.07125v1

    • [stat.ML]Sampler for Composition Ratio by Markov Chain Monte Carlo
    Yachiko Obara, Tetsuro Morimura, Hiroki Yanagisawa
    http://arxiv.org/abs/1906.06663v1

    • [stat.ML]Smooth function approximation by deep neural networks with general activation functions
    Ilsang Ohn, Yongdai Kim
    http://arxiv.org/abs/1906.06903v1

    • [stat.ML]Stacked Capsule Autoencoders
    Adam R. Kosiorek, Sara Sabour, Yee Whye Teh, Geoffrey E. Hinton
    http://arxiv.org/abs/1906.06818v1

    • [stat.ML]The Price of Local Fairness in Multistage Selection
    Vitalii Emelianov, George Arvanitakis, Nicolas Gast, Krishna Gummadi, Patrick Loiseau
    http://arxiv.org/abs/1906.06613v1

    • [stat.ML]The True Sample Complexity of Identifying Good Arms
    Julian Katz-Samuels, Kevin Jamieson
    http://arxiv.org/abs/1906.06594v1