astro-ph.SR - 太阳和天体物理学恒星

    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.DS - 数据结构与算法 cs.ET - 新兴技术 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.LO - 计算逻辑 cs.MA - 多代理系统 cs.NA - 数值分析 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.OS - 操作系统 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 cs.SY - 系统与控制 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 hep-ph - 高能物理现象学 math.AT - 代数拓扑 math.DG - 微分几何 math.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 physics.comp-ph - 计算物理学 physics.data-an - 数据分析、 统计和概率 q-bio.NC - 神经元与认知 q-fin.ST - 统计金融学 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [astro-ph.SR]A Curated Image Parameter Dataset from Solar Dynamics Observatory Mission
    • [cs.AI]Automated Video Game Testing Using Synthetic and Human-Like Agents
    • [cs.AI]Blackbox meets blackbox: Representational Similarity and Stability Analysis of Neural Language Models and Brains
    • [cs.AI]Does It Make Sense? And Why? A Pilot Study for Sense Making and Explanation
    • [cs.AI]Hierarchical Decision Making by Generating and Following Natural Language Instructions
    • [cs.AI]Kandinsky Patterns
    • [cs.AI]Pre-training of Graph Augmented Transformers for Medication Recommendation
    • [cs.AI]Smoothing Structured Decomposable Circuits
    • [cs.CL]A Cross-Sentence Latent Variable Model for Semi-Supervised Text Sequence Matching
    • [cs.CL]A Review of Language and Speech Features for Cognitive-Linguistic Assessment
    • [cs.CL]A Semi-Supervised Approach for Low-Resourced Text Generation
    • [cs.CL]A Study of Feature Extraction techniques for Sentiment Analysis
    • [cs.CL]A Survey of Natural Language Generation Techniques with a Focus on Dialogue Systems - Past, Present and Future Directions
    • [cs.CL]A computational linguistic study of personal recovery in bipolar disorder
    • [cs.CL]Are Girls Neko or Shōjo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization
    • [cs.CL]Are You Looking? Grounding to Multiple Modalities in Vision-and-Language Navigation
    • [cs.CL]Are we there yet? Encoder-decoder neural networks as cognitive models of English past tense inflection
    • [cs.CL]Assessing the Ability of Self-Attention Networks to Learn Word Order
    • [cs.CL]Back Attention Knowledge Transfer for Low-resource Named Entity Recognition
    • [cs.CL]Better Character Language Modeling Through Morphology
    • [cs.CL]Boosting Entity Linking Performance by Leveraging Unlabeled Documents
    • [cs.CL]Budgeted Policy Learning for Task-Oriented Dialogue Systems
    • [cs.CL]ChID: A Large-scale Chinese IDiom Dataset for Cloze Test
    • [cs.CL]Coherent Comment Generation for Chinese Articles with a Graph-to-Sequence Model
    • [cs.CL]Controllable Paraphrase Generation with a Syntactic Exemplar
    • [cs.CL]Curate and Generate: A Corpus and Method for Joint Control of Semantics and Style in Neural NLG
    • [cs.CL]Deep Unknown Intent Detection with Margin Loss
    • [cs.CL]Distantly Supervised Named Entity Recognition using Positive-Unlabeled Learning
    • [cs.CL]Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study
    • [cs.CL]Domain Adaptation of Neural Machine Translation by Lexicon Induction
    • [cs.CL]Domain Adaptive Inference for Neural Machine Translation
    • [cs.CL]Dynamically Composing Domain-Data Selection with Clean-Data Selection by “Co-Curricular Learning” for Neural Machine Translation
    • [cs.CL]Emotion-Cause Pair Extraction: A New Task to Emotion Analysis in Texts
    • [cs.CL]Evaluating Discourse in Structured Text Representations
    • [cs.CL]Evaluating Gender Bias in Machine Translation
    • [cs.CL]Exploiting Sentential Context for Neural Machine Translation
    • [cs.CL]Exploring Phoneme-Level Speech Representations for End-to-End Speech Translation
    • [cs.CL]Finding Syntactic Representations in Neural Stacks
    • [cs.CL]Fluent Translations from Disfluent Speech in End-to-End Speech Translation
    • [cs.CL]From Independent Prediction to Re-ordered Prediction: Integrating Relative Position and Global Label Information to Emotion Cause Identification
    • [cs.CL]From Speech Chain to Multimodal Chain: Leveraging Cross-modal Data Augmentation for Semi-supervised Learning
    • [cs.CL]From Words to Sentences: A Progressive Learning Approach for Zero-resource Machine Translation with Visual Pivots
    • [cs.CL]Gender-preserving Debiasing for Pre-trained Word Embeddings
    • [cs.CL]Gendered Ambiguous Pronouns Shared Task: Boosting Model Confidence by Evidence Pooling
    • [cs.CL]Global Textual Relation Embedding for Relational Understanding
    • [cs.CL]Handling Divergent Reference Texts when Evaluating Table-to-Text Generation
    • [cs.CL]HighRES: Highlight-based Reference-less Evaluation of Summarization
    • [cs.CL]How Large Are Lions? Inducing Distributions over Quantitative Attributes
    • [cs.CL]How multilingual is Multilingual BERT?
    • [cs.CL]Improved Zero-shot Neural Machine Translation via Ignoring Spurious Correlations
    • [cs.CL]Improving Long Distance Slot Carryover in Spoken Dialogue Systems
    • [cs.CL]Joint Effects of Context and User History for Predicting Online Conversation Re-entries
    • [cs.CL]Jointly Learning Semantic Parser and Natural Language Generator via Dual Information Maximization
    • [cs.CL]KERMIT: Generative Insertion-Based Modeling for Sequences
    • [cs.CL]Know More about Each Other: Evolving Dialogue Strategy via Compound Assessment
    • [cs.CL]Latent Retrieval for Weakly Supervised Open Domain Question Answering
    • [cs.CL]Lattice-Based Transformer Encoder for Neural Machine Translation
    • [cs.CL]Learning to Explain: Answering Why-Questions via Rephrasing
    • [cs.CL]Massive Styles Transfer with Limited Labeled Data
    • [cs.CL]Multi-Task Semantic Dependency Parsing with Policy Gradient for Learning Easy-First Strategies
    • [cs.CL]Multi-task Pairwise Neural Ranking for Hashtag Segmentation
    • [cs.CL]Multimodal Transformer for Unaligned Multimodal Language Sequences
    • [cs.CL]NNE: A Dataset for Nested Named Entity Recognition in English Newswire
    • [cs.CL]Optimal coding and the origins of Zipfian laws
    • [cs.CL]Phase-based Minimalist Parsing and complexity in non-local dependencies
    • [cs.CL]Pitfalls in the Evaluation of Sentence Embeddings
    • [cs.CL]Plain English Summarization of Contracts
    • [cs.CL]Pretraining Methods for Dialog Context Representation Learning
    • [cs.CL]Progressive Self-Supervised Attention Learning for Aspect-Level Sentiment Analysis
    • [cs.CL]Promotion of Answer Value Measurement with Domain Effects in Community Question Answering Systems
    • [cs.CL]Question Answering as an Automatic Evaluation Metric for News Article Summarization
    • [cs.CL]RTHN: A RNN-Transformer Hierarchical Network for Emotion Cause Extraction
    • [cs.CL]Recognising Agreement and Disagreement between Stances with Reason Comparing Networks
    • [cs.CL]Relation Embedding with Dihedral Group in Knowledge Graph
    • [cs.CL]Relational Word Embeddings
    • [cs.CL]Resolving Gendered Ambiguous Pronouns with BERT
    • [cs.CL]Robust Sequence-to-Sequence Acoustic Modeling with Stepwise Monotonic Attention for Neural TTS
    • [cs.CL]Self-Attentional Models for Lattice Inputs
    • [cs.CL]Semantically Constrained Multilayer Annotation: The Case of Coreference
    • [cs.CL]Sentiment Tagging with Partial Labels using Modular Architectures
    • [cs.CL]Sequence Tagging with Contextual and Non-Contextual Subword Representations: A Multilingual Evaluation
    • [cs.CL]Sequential Neural Networks as Automata
    • [cs.CL]ShEMO — A Large-Scale Validated Database for Persian Speech Emotion Detection
    • [cs.CL]SherLIiC: A Typed Event-Focused Lexical Inference Benchmark for Evaluating Natural Language Inference
    • [cs.CL]Simultaneous Translation with Flexible Policy via Restricted Imitation Learning
    • [cs.CL]System Demo for Transfer Learning across Vision and Text using Domain Specific CNN Accelerator for On-Device NLP Applications
    • [cs.CL]TalkSumm: A Dataset and Scalable Annotation Method for Scientific Paper Summarization Based on Conference Talks
    • [cs.CL]Task-Guided Pair Embedding in Heterogeneous Network
    • [cs.CL]The PhotoBook Dataset: Building Common Ground through Visually-Grounded Dialogue
    • [cs.CL]Toward Grammatical Error Detection from Sentence Labels: Zero-shot Sequence Labeling with CNNs and Contextualized Embeddings
    • [cs.CL]Tracing Antisemitic Language Through Diachronic Embedding Projections: France 1789-1914
    • [cs.CL]Training Neural Machine Translation To Apply Terminology Constraints
    • [cs.CL]Training Neural Response Selection for Task-Oriented Dialogue Systems
    • [cs.CL]Transcoding compositionally: using attention to find more generalizable solutions
    • [cs.CL]Transferable Neural Projection Representations
    • [cs.CL]Transforming Complex Sentences into a Semantic Hierarchy
    • [cs.CL]Unsupervised Bilingual Lexicon Induction from Mono-lingual Multimodal Data
    • [cs.CR]DAWN: Dynamic Adversarial Watermarking of Neural Networks
    • [cs.CR]Encryption Scheme Based on Expanded Reed-Solomon Codes
    • [cs.CR]Generative Adversarial Networks for Distributed Intrusion Detection in the Internet of Things
    • [cs.CR]Human-Usable Password Schemas: Beyond Information-Theoretic Security
    • [cs.CR]New non-linearity parameters of Boolean functions
    • [cs.CR]Privacy-preserving Crowd-guided AI Decision-making in Ethical Dilemmas
    • [cs.CR]Towards Fair and Decentralized Privacy-Preserving Deep Learning with Blockchain
    • [cs.CV]3D Appearance Super-Resolution with Deep Learning
    • [cs.CV]A Closed-form Solution to Universal Style Transfer
    • [cs.CV]A Hybrid RNN-HMM Approach for Weakly Supervised Temporal Action Segmentation
    • [cs.CV]Active Object Manipulation Facilitates Visual Object Learning: An Egocentric Vision Study
    • [cs.CV]Adversarial Examples for Edge Detection: They Exist, and They Transfer
    • [cs.CV]An Adaptive Training-less System for Anomaly Detection in Crowd Scenes
    • [cs.CV]Automated Steel Bar Counting and Center Localization with Convolutional Neural Networks
    • [cs.CV]Automatic Health Problem Detection from Gait Videos Using Deep Neural Networks
    • [cs.CV]Color Constancy Convolutional Autoencoder
    • [cs.CV]Comparing two- and three-view Computer Vision
    • [cs.CV]Computing Valid p-values for Image Segmentation by Selective Inference
    • [cs.CV]Content Adaptive Optimization for Neural Image Compression
    • [cs.CV]Cross-Domain Cascaded Deep Feature Translation
    • [cs.CV]Data Augmentation for Object Detection via Progressive and Selective Instance-Switching
    • [cs.CV]Deep Face Recognition Model Compression via Knowledge Transfer and Distillation
    • [cs.CV]Deeply-supervised Knowledge Synergy
    • [cs.CV]Depth-Preserving Real-Time Arbitrary Style Transfer
    • [cs.CV]Disentangling neural mechanisms for perceptual grouping
    • [cs.CV]Dominant Set Clustering and Pooling for Multi-View 3D Object Recognition
    • [cs.CV]DualDis: Dual-Branch Disentangling with Adversarial Learning
    • [cs.CV]Dynamic Neural Network Decoupling
    • [cs.CV]End-to-End Learning of Geometric Deformations of Feature Maps for Virtual Try-On
    • [cs.CV]Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study
    • [cs.CV]Example-Guided Style Consistent Image Synthesis from Semantic Labeling
    • [cs.CV]Exploiting Offset-guided Network for Pose Estimation and Tracking
    • [cs.CV]Face Parsing with RoI Tanh-Warping
    • [cs.CV]Fashion Editing with Multi-scale Attention Normalization
    • [cs.CV]GazeCorrection:Self-Guided Eye Manipulation in the wild using Self-Supervised Generative Adversarial Networks
    • [cs.CV]Generating Question Relevant Captions to Aid Visual Question Answering
    • [cs.CV]Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network
    • [cs.CV]How Much Does Audio Matter to Recognize Egocentric Object Interactions?
    • [cs.CV]Incremental Few-Shot Learning for Pedestrian Attribute Recognition
    • [cs.CV]Iterative Path Reconstruction for Large-Scale Inertial Navigation on Smartphones
    • [cs.CV]KarNet: An Efficient Boolean Function Simplifier
    • [cs.CV]Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds
    • [cs.CV]Learning Rotation Adaptive Correlation Filters in Robust Visual Object Tracking
    • [cs.CV]Learning to Generate Grounded Image Captions without Localization Supervision
    • [cs.CV]Learning to Self-Train for Semi-Supervised Few-Shot Classification
    • [cs.CV]Localization in Aerial Imagery with Grid Maps using LocGAN
    • [cs.CV]Masked Non-Autoregressive Image Captioning
    • [cs.CV]Mining YouTube - A dataset for learning fine-grained action concepts from webly supervised video data
    • [cs.CV]Natural Vocabulary Emerges from Free-Form Annotations
    • [cs.CV]Panoptic Edge Detection
    • [cs.CV]Parametric Shape Modeling and Skeleton Extraction with Radial Basis Functions using Similarity Domains Network
    • [cs.CV]Perceptual Embedding Consistency for Seamless Reconstruction of Tilewise Style Transfer
    • [cs.CV]Photo-Geometric Autoencoding to Learn 3D Objects from Unlabelled Images
    • [cs.CV]RF-Net: An End-to-End Image Matching Network based on Receptive Field
    • [cs.CV]RGB and LiDAR fusion based 3D Semantic Segmentation for Autonomous Driving
    • [cs.CV]Random Path Selection for Incremental Learning
    • [cs.CV]Reconstruct and Represent Video Contents for Captioning via Reinforcement Learning
    • [cs.CV]Relational Reasoning using Prior Knowledge for Visual Captioning
    • [cs.CV]Resolving Overlapping Convex Objects in Silhouette Images by Concavity Analysis and Gaussian Process
    • [cs.CV]Rethinking Loss Design for Large-scale 3D Shape Retrieval
    • [cs.CV]Robust copy-move forgery detection by false alarms control
    • [cs.CV]Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations
    • [cs.CV]Selective Style Transfer for Text
    • [cs.CV]Semi- and Weakly-supervised Human Pose Estimation
    • [cs.CV]Separate from Observation: Unsupervised Single Image Layer Separation
    • [cs.CV]State-aware Re-identification Feature for Multi-target Multi-camera Tracking
    • [cs.CV]Style Transfer With Adaptation to the Central Objects of the Scene
    • [cs.CV]Text-based Editing of Talking-head Video
    • [cs.CV]The iMet Collection 2019 Challenge Dataset
    • [cs.CV]Towards better Validity: Dispersion based Clustering for Unsupervised Person Re-identification
    • [cs.CV]Transfer Learning with intelligent training data selection for prediction of Alzheimer’s Disease
    • [cs.CV]Triangulation Learning Network: from Monocular to Stereo 3D Object Detection
    • [cs.CV]Visual Diagnosis of Dermatological Disorders: Human and Machine Performance
    • [cs.CV]Visual Tree Convolutional Neural Network in Image Classification
    • [cs.CV]Zero-Shot Semantic Segmentation
    • [cs.CV]cGANs with Conditional Convolution Layer
    • [cs.CY]Apprentissage de la pensée informatique : de la formation des enseignant$\cdot$e$\cdot$s à la formation de tou$\cdot$te$\cdot$s les citoyen$\cdot$ne$\cdot$s
    • [cs.CY]Grade prediction with course and student specific models
    • [cs.CY]Peut-on former les enseignant$\cdot$e$\cdot$s en un rien de temps ?
    • [cs.DB]Efficient Algorithms for Densest Subgraph Discovery
    • [cs.DB]Motivo: fast motif counting via succinct color coding and adaptive sampling
    • [cs.DC]A Hybrid Cache Architecture for Meeting Per-Tenant Performance Goals in a Private Cloud
    • [cs.DC]A Technique for Finding Optimal Program Launch Parameters Targeting Manycore Accelerators
    • [cs.DC]Assessing Performance Implications of Deep Copy Operations via Microbenchmarking
    • [cs.DC]Mutable Locks: Combining the Best of Spin and Sleep Locks
    • [cs.DC]Optimal Register Construction in M&M Systems
    • [cs.DC]Patterns for Blockchain Migration
    • [cs.DC]Probabilistic Top-k Dominating Query Monitoring over Multiple Uncertain IoT Data Streams in Edge Computing Environments
    • [cs.DC]Proximity Neighbor Selection in Blockchain Networks
    • [cs.DC]Reconfigurable Atomic Transaction Commit (Extended Version)
    • [cs.DS]A Direct $\tilde{O}(1/ε)$ Iteration Parallel Algorithm for Optimal Transport
    • [cs.DS]Cores and Other Dense Structures in Complex Networks
    • [cs.DS]On the Use of Randomness in Local Distributed Graph Algorithms
    • [cs.ET]In-memory hyperdimensional computing
    • [cs.GR]3D Magic Mirror: Automatic Video to 3D Caricature Translation
    • [cs.HC]An Extensive Review of Computational Dance Automation Techniques and Applications
    • [cs.IR]Contextually Propagated Term Weights for Document Representation
    • [cs.IR]Federated Hierarchical Hybrid Networks for Clickbait Detection
    • [cs.IR]Incorporating System-Level Objectives into Recommender Systems
    • [cs.IR]Mining Data from the Congressional Record
    • [cs.IR]Personalized Multimedia Item and Key Frame Recommendation
    • [cs.IR]Sequential Scenario-Specific Meta Learner for Online Recommendation
    • [cs.IR]Technology Knowledge Graph Based on Patent Data
    • [cs.IR]Unsupervised Neural Generative Semantic Hashing
    • [cs.IR]User Profile Feature-Based Approach to Address the Cold Start Problem in Collaborative Filtering for Personalized Movie Recommendation
    • [cs.IT]Closed-Form Analysis of Non-Linear Age-of-Information in Status Updates with an Energy Harvesting Transmitter
    • [cs.IT]Cooperative Downlink Interference Transmission and Cancellation for Cellular-Connected UAV: A Divide-and-Conquer Approach
    • [cs.IT]Harvest-or-Transmit Policy for Cognitive Radio Networks: A Learning Theoretic Approach
    • [cs.IT]Multi-dimensional Spectral Super-Resolution with Prior Knowledge via Frequency-Selective Vandermonde Decomposition and ADMM
    • [cs.IT]Performance Evaluation for the Co-existence of eMBB and URLLC Networks: Synchronized versus Unsynchronized TDD
    • [cs.IT]Probabilistic Existence Results for Parent-Identifying Schemes
    • [cs.IT]The Classical Capacity of a Quantum Erasure Queue-Channel
    • [cs.IT]Transmit Power Policy and Ergodic Multicast Rate Analysis of Cognitive Radio Networks in Generalized Fading
    • [cs.IT]Two Classes of New MDS Self-dual Codes over Finite Fields
    • [cs.LG]A Case for Backward Compatibility for Human-AI Teams
    • [cs.LG]A Fast-Optimal Guaranteed Algorithm For Learning Sub-Interval Relationships in Time Series
    • [cs.LG]A Language-Agnostic Model for Semantic Source Code Labeling
    • [cs.LG]A Novel Hyperparameter-free Approach to Decision Tree Construction that Avoids Overfitting by Design
    • [cs.LG]A Perspective on Objects and Systematic Generalization in Model-Based RL
    • [cs.LG]A Strong and Robust Baseline for Text-Image Matching
    • [cs.LG]A necessary and sufficient stability notion for adaptive generalization
    • [cs.LG]Achieving Fairness in Determining Medicaid Eligibility through Fairgroup Construction
    • [cs.LG]Achieving Generalizable Robustness of Deep Neural Networks by Stability Training
    • [cs.LG]Active Learning for Binary Classification with Abstention
    • [cs.LG]Adaptive Online Learning for Gradient-Based Optimizers
    • [cs.LG]Adversarial Exploitation of Policy Imitation
    • [cs.LG]Adversarial Risk Bounds for Neural Networks through Sparsity based Compression
    • [cs.LG]Adversarial Training Generalizes Data-dependent Spectral Norm Regularization
    • [cs.LG]Adversarially Robust Generalization Just Requires More Unlabeled Data
    • [cs.LG]An Adaptable Framework for Deep Adversarial Label Learning from Weak Supervision
    • [cs.LG]An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem
    • [cs.LG]An Empirical Study on Hyperparameters and their Interdependence for RL Generalization
    • [cs.LG]An interpretable machine learning framework for modelling human decision behavior
    • [cs.LG]Analysis and Improvement of Adversarial Training in DQN Agents With Adversarially-Guided Exploration (AGE)
    • [cs.LG]Approximation capability of neural networks on spaces of probability measures and tree-structured domains
    • [cs.LG]Architecture Selection via the Trade-off Between Accuracy and Robustness
    • [cs.LG]Attributed Graph Clustering via Adaptive Graph Convolution
    • [cs.LG]Autonomous Reinforcement Learning of Multiple Interrelated Tasks
    • [cs.LG]Big-Data Clustering: K-Means or K-Indicators?
    • [cs.LG]Biomedical Named Entity Recognition via Reference-Set Augmented Bootstrapping
    • [cs.LG]Blow: a single-scale hyperconditioned flow for non-parallel raw-audio voice conversion
    • [cs.LG]Breaking Inter-Layer Co-Adaptation by Classifier Anonymization
    • [cs.LG]C2P2: A Collective Cryptocurrency Up/Down Price Prediction Engine
    • [cs.LG]Characterizing and Forecasting User Engagement with In-app Action Graph: A Case Study of Snapchat
    • [cs.LG]Classification of Crop Tolerance to Heat and Drought: A Deep Convolutional Neural Networks Approach
    • [cs.LG]Clustering by Orthogonal NMF Model and Non-Convex Penalty Optimization
    • [cs.LG]Conditional Generative Models are not Robust
    • [cs.LG]Continual Learning of New Sound Classes using Generative Replay
    • [cs.LG]Continual learning with hypernetworks
    • [cs.LG]Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification
    • [cs.LG]Correctness Verification of Neural Networks
    • [cs.LG]Coupled VAE: Improved Accuracy and Robustness of a Variational Autoencoder
    • [cs.LG]DANE: Domain Adaptive Network Embedding
    • [cs.LG]Data Sampling for Graph Based Unsupervised Learning: Convex and Greedy Optimization
    • [cs.LG]Data-driven Estimation of Sinusoid Frequencies
    • [cs.LG]Deep Reasoning Networks: Thinking Fast and Slow
    • [cs.LG]DiffQue: Estimating Relative Difficulty of Questions in Community Question Answering Services
    • [cs.LG]Dimensionality compression and expansion in Deep Neural Networks
    • [cs.LG]Discovering Neural Wirings
    • [cs.LG]Discriminative adversarial networks for positive-unlabeled learning
    • [cs.LG]Disparate Vulnerability: on the Unfairness of Privacy Attacks Against Machine Learning
    • [cs.LG]Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards
    • [cs.LG]Do place cells dream of conditional probabilities? Learning Neural Nyström representations
    • [cs.LG]Ease.ml/meter: Quantitative Overfitting Management for Human-in-the-loop ML Application Development
    • [cs.LG]Embedded hyper-parameter tuning by Simulated Annealing
    • [cs.LG]Encoder-Powered Generative Adversarial Networks
    • [cs.LG]Encoding Invariances in Deep Generative Models
    • [cs.LG]Enhancing Transformation-based Defenses using a Distribution Classifier
    • [cs.LG]Episodic Memory in Lifelong Language Learning
    • [cs.LG]Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision
    • [cs.LG]Exact Combinatorial Optimization with Graph Convolutional Neural Networks
    • [cs.LG]Exact inference in structured prediction
    • [cs.LG]Factor Graph Neural Network
    • [cs.LG]Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models
    • [cs.LG]Feature-Based Q-Learning for Two-Player Stochastic Games
    • [cs.LG]Gated recurrent units viewed through the lens of continuous time dynamical systems
    • [cs.LG]Generating Diverse High-Fidelity Images with VQ-VAE-2
    • [cs.LG]Generative Adversarial Networks: A Survey and Taxonomy
    • [cs.LG]Graduated Optimization of Black-Box Functions
    • [cs.LG]HERA: Partial Label Learning by Combining Heterogeneous Loss with Sparse and Low-Rank Regularization
    • [cs.LG]Hierarchical Auxiliary Learning
    • [cs.LG]Implicit Regularization in Deep Matrix Factorization
    • [cs.LG]Information Competing Process for Learning Diversified Representations
    • [cs.LG]Inverse boosting pruning trees for depression detection on Twitter
    • [cs.LG]Kernel Instrumental Variable Regression
    • [cs.LG]Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints
    • [cs.LG]Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs
    • [cs.LG]Learning Domain Randomization Distributions for Transfer of Locomotion Policies
    • [cs.LG]Learning Interpretable Shapelets for Time Series Classification through Adversarial Regularization
    • [cs.LG]Learning Representations by Maximizing Mutual Information Across Views
    • [cs.LG]Learning Transferable Cooperative Behavior in Multi-Agent Teams
    • [cs.LG]Learning low-dimensional state embeddings and metastable clusters from time series data
    • [cs.LG]Learning to Clear the Market
    • [cs.LG]Load Balancing for Ultra-Dense Networks: A Deep Reinforcement Learning Based Approach
    • [cs.LG]Low-rank Random Tensor for Bilinear Pooling
    • [cs.LG]Metric Learning for Individual Fairness
    • [cs.LG]Minimax bounds for structured prediction
    • [cs.LG]Model selection for contextual bandits
    • [cs.LG]Modular Universal Reparameterization: Deep Multi-task Learning Across Diverse Domains
    • [cs.LG]Near-Optimal Online Egalitarian learning in General Sum Repeated Matrix Games
    • [cs.LG]Nemesyst: A Hybrid Parallelism Deep Learning-Based Framework Applied for Internet of Things Enabled Food Retailing Refrigeration Systems
    • [cs.LG]Neural Network-based Object Classification by Known and Unknown Features (Based on Text Queries)
    • [cs.LG]NeuralDivergence: Exploring and Understanding Neural Networks by Comparing Activation Distributions
    • [cs.LG]NodeDrop: A Condition for Reducing Network Size without Effect on Output
    • [cs.LG]Nonstochastic Multiarmed Bandits with Unrestricted Delays
    • [cs.LG]Off-Policy Evaluation via Off-Policy Classification
    • [cs.LG]On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems
    • [cs.LG]On Privacy Protection of Latent Dirichlet Allocation Model Training
    • [cs.LG]On The Radon—Nikodym Spectral Approach With Optimal Clustering
    • [cs.LG]On the Correctness and Sample Complexity of Inverse Reinforcement Learning
    • [cs.LG]On the computational complexity of the probabilistic label tree algorithms
    • [cs.LG]One-Way Prototypical Networks
    • [cs.LG]Optimal Learning of Mallows Block Model
    • [cs.LG]Optimal Transport on the Manifold of SPD Matrices for Domain Adaptation
    • [cs.LG]Optimal Unsupervised Domain Translation
    • [cs.LG]Options as responses: Grounding behavioural hierarchies in multi-agent RL
    • [cs.LG]PCA-driven Hybrid network design for enabling Intelligence at the Edge
    • [cs.LG]Posterior Variance Analysis of Gaussian Processes with Application to Average Learning Curves
    • [cs.LG]Proximal Reliability Optimization for Reinforcement Learning
    • [cs.LG]Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel
    • [cs.LG]RL-Based Method for Benchmarking the Adversarial Resilience and Robustness of Deep Reinforcement Learning Policies
    • [cs.LG]Radial-Based Undersampling for Imbalanced Data Classification
    • [cs.LG]Robust Learning Under Label Noise With Iterative Noise-Filtering
    • [cs.LG]Self-supervised Body Image Acquisition Using a Deep Neural Network for Sensorimotor Prediction
    • [cs.LG]Sequential Triggers for Watermarking of Deep Reinforcement Learning Policies
    • [cs.LG]Sparse Representation Classification via Screening for Graphs
    • [cs.LG]Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction
    • [cs.LG]Statistically Significant Discriminative Patterns Searching
    • [cs.LG]Super-resolution of Time-series Labels for Bootstrapped Event Detection
    • [cs.LG]Temporal Density Extrapolation using a Dynamic Basis Approach
    • [cs.LG]The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies
    • [cs.LG]The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation
    • [cs.LG]The Principle of Unchanged Optimality in Reinforcement Learning Generalization
    • [cs.LG]Topological Autoencoders
    • [cs.LG]Toward Building Conversational Recommender Systems: A Contextual Bandit Approach
    • [cs.LG]Towards Interactive Training of Non-Player Characters in Video Games
    • [cs.LG]Truncated Cauchy Non-negative Matrix Factorization
    • [cs.LG]Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control
    • [cs.LG]Unsupervised Emergence of Egocentric Spatial Structure from Sensorimotor Prediction
    • [cs.LG]Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning
    • [cs.LG]Wasserstein Weisfeiler-Lehman Graph Kernels
    • [cs.LG]Weakly Supervised Disentanglement by Pairwise Similarities
    • [cs.LG]Y-GAN: A Generative Adversarial Network for Depthmap Estimation from Multi-camera Stereo Images
    • [cs.LO]Reasoning about disclosure in data integration in the presence of source constraints
    • [cs.MA]Multiple Drones driven Hexagonally Partitioned Area Exploration: Simulation and Evaluation
    • [cs.NA]Learning Neural PDE Solvers with Convergence Guarantees
    • [cs.NE]Hamiltonian Neural Networks
    • [cs.NE]Kinetic Market Model: An Evolutionary Algorithm
    • [cs.NE]Multi-objective Pruning for CNNs using Genetic Algorithm
    • [cs.NE]Neural networks grown and self-organized by noise
    • [cs.NE]Push and Pull Search Embedded in an M2M Framework for Solving Constrained Multi-objective Optimization Problems
    • [cs.NE]SpikeGrad: An ANN-equivalent Computation Model for Implementing Backpropagation with Spikes
    • [cs.NE]Training Detection-Range-Frugal Cooperative Collision Avoidance Models for Quadcopters via Neuroevolution
    • [cs.NI]Blockchain for Internet of Things: A Survey
    • [cs.NI]Cellular Traffic Prediction and Classification: a comparative evaluation of LSTM and ARIMA
    • [cs.NI]On Provisioning Cellular Networks for Distributed Inference
    • [cs.NI]Probabilistic QoS-aware Placement of VNF chains at the Edge
    • [cs.OS]Cache Contention on Multicore Systems: An Ontology-based Approach
    • [cs.RO]Air Learning: An AI Research Platform for Algorithm-Hardware Benchmarking of Autonomous Aerial Robots
    • [cs.RO]Analysis of Obstacle based Probabilistic RoadMap Method using Geometric Probability
    • [cs.RO]Closed-Loop Control of a Delta-Wing Unmanned Aerial-Aquatic Vehicle
    • [cs.RO]Effects of Different Hand-Grounding Locations on Haptic Performance With a Wearable Kinesthetic Haptic Device
    • [cs.RO]GAMMA: A General Agent Motion Prediction Model for Autonomous Driving
    • [cs.RO]Grid-based Localization Stack for Inspection Drones towards Automation of Large Scale Warehouse Systems
    • [cs.RO]Harnessing Reinforcement Learning for Neural Motion Planning
    • [cs.RO]Knowledge is Never Enough: Towards Web Aided Deep Open World Recognition
    • [cs.RO]Localization Requirements for Autonomous Vehicles
    • [cs.RO]Longitudinal Trajectory Prediction of Human-driven Vehicles Near Traffic Lights
    • [cs.RO]Rapidly-Exploring Quotient-Space Trees: Motion Planning using Sequential Simplifications
    • [cs.RO]Socially Inspired Communication in Swarm Robotics
    • [cs.RO]Vision-Based Autonomous UAV Navigation and Landing for Urban Search and Rescue
    • [cs.SD]A Surprising Density of Illusionable Natural Speech
    • [cs.SE]Gamification of Enterprise Systems: A Synthesis of Mechanics, Dynamics, and Risks
    • [cs.SE]Neural Bug Finding: A Study of Opportunities and Challenges
    • [cs.SI]Can Women Break the Glass Ceiling?: An Analysis of #MeToo Hashtagged Posts on Twitter
    • [cs.SI]Evaluating network partitions through visualization
    • [cs.SI]Implication Avoiding Dynamics for Externally Observed Networks
    • [cs.SI]Need for Critical Cyber Defence, Security Strategy and Privacy Policy in Bangladesh - Hype or Reality?
    • [cs.SI]The Strength of Structural Diversity in Online Social Networks
    • [cs.SI]Understanding the Silence of Sexual Harassment Victims Through the #WhyIDidntReport Movement
    • [cs.SY]Robust stability of moving horizon estimation for nonlinear systems with bounded disturbances using adaptive arrival cost
    • [eess.AS]Evaluating Non-aligned Musical Score Transcriptions with MV2H
    • [eess.AS]MelNet: A Generative Model for Audio in the Frequency Domain
    • [eess.IV]A Semantic-based Medical Image Fusion Approach
    • [eess.IV]Deep Feature Learning from a Hospital-Scale Chest X-ray Dataset with Application to TB Detection on a Small-Scale Dataset
    • [eess.IV]Learning Deep Image Priors for Blind Image Denoising
    • [eess.IV]Lung cancer screening with low-dose CT scans using a deep learning approach
    • [eess.IV]Natural Image Noise Dataset
    • [eess.IV]Probabilistic Noise2Void: Unsupervised Content-Aware Denoising
    • [eess.SP]A Nonlinear Acceleration Method for Iterative Algorithms
    • [eess.SP]Deep Reinforcement Learning Architecture for Continuous Power Allocation in High Throughput Satellites
    • [eess.SP]Deterministic and stochastic damage detection via dynamic response analysis
    • [eess.SP]Gridless Variational Bayesian Channel Estimation for Antenna Array Systems with Low Resolution ADCs
    • [eess.SP]Sparse Bayesian Learning Approach for Discrete Signal Reconstruction
    • [eess.SP]What, Where and How to Transfer in SAR Target Recognition Based on Deep CNNs
    • [hep-ph]Effective LHC measurements with matrix elements and machine learning
    • [math.AT]A numerical measure of the instability of Mapper-type algorithms
    • [math.DG]Optimal transport and information geometry
    • [math.NA]Exploiting nested task-parallelism in the $\mathcal{H}-LU$ factorization
    • [math.OC]A Generic Acceleration Framework for Stochastic Composite Optimization
    • [math.OC]Adaptive Model Refinement with Batch Bayesian Sampling for Optimization of Bio-inspired Flow Tailoring
    • [math.OC]Data-Pooling in Stochastic Optimization
    • [math.OC]Generalized Momentum-Based Methods: A Hamiltonian Perspective
    • [math.OC]Higher-Order Accelerated Methods for Faster Non-Smooth Optimization
    • [math.OC]Proximal Point Approximations Achieving a Convergence Rate of $\mathcal{O}(1/k)$ for Smooth Convex-Concave Saddle Point Problems: Optimistic Gradient and Extra-gradient Methods
    • [math.OC]Robust exploration in linear quadratic reinforcement learning
    • [math.OC]Towards Unified Acceleration of High-Order Algorithms under Hölder Continuity and Uniform Convexity
    • [math.ST]A mean-field limit for certain deep neural networks
    • [math.ST]A test against trend in random sequences
    • [math.ST]Asymptotic Properties of Neural Network Sieve Estimators
    • [math.ST]Confidence Regions in Wasserstein Distributionally Robust Estimation
    • [math.ST]How many variables should be entered in a principal component regression equation?
    • [math.ST]Inference robust to outliers with l1-norm penalization
    • [math.ST]Multi-reference factor analysis: low-rank covariance estimation under unknown translations
    • [math.ST]On Testing for Parameters in Ising Models
    • [math.ST]Robust Mean Estimation with the Bayesian Median of Means
    • [math.ST]Semiparametric Analysis of the Proportional Likelihood Ratio Model and Omnibus Estimation Procedure
    • [physics.comp-ph]A new nonlocal forward model for diffuse optical tomography
    • [physics.data-an]Revision of ISO 19229 to support the certification of calibration gases for purity
    • [q-bio.NC]A detailed study of recurrent neural networks used to model tasks in the cerebral cortex
    • [q-bio.NC]Learning to solve the credit assignment problem
    • [q-bio.NC]Signal Coding and Perfect Reconstruction using Spike Trains
    • [q-fin.ST]Conditional inference on the asset with maximum Sharpe ratio
    • [stat.AP]A Dyadic IRT Model
    • [stat.AP]Encouraging Equitable Bikeshare: Implications of Docked and Dockless Models for Spatial Equity
    • [stat.AP]Generalised linear models for prognosis and intervention: Theory, practice, and implications for machine learning
    • [stat.AP]Joint spatial modeling of significant wave height and wave period using the SPDE approach
    • [stat.AP]Model Trees for Personalization
    • [stat.AP]Statistical analysis of the water level of Huang He river (Yellow river) in China
    • [stat.AP]Stress Testing Network Reconstruction via Graphical Causal Mode
    • [stat.CO]lspartition: Partitioning-Based Least Squares Regression
    • [stat.CO]nprobust: Nonparametric Kernel-Based Estimation and Robust Bias-Corrected Inference
    • [stat.ME]Anchored Causal Inference in the Presence of Measurement Error
    • [stat.ME]Bayesian Profiling Multiple Imputation for Missing Electronic Health Records
    • [stat.ME]Central Quantile Subspace
    • [stat.ME]Clustering Multivariate Data using Factor Analytic Bayesian Mixtures with an Unknown Number of Components
    • [stat.ME]Combining Heterogeneous Spatial Datasets with Process-based Spatial Fusion Models: A Unifying Framework
    • [stat.ME]Comprehensive cluster validity Index based on structural simplicity
    • [stat.ME]Confidence Intervals for Selected Parameters
    • [stat.ME]Copula-based functional Bayes classification with principal components and partial least squares
    • [stat.ME]Covariate-Powered Empirical Bayes Estimation
    • [stat.ME]Diagonally-Dominant Principal Component Analysis
    • [stat.ME]Estimating Real Log Canonical Thresholds
    • [stat.ME]Estimating Time-Varying Causal Excursion Effect in Mobile Health with Binary Outcomes
    • [stat.ME]Functional time series prediction under partial observation of the future curve
    • [stat.ME]Gap-Measure Tests with Applications to Data Integrity Verification
    • [stat.ME]Generating Poisson-Distributed Differentially Private Synthetic Data
    • [stat.ME]Kernel Mean Embedding Based Hypothesis Tests for Comparing Spatial Point Patterns
    • [stat.ME]Mixture of hidden Markov models for accelerometer data
    • [stat.ME]Multiplicative Effect Modeling: The General Case
    • [stat.ME]Partial and semi-partial measures of spatial associations for multivariate lattice data
    • [stat.ME]Semi-parametric Bayesian variable selection for gene-environment interactions
    • [stat.ME]Statistical methods for biomarker data pooled from multiple nested case-control studies
    • [stat.ME]The performance of the partially overlapping samples t-tests at the limits
    • [stat.ME]Transformed Central Quantile Subspace
    • [stat.ME]Unconstrained representation of orthogonal matrices with application to common principle components
    • [stat.ML]A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off
    • [stat.ML]An Evaluation Toolkit to Guide Model Selection and Cohort Definition in Causal Inference
    • [stat.ML]Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination
    • [stat.ML]Assessing Disparate Impacts of Personalized Interventions: Identifiability and Bounds
    • [stat.ML]Bayesian Optimization of Composite Functions
    • [stat.ML]Bayesian Prior Networks with PAC Training
    • [stat.ML]BreGMN: scaled-Bregman Generative Modeling Networks
    • [stat.ML]Capabilities and Limitations of Time-lagged Autoencoders for Slow Mode Discovery in Dynamical Systems
    • [stat.ML]Concept Tree: High-Level Representation of Variables for More Interpretable Surrogate Decision Trees
    • [stat.ML]Deep ReLU Networks Have Surprisingly Few Activation Patterns
    • [stat.ML]GANchors: Realistic Image Perturbation Distributions for Anchors Using Generative Models
    • [stat.ML]Graphon Estimation from Partially Observed Network Data
    • [stat.ML]Hybrid Machine Learning Forecasts for the FIFA Women’s World Cup 2019
    • [stat.ML]Learning Perceptually-Aligned Representations via Adversarial Robustness
    • [stat.ML]MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning
    • [stat.ML]MaxGap Bandit: Adaptive Algorithms for Approximate Ranking
    • [stat.ML]Nonparametric Functional Approximation with Delaunay Triangulation
    • [stat.ML]Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement
    • [stat.ML]Robust approximate linear regression without correspondence
    • [stat.ML]Separable Layers Enable Structured Efficient Linear Substitutions
    • [stat.ML]Streaming Variational Monte Carlo
    • [stat.ML]Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules
    • [stat.ML]Tensor Restricted Isometry Property Analysis For a Large Class of Random Measurement Ensembles
    • [stat.ML]The Extended Dawid-Skene Model: Fusing Information from Multiple Data Schemas
    • [stat.ML]Towards Task and Architecture-Independent Generalization Gap Predictors
    • [stat.ML]Universal Boosting Variational Inference
    • [stat.ML]What do AI algorithms actually learn? - On false structures in deep learning

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

    • [astro-ph.SR]A Curated Image Parameter Dataset from Solar Dynamics Observatory Mission
    Azim Ahmadzadeh, Dustin J. Kempton, Rafal A. Angryk
    http://arxiv.org/abs/1906.01062v1

    • [cs.AI]Automated Video Game Testing Using Synthetic and Human-Like Agents
    Sinan Ariyurek, Aysu Betin-Can, Elif Surer
    http://arxiv.org/abs/1906.00317v1

    • [cs.AI]Blackbox meets blackbox: Representational Similarity and Stability Analysis of Neural Language Models and Brains
    Samira Abnar, Lisa Beinborn, Rochelle Choenni, Willem Zuidema
    http://arxiv.org/abs/1906.01539v1

    • [cs.AI]Does It Make Sense? And Why? A Pilot Study for Sense Making and Explanation
    Cunxiang Wang, Shuailong Liang, Yue Zhang, Xiaonan Li, Tian Gao
    http://arxiv.org/abs/1906.00363v1

    • [cs.AI]Hierarchical Decision Making by Generating and Following Natural Language Instructions
    Hengyuan Hu, Denis Yarats, Qucheng Gong, Yuandong Tian, Mike Lewis
    http://arxiv.org/abs/1906.00744v1

    • [cs.AI]Kandinsky Patterns
    Heimo Mueller, Andreas Holzinger
    http://arxiv.org/abs/1906.00657v1

    • [cs.AI]Pre-training of Graph Augmented Transformers for Medication Recommendation
    Junyuan Shang, Tengfei Ma, Cao Xiao, Jimeng Sun
    http://arxiv.org/abs/1906.00346v1

    • [cs.AI]Smoothing Structured Decomposable Circuits
    Andy Shih, Guy Van den Broeck, Paul Beame, Antoine Amarilli
    http://arxiv.org/abs/1906.00311v1

    • [cs.CL]A Cross-Sentence Latent Variable Model for Semi-Supervised Text Sequence Matching
    Jihun Choi, Taeuk Kim, Sang-goo Lee
    http://arxiv.org/abs/1906.01343v1

    • [cs.CL]A Review of Language and Speech Features for Cognitive-Linguistic Assessment
    Rohit Voleti, Julie M. Liss, Visar Berisha
    http://arxiv.org/abs/1906.01157v1

    • [cs.CL]A Semi-Supervised Approach for Low-Resourced Text Generation
    Hongyu Zang, Xiaojun Wan
    http://arxiv.org/abs/1906.00584v1

    • [cs.CL]A Study of Feature Extraction techniques for Sentiment Analysis
    Avinash Madasu, Sivasankar E
    http://arxiv.org/abs/1906.01573v1

    • [cs.CL]A Survey of Natural Language Generation Techniques with a Focus on Dialogue Systems - Past, Present and Future Directions
    Sashank Santhanam, Samira Shaikh
    http://arxiv.org/abs/1906.00500v1

    • [cs.CL]A computational linguistic study of personal recovery in bipolar disorder
    Glorianna Jagfeld
    http://arxiv.org/abs/1906.01010v1

    • [cs.CL]Are Girls Neko or Shōjo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization
    Mozhi Zhang, Keyulu Xu, Ken-ichi Kawarabayashi, Stefanie Jegelka, Jordan Boyd-Graber
    http://arxiv.org/abs/1906.01622v1

    • [cs.CL]Are You Looking? Grounding to Multiple Modalities in Vision-and-Language Navigation
    Ronghang Hu, Daniel Fried, Anna Rohrbach, Dan Klein, Trevor Darrell, Kate Saenko
    http://arxiv.org/abs/1906.00347v2

    • [cs.CL]Are we there yet? Encoder-decoder neural networks as cognitive models of English past tense inflection
    Maria Corkery, Yevgen Matusevych, Sharon Goldwater
    http://arxiv.org/abs/1906.01280v1

    • [cs.CL]Assessing the Ability of Self-Attention Networks to Learn Word Order
    Baosong Yang, Longyue Wang, Derek F. Wong, Lidia S. Chao, Zhaopeng Tu
    http://arxiv.org/abs/1906.00592v1

    • [cs.CL]Back Attention Knowledge Transfer for Low-resource Named Entity Recognition
    Linghao Sun, Huixiong Yi, Huanhuan Chen
    http://arxiv.org/abs/1906.01183v1

    • [cs.CL]Better Character Language Modeling Through Morphology
    Terra Blevins, Luke Zettlemoyer
    http://arxiv.org/abs/1906.01037v1

    • [cs.CL]Boosting Entity Linking Performance by Leveraging Unlabeled Documents
    Phong Le, Ivan Titov
    http://arxiv.org/abs/1906.01250v1

    • [cs.CL]Budgeted Policy Learning for Task-Oriented Dialogue Systems
    Zhirui Zhang, Xiujun Li, Jianfeng Gao, Enhong Chen
    http://arxiv.org/abs/1906.00499v1

    • [cs.CL]ChID: A Large-scale Chinese IDiom Dataset for Cloze Test
    Chujie Zheng, Minlie Huang, Aixin Sun
    http://arxiv.org/abs/1906.01265v1

    • [cs.CL]Coherent Comment Generation for Chinese Articles with a Graph-to-Sequence Model
    Wei Li, Jingjing Xu, Yancheng He, Shengli Yan, Yunfang Wu, Xu sun
    http://arxiv.org/abs/1906.01231v1

    • [cs.CL]Controllable Paraphrase Generation with a Syntactic Exemplar
    Mingda Chen, Qingming Tang, Sam Wiseman, Kevin Gimpel
    http://arxiv.org/abs/1906.00565v1

    • [cs.CL]Curate and Generate: A Corpus and Method for Joint Control of Semantics and Style in Neural NLG
    Shereen Oraby, Vrindavan Harrison, Abteen Ebrahimi, Marilyn Walker
    http://arxiv.org/abs/1906.01334v1

    • [cs.CL]Deep Unknown Intent Detection with Margin Loss
    Ting-En Lin, Hua Xu
    http://arxiv.org/abs/1906.00434v1

    • [cs.CL]Distantly Supervised Named Entity Recognition using Positive-Unlabeled Learning
    Minlong Peng, Xiaoyu Xing, Qi Zhang, Jinlan Fu, Xuanjing Huang
    http://arxiv.org/abs/1906.01378v1

    • [cs.CL]Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study
    Chinnadhurai Sankar, Sandeep Subramanian, Christopher Pal, Sarath Chandar, Yoshua Bengio
    http://arxiv.org/abs/1906.01603v1

    • [cs.CL]Domain Adaptation of Neural Machine Translation by Lexicon Induction
    Junjie Hu, Mengzhou Xia, Graham Neubig, Jaime Carbonell
    http://arxiv.org/abs/1906.00376v1

    • [cs.CL]Domain Adaptive Inference for Neural Machine Translation
    Danielle Saunders, Felix Stahlberg, Adria de Gispert, Bill Byrne
    http://arxiv.org/abs/1906.00408v1

    • [cs.CL]Dynamically Composing Domain-Data Selection with Clean-Data Selection by “Co-Curricular Learning” for Neural Machine Translation
    Wei Wang, Isaac Caswell, Ciprian Chelba
    http://arxiv.org/abs/1906.01130v1

    • [cs.CL]Emotion-Cause Pair Extraction: A New Task to Emotion Analysis in Texts
    Rui Xia, Zixiang Ding
    http://arxiv.org/abs/1906.01267v1

    • [cs.CL]Evaluating Discourse in Structured Text Representations
    Elisa Ferracane, Greg Durrett, Junyi Jessy Li, Katrin Erk
    http://arxiv.org/abs/1906.01472v1

    • [cs.CL]Evaluating Gender Bias in Machine Translation
    Gabriel Stanovsky, Noah A. Smith, Luke Zettlemoyer
    http://arxiv.org/abs/1906.00591v1

    • [cs.CL]Exploiting Sentential Context for Neural Machine Translation
    Xing Wang, Zhaopeng Tu, Longyue Wang, Shuming Shi
    http://arxiv.org/abs/1906.01268v1

    • [cs.CL]Exploring Phoneme-Level Speech Representations for End-to-End Speech Translation
    Elizabeth Salesky, Matthias Sperber, Alan W Black
    http://arxiv.org/abs/1906.01199v1

    • [cs.CL]Finding Syntactic Representations in Neural Stacks
    William Merrill, Lenny Khazan, Noah Amsel, Yiding Hao, Simon Mendelsohn, Robert Frank
    http://arxiv.org/abs/1906.01594v1

    • [cs.CL]Fluent Translations from Disfluent Speech in End-to-End Speech Translation
    Elizabeth Salesky, Matthias Sperber, Alex Waibel
    http://arxiv.org/abs/1906.00556v1

    • [cs.CL]From Independent Prediction to Re-ordered Prediction: Integrating Relative Position and Global Label Information to Emotion Cause Identification
    Zixiang Ding, Huihui He, Mengran Zhang, Rui Xia
    http://arxiv.org/abs/1906.01230v1

    • [cs.CL]From Speech Chain to Multimodal Chain: Leveraging Cross-modal Data Augmentation for Semi-supervised Learning
    Johanes Effendi, Andros Tjandra, Sakriani Sakti, Satoshi Nakamura
    http://arxiv.org/abs/1906.00579v1

    • [cs.CL]From Words to Sentences: A Progressive Learning Approach for Zero-resource Machine Translation with Visual Pivots
    Shizhe Chen, Qin Jin, Jianlong Fu
    http://arxiv.org/abs/1906.00872v1

    • [cs.CL]Gender-preserving Debiasing for Pre-trained Word Embeddings
    Masahiro Kaneko, Danushka Bollegala
    http://arxiv.org/abs/1906.00742v1

    • [cs.CL]Gendered Ambiguous Pronouns Shared Task: Boosting Model Confidence by Evidence Pooling
    Sandeep Attree
    http://arxiv.org/abs/1906.00839v1

    • [cs.CL]Global Textual Relation Embedding for Relational Understanding
    Zhiyu Chen, Hanwen Zha, Honglei Liu, Wenhu Chen, Xifeng Yan, Yu Su
    http://arxiv.org/abs/1906.00550v1

    • [cs.CL]Handling Divergent Reference Texts when Evaluating Table-to-Text Generation
    Bhuwan Dhingra, Manaal Faruqui, Ankur Parikh, Ming-Wei Chang, Dipanjan Das, William W. Cohen
    http://arxiv.org/abs/1906.01081v1

    • [cs.CL]HighRES: Highlight-based Reference-less Evaluation of Summarization
    Hardy, Shashi Narayan, Andreas Vlachos
    http://arxiv.org/abs/1906.01361v1

    • [cs.CL]How Large Are Lions? Inducing Distributions over Quantitative Attributes
    Yanai Elazar, Abhijit Mahabal, Deepak Ramachandran, Tania Bedrax-Weiss, Dan Roth
    http://arxiv.org/abs/1906.01327v1

    • [cs.CL]How multilingual is Multilingual BERT?
    Telmo Pires, Eva Schlinger, Dan Garrette
    http://arxiv.org/abs/1906.01502v1

    • [cs.CL]Improved Zero-shot Neural Machine Translation via Ignoring Spurious Correlations
    Jiatao Gu, Yong Wang, Kyunghyun Cho, Victor O. K. Li
    http://arxiv.org/abs/1906.01181v1

    • [cs.CL]Improving Long Distance Slot Carryover in Spoken Dialogue Systems
    Tongfei Chen, Chetan Naik, Hua He, Pushpendre Rastogi, Lambert Mathias
    http://arxiv.org/abs/1906.01149v1

    • [cs.CL]Joint Effects of Context and User History for Predicting Online Conversation Re-entries
    Xingshan Zeng, Jing Li, Lu Wang, Kam-Fai Wong
    http://arxiv.org/abs/1906.01185v1

    • [cs.CL]Jointly Learning Semantic Parser and Natural Language Generator via Dual Information Maximization
    Hai Ye, Wenjie Li, Lu Wang
    http://arxiv.org/abs/1906.00575v1

    • [cs.CL]KERMIT: Generative Insertion-Based Modeling for Sequences
    William Chan, Nikita Kitaev, Kelvin Guu, Mitchell Stern, Jakob Uszkoreit
    http://arxiv.org/abs/1906.01604v1

    • [cs.CL]Know More about Each Other: Evolving Dialogue Strategy via Compound Assessment
    Siqi Bao, Huang He, Fan Wang, Rongzhong Lian, Hua Wu
    http://arxiv.org/abs/1906.00549v1

    • [cs.CL]Latent Retrieval for Weakly Supervised Open Domain Question Answering
    Kenton Lee, Ming-Wei Chang, Kristina Toutanova
    http://arxiv.org/abs/1906.00300v1

    • [cs.CL]Lattice-Based Transformer Encoder for Neural Machine Translation
    Fengshun Xiao, Jiangtong Li, Hai Zhao, Rui Wang, Kehai Chen
    http://arxiv.org/abs/1906.01282v1

    • [cs.CL]Learning to Explain: Answering Why-Questions via Rephrasing
    Allen Nie, Erin D. Bennett, Noah D. Goodman
    http://arxiv.org/abs/1906.01243v1

    • [cs.CL]Massive Styles Transfer with Limited Labeled Data
    Hongyu Zang, Xiaojun Wan
    http://arxiv.org/abs/1906.00580v1

    • [cs.CL]Multi-Task Semantic Dependency Parsing with Policy Gradient for Learning Easy-First Strategies
    Shuhei Kurita, Anders Søgaard
    http://arxiv.org/abs/1906.01239v1

    • [cs.CL]Multi-task Pairwise Neural Ranking for Hashtag Segmentation
    Mounica Maddela, Wei Xu, Daniel Preoţiuc-Pietro
    http://arxiv.org/abs/1906.00790v1

    • [cs.CL]Multimodal Transformer for Unaligned Multimodal Language Sequences
    Yao-Hung Hubert Tsai, Shaojie Bai, Paul Pu Liang, J. Zico Kolter, Louis-Philippe Morency, Ruslan Salakhutdinov
    http://arxiv.org/abs/1906.00295v1

    • [cs.CL]NNE: A Dataset for Nested Named Entity Recognition in English Newswire
    Nicky Ringland, Xiang Dai, Ben Hachey, Sarvnaz Karimi, Cecile Paris, James R. Curran
    http://arxiv.org/abs/1906.01359v1

    • [cs.CL]Optimal coding and the origins of Zipfian laws
    Ramon Ferrer-i-Cancho, Christian Bentz
    http://arxiv.org/abs/1906.01545v1

    • [cs.CL]Phase-based Minimalist Parsing and complexity in non-local dependencies
    Cristiano Chesi
    http://arxiv.org/abs/1906.00908v1

    • [cs.CL]Pitfalls in the Evaluation of Sentence Embeddings
    Steffen Eger, Andreas Rücklé, Iryna Gurevych
    http://arxiv.org/abs/1906.01575v1

    • [cs.CL]Plain English Summarization of Contracts
    Laura Manor, Junyi Jessy Li
    http://arxiv.org/abs/1906.00424v1

    • [cs.CL]Pretraining Methods for Dialog Context Representation Learning
    Shikib Mehri, Evgeniia Razumovskaia, Tiancheng Zhao, Maxine Eskenazi
    http://arxiv.org/abs/1906.00414v2

    • [cs.CL]Progressive Self-Supervised Attention Learning for Aspect-Level Sentiment Analysis
    Jialong Tang, Ziyao Lu, Jinsong Su, Yubin Ge, Linfeng Song, Le Sun, Jiebo Luo
    http://arxiv.org/abs/1906.01213v1

    • [cs.CL]Promotion of Answer Value Measurement with Domain Effects in Community Question Answering Systems
    Binbin Jin, Enhong Chen, Hongke Zhao, Zhenya Huang, Qi Liu, Hengshu Zhu, Shui Yu
    http://arxiv.org/abs/1906.00156v1

    • [cs.CL]Question Answering as an Automatic Evaluation Metric for News Article Summarization
    Matan Eyal, Tal Baumel, Michael Elhadad
    http://arxiv.org/abs/1906.00318v1

    • [cs.CL]RTHN: A RNN-Transformer Hierarchical Network for Emotion Cause Extraction
    Rui Xia, Mengran Zhang, Zixiang Ding
    http://arxiv.org/abs/1906.01236v1

    • [cs.CL]Recognising Agreement and Disagreement between Stances with Reason Comparing Networks
    Chang Xu, Cecile Paris, Surya Nepal, Ross Sparks
    http://arxiv.org/abs/1906.01392v1

    • [cs.CL]Relation Embedding with Dihedral Group in Knowledge Graph
    Canran Xu, Ruijiang Li
    http://arxiv.org/abs/1906.00687v1

    • [cs.CL]Relational Word Embeddings
    Jose Camacho-Collados, Luis Espinosa-Anke, Steven Schockaert
    http://arxiv.org/abs/1906.01373v1

    • [cs.CL]Resolving Gendered Ambiguous Pronouns with BERT
    Matei Ionita, Yury Kashnitsky, Ken Krige, Vladimir Larin, Dennis Logvinenko, Atanas Atanasov
    http://arxiv.org/abs/1906.01161v1

    • [cs.CL]Robust Sequence-to-Sequence Acoustic Modeling with Stepwise Monotonic Attention for Neural TTS
    Mutian He, Yan Deng, Lei He
    http://arxiv.org/abs/1906.00672v1

    • [cs.CL]Self-Attentional Models for Lattice Inputs
    Matthias Sperber, Graham Neubig, Ngoc-Quan Pham, Alex Waibel
    http://arxiv.org/abs/1906.01617v1

    • [cs.CL]Semantically Constrained Multilayer Annotation: The Case of Coreference
    Jakob Prange, Nathan Schneider, Omri Abend
    http://arxiv.org/abs/1906.00663v2

    • [cs.CL]Sentiment Tagging with Partial Labels using Modular Architectures
    Xiao Zhang, Dan Goldwasser
    http://arxiv.org/abs/1906.00534v2

    • [cs.CL]Sequence Tagging with Contextual and Non-Contextual Subword Representations: A Multilingual Evaluation
    Benjamin Heinzerling, Michael Strube
    http://arxiv.org/abs/1906.01569v1

    • [cs.CL]Sequential Neural Networks as Automata
    William Merrill
    http://arxiv.org/abs/1906.01615v1

    • [cs.CL]ShEMO — A Large-Scale Validated Database for Persian Speech Emotion Detection
    Omid Mohamad Nezami, Paria Jamshid Lou, Mansoureh Karami
    http://arxiv.org/abs/1906.01155v1

    • [cs.CL]SherLIiC: A Typed Event-Focused Lexical Inference Benchmark for Evaluating Natural Language Inference
    Martin Schmitt, Hinrich Schütze
    http://arxiv.org/abs/1906.01393v1

    • [cs.CL]Simultaneous Translation with Flexible Policy via Restricted Imitation Learning
    Baigong Zheng, Renjie Zheng, Mingbo Ma, Liang Huang
    http://arxiv.org/abs/1906.01135v1

    • [cs.CL]System Demo for Transfer Learning across Vision and Text using Domain Specific CNN Accelerator for On-Device NLP Applications
    Baohua Sun, Lin Yang, Michael Lin, Wenhan Zhang, Patrick Dong, Charles Young, Jason Dong
    http://arxiv.org/abs/1906.01145v1

    • [cs.CL]TalkSumm: A Dataset and Scalable Annotation Method for Scientific Paper Summarization Based on Conference Talks
    Guy Lev, Michal Shmueli-Scheuer, Jonathan Herzig, Achiya Jerbi, David Konopnicki
    http://arxiv.org/abs/1906.01351v1

    • [cs.CL]Task-Guided Pair Embedding in Heterogeneous Network
    Chanyoung Park, Donghyun Kim, Qi Zhu, Jiawei Han, Hwanjo Yu
    http://arxiv.org/abs/1906.01546v1

    • [cs.CL]The PhotoBook Dataset: Building Common Ground through Visually-Grounded Dialogue
    Janosch Haber, Tim Baumgärtner, Ece Takmaz, Lieke Gelderloos, Elia Bruni, Raquel Fernández
    http://arxiv.org/abs/1906.01530v1

    • [cs.CL]Toward Grammatical Error Detection from Sentence Labels: Zero-shot Sequence Labeling with CNNs and Contextualized Embeddings
    Allen Schmaltz
    http://arxiv.org/abs/1906.01154v1

    • [cs.CL]Tracing Antisemitic Language Through Diachronic Embedding Projections: France 1789-1914
    Rocco Tripodi, Massimo Warglien, Simon Levis Sullam, Deborah Paci
    http://arxiv.org/abs/1906.01440v1

    • [cs.CL]Training Neural Machine Translation To Apply Terminology Constraints
    Georgiana Dinu, Prashant Mathur, Marcello Federico, Yaser Al-Onaizan
    http://arxiv.org/abs/1906.01105v1

    • [cs.CL]Training Neural Response Selection for Task-Oriented Dialogue Systems
    Matthew Henderson, Ivan Vulić, Daniela Gerz, Iñigo Casanueva, Paweł Budzianowski, Sam Coope, Georgios Spithourakis, Tsung-Hsien Wen, Nikola Mrkšić, Pei-Hao Su
    http://arxiv.org/abs/1906.01543v1

    • [cs.CL]Transcoding compositionally: using attention to find more generalizable solutions
    Kris Korrel, Dieuwke Hupkes, Verna Dankers, Elia Bruni
    http://arxiv.org/abs/1906.01234v1

    • [cs.CL]Transferable Neural Projection Representations
    Chinnadhurai Sankar, Sujith Ravi, Zornitsa Kozareva
    http://arxiv.org/abs/1906.01605v1

    • [cs.CL]Transforming Complex Sentences into a Semantic Hierarchy
    Christina Niklaus, Matthias Cetto, Andre Freitas, Siegfried Handschuh
    http://arxiv.org/abs/1906.01038v1

    • [cs.CL]Unsupervised Bilingual Lexicon Induction from Mono-lingual Multimodal Data
    Shizhe Chen, Qin Jin, Alexander Hauptmann
    http://arxiv.org/abs/1906.00378v1

    • [cs.CR]DAWN: Dynamic Adversarial Watermarking of Neural Networks
    Sebastian Szyller, Buse Gul Atli, Samuel Marchal, N. Asokan
    http://arxiv.org/abs/1906.00830v1

    • [cs.CR]Encryption Scheme Based on Expanded Reed-Solomon Codes
    Karan Khathuria, Joachim Rosenthal, Violetta Weger
    http://arxiv.org/abs/1906.00745v1

    • [cs.CR]Generative Adversarial Networks for Distributed Intrusion Detection in the Internet of Things
    Aidin Ferdowsi, Walid Saad
    http://arxiv.org/abs/1906.00567v1

    • [cs.CR]Human-Usable Password Schemas: Beyond Information-Theoretic Security
    Elan Rosenfeld, Santosh Vempala, Manuel Blum
    http://arxiv.org/abs/1906.00029v1

    • [cs.CR]New non-linearity parameters of Boolean functions
    Igor Semaev
    http://arxiv.org/abs/1906.00426v1

    • [cs.CR]Privacy-preserving Crowd-guided AI Decision-making in Ethical Dilemmas
    Teng Wang, Jun Zhao, Han Yu, Jinyan Liu, Xinyu Yang, Xuebin Ren, Shuyu Shi
    http://arxiv.org/abs/1906.01562v1

    • [cs.CR]Towards Fair and Decentralized Privacy-Preserving Deep Learning with Blockchain
    Lingjuan Lyu, Jiangshan Yu, Karthik Nandakumar, Yitong Li, Xingjun Ma, Jiong Jin
    http://arxiv.org/abs/1906.01167v1

    • [cs.CV]3D Appearance Super-Resolution with Deep Learning
    Yawei Li, Vagia Tsiminaki, Radu Timofte, Marc Pollefeys, Luc van Gool
    http://arxiv.org/abs/1906.00925v2

    • [cs.CV]A Closed-form Solution to Universal Style Transfer
    Ming Lu, Hao Zhao, Anbang Yao, Yurong Chen, Feng Xu, Li Zhang
    http://arxiv.org/abs/1906.00668v1

    • [cs.CV]A Hybrid RNN-HMM Approach for Weakly Supervised Temporal Action Segmentation
    Hilde Kuehne, Alexander Richard, Juergen Gall
    http://arxiv.org/abs/1906.01028v1

    • [cs.CV]Active Object Manipulation Facilitates Visual Object Learning: An Egocentric Vision Study
    Satoshi Tsutsui, Dian Zhi, Md Alimoor Reza, David Crandall, Chen Yu
    http://arxiv.org/abs/1906.01415v1

    • [cs.CV]Adversarial Examples for Edge Detection: They Exist, and They Transfer
    Christian Cosgrove, Alan L. Yuille
    http://arxiv.org/abs/1906.00335v1

    • [cs.CV]An Adaptive Training-less System for Anomaly Detection in Crowd Scenes
    Arindam Sikdar, Ananda S. Chowdhury
    http://arxiv.org/abs/1906.00705v1

    • [cs.CV]Automated Steel Bar Counting and Center Localization with Convolutional Neural Networks
    Zhun Fan, Jiewei Lu, Benzhang Qiu, Tao Jiang, Kang An, Alex Noel Josephraj, Chuliang Wei
    http://arxiv.org/abs/1906.00891v1

    • [cs.CV]Automatic Health Problem Detection from Gait Videos Using Deep Neural Networks
    Rahil Mehrizi, Xi Peng, Shaoting Zhang, Ruisong Liao, Kang Li
    http://arxiv.org/abs/1906.01480v1

    • [cs.CV]Color Constancy Convolutional Autoencoder
    Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Jarno Nikkanen, Moncef Gabbouj
    http://arxiv.org/abs/1906.01340v1

    • [cs.CV]Comparing two- and three-view Computer Vision
    Zsolt Levente Kucsván
    http://arxiv.org/abs/1906.01003v1

    • [cs.CV]Computing Valid p-values for Image Segmentation by Selective Inference
    Kosuke Tanizaki, Noriaki Hashimoto, Yu Inatsu, Hidekata Hontani, Ichiro Takeuchi
    http://arxiv.org/abs/1906.00629v1

    • [cs.CV]Content Adaptive Optimization for Neural Image Compression
    Joaquim Campos, Meierhans Simon, Abdelaziz Djelouah, Christopher Schroers
    http://arxiv.org/abs/1906.01223v1

    • [cs.CV]Cross-Domain Cascaded Deep Feature Translation
    Oren Katzir, Dani Lischinski, Daniel Cohen-Or
    http://arxiv.org/abs/1906.01526v1

    • [cs.CV]Data Augmentation for Object Detection via Progressive and Selective Instance-Switching
    Hao Wang, Qilong Wang, Fan Yang, Weiqi Zhang, Wangmeng Zuo
    http://arxiv.org/abs/1906.00358v1

    • [cs.CV]Deep Face Recognition Model Compression via Knowledge Transfer and Distillation
    Jayashree Karlekar, Jiashi Feng, Zi Sian Wong, Sugiri Pranata
    http://arxiv.org/abs/1906.00619v1

    • [cs.CV]Deeply-supervised Knowledge Synergy
    Dawei Sun, Anbang Yao, Aojun Zhou, Hao Zhao
    http://arxiv.org/abs/1906.00675v2

    • [cs.CV]Depth-Preserving Real-Time Arbitrary Style Transfer
    Konstantin Kozlovtsev, Victor Kitov
    http://arxiv.org/abs/1906.01123v1

    • [cs.CV]Disentangling neural mechanisms for perceptual grouping
    Junkyung Kim, Drew Linsley, Kalpit Thakkar, Thomas Serre
    http://arxiv.org/abs/1906.01558v1

    • [cs.CV]Dominant Set Clustering and Pooling for Multi-View 3D Object Recognition
    Chu Wang, Marcello Pelillo, Kaleem Siddiqi
    http://arxiv.org/abs/1906.01592v1

    • [cs.CV]DualDis: Dual-Branch Disentangling with Adversarial Learning
    Thomas Robert, Nicolas Thome, Matthieu Cord
    http://arxiv.org/abs/1906.00804v1

    • [cs.CV]Dynamic Neural Network Decoupling
    Yuchao Li, Rongrong Ji, Shaohui Lin, Baochang Zhang, Chenqian Yan, Yongjian Wu, Feiyue Huang, Ling Shao
    http://arxiv.org/abs/1906.01166v1

    • [cs.CV]End-to-End Learning of Geometric Deformations of Feature Maps for Virtual Try-On
    Thibaut Issenhuth, Jérémie Mary, Clément Calauzennes
    http://arxiv.org/abs/1906.01347v1

    • [cs.CV]Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study
    Thomas W. Rogers, Nicolas Jaccard, Francis Carbonaro, Hans G. Lemij, Koenraad A. Vermeer, Nicolaas J. Reus, Sameer Trikha
    http://arxiv.org/abs/1906.01272v1

    • [cs.CV]Example-Guided Style Consistent Image Synthesis from Semantic Labeling
    Miao Wang, Guo-Ye Yang, Ruilong Li, Run-Ze Liang, Song-Hai Zhang, Peter. M. Hall, Shi-Min Hu
    http://arxiv.org/abs/1906.01314v1

    • [cs.CV]Exploiting Offset-guided Network for Pose Estimation and Tracking
    Rui Zhang, Zheng Zhu, Peng Li, Rui Wu, Chaoxu Guo, Guan Huang, Hailun Xia
    http://arxiv.org/abs/1906.01344v1

    • [cs.CV]Face Parsing with RoI Tanh-Warping
    Jinpeng Lin, Hao Yang, Dong Chen, Ming Zeng, Fang Wen, Lu Yuan
    http://arxiv.org/abs/1906.01342v1

    • [cs.CV]Fashion Editing with Multi-scale Attention Normalization
    Haoye Dong, Xiaodan Liang, Yixuan Zhang, Xujie Zhang, Zhenyu Xie, Bowen Wu, Ziqi Zhang, Xiaohui Shen, Jian Yin
    http://arxiv.org/abs/1906.00884v1

    • [cs.CV]GazeCorrection:Self-Guided Eye Manipulation in the wild using Self-Supervised Generative Adversarial Networks
    Jichao Zhang, Meng Sun, Jingjing Chen, Hao Tang, Yan Yan, Xueying Qin, Nicu Sebe
    http://arxiv.org/abs/1906.00805v1

    • [cs.CV]Generating Question Relevant Captions to Aid Visual Question Answering
    Jialin Wu, Zeyuan Hu, Raymond J. Mooney
    http://arxiv.org/abs/1906.00513v1

    • [cs.CV]Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network
    Feng Mao, Xiang Wu, Hui Xue, Rong Zhang
    http://arxiv.org/abs/1906.00377v1

    • [cs.CV]How Much Does Audio Matter to Recognize Egocentric Object Interactions?
    Alejandro Cartas, Jordi Luque, Petia Radeva, Carlos Segura, Mariella Dimiccoli
    http://arxiv.org/abs/1906.00634v1

    • [cs.CV]Incremental Few-Shot Learning for Pedestrian Attribute Recognition
    Liuyu Xiang, Xiaoming Jin, Guiguang Ding, Jungong Han, Leida Li
    http://arxiv.org/abs/1906.00330v1

    • [cs.CV]Iterative Path Reconstruction for Large-Scale Inertial Navigation on Smartphones
    Santiago Cortés Reina, Yuxin Hou, Juho Kannala, Arno Solin
    http://arxiv.org/abs/1906.00360v1

    • [cs.CV]KarNet: An Efficient Boolean Function Simplifier
    Shanka Subhra Mondal, Abhilash Nandy, Ritesh Agrawal, Debashis Sen
    http://arxiv.org/abs/1906.01363v1

    • [cs.CV]Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds
    Bo Yang, Jianan Wang, Ronald Clark, Qingyong Hu, Sen Wang, Andrew Markham, Niki Trigoni
    http://arxiv.org/abs/1906.01140v1

    • [cs.CV]Learning Rotation Adaptive Correlation Filters in Robust Visual Object Tracking
    Litu Rout, Priya Mariam Raju, Deepak Mishra, Rama Krishna Sai Subrahmanyam Gorthi
    http://arxiv.org/abs/1906.01551v1

    • [cs.CV]Learning to Generate Grounded Image Captions without Localization Supervision
    Chih-Yao Ma, Yannis Kalantidis, Ghassan AlRegib, Peter Vajda, Marcus Rohrbach, Zsolt Kira
    http://arxiv.org/abs/1906.00283v1

    • [cs.CV]Learning to Self-Train for Semi-Supervised Few-Shot Classification
    Qianru Sun, Xinzhe Li, Yaoyao Liu, Shibao Zheng, Tat-Seng Chua, Bernt Schiele
    http://arxiv.org/abs/1906.00562v1

    • [cs.CV]Localization in Aerial Imagery with Grid Maps using LocGAN
    Haohao Hu, Junyi Zhu, Sascha Wirges, Martin Lauer
    http://arxiv.org/abs/1906.01540v1

    • [cs.CV]Masked Non-Autoregressive Image Captioning
    Junlong Gao, Xi Meng, Shiqi Wang, Xia Li, Shanshe Wang, Siwei Ma, Wen Gao
    http://arxiv.org/abs/1906.00717v1

    • [cs.CV]Mining YouTube - A dataset for learning fine-grained action concepts from webly supervised video data
    Hilde Kuehne, Ahsan Iqbal, Alexander Richard, Juergen Gall
    http://arxiv.org/abs/1906.01012v1

    • [cs.CV]Natural Vocabulary Emerges from Free-Form Annotations
    Jordi Pont-Tuset, Michael Gygli, Vittorio Ferrari
    http://arxiv.org/abs/1906.01542v1

    • [cs.CV]Panoptic Edge Detection
    Yuan Hu, Yingtian Zou, Jiashi Feng
    http://arxiv.org/abs/1906.00590v1

    • [cs.CV]Parametric Shape Modeling and Skeleton Extraction with Radial Basis Functions using Similarity Domains Network
    Sedat Ozer
    http://arxiv.org/abs/1906.00265v1

    • [cs.CV]Perceptual Embedding Consistency for Seamless Reconstruction of Tilewise Style Transfer
    Amal Lahiani, Nassir Navab, Shadi Albarqouni, Eldad Klaiman
    http://arxiv.org/abs/1906.00617v1

    • [cs.CV]Photo-Geometric Autoencoding to Learn 3D Objects from Unlabelled Images
    Shangzhe Wu, Christian Rupprecht, Andrea Vedaldi
    http://arxiv.org/abs/1906.01568v1

    • [cs.CV]RF-Net: An End-to-End Image Matching Network based on Receptive Field
    Xuelun Shen, Cheng Wang, Xin Li, Zenglei Yu, Jonathan Li, Chenglu Wen, Ming Cheng, Zijian He
    http://arxiv.org/abs/1906.00604v1

    • [cs.CV]RGB and LiDAR fusion based 3D Semantic Segmentation for Autonomous Driving
    Khaled El Madawy, Hazem Rashed, Ahmad El Sallab, Omar Nasr, Hanan Kamel, Senthil Yogamani
    http://arxiv.org/abs/1906.00208v1

    • [cs.CV]Random Path Selection for Incremental Learning
    Jathushan Rajasegaran, Munawar Hayat, Salman Khan, Fahad Shahbaz Khan, Ling Shao
    http://arxiv.org/abs/1906.01120v1

    • [cs.CV]Reconstruct and Represent Video Contents for Captioning via Reinforcement Learning
    Wei Zhang, Bairui Wang, Lin Ma, Wei Liu
    http://arxiv.org/abs/1906.01452v1

    • [cs.CV]Relational Reasoning using Prior Knowledge for Visual Captioning
    Jingyi Hou, Xinxiao Wu, Yayun Qi, Wentian Zhao, Jiebo Luo, Yunde Jia
    http://arxiv.org/abs/1906.01290v1

    • [cs.CV]Resolving Overlapping Convex Objects in Silhouette Images by Concavity Analysis and Gaussian Process
    Sahar Zafari, Mariia Murashkina, Tuomas Eerola, Jouni Sampo, Heikki Kälviäinen, Heikki Haario
    http://arxiv.org/abs/1906.01049v1

    • [cs.CV]Rethinking Loss Design for Large-scale 3D Shape Retrieval
    Zhaoqun Li, Cheng Xu, Biao Leng
    http://arxiv.org/abs/1906.00546v1

    • [cs.CV]Robust copy-move forgery detection by false alarms control
    Thibaud Ehret
    http://arxiv.org/abs/1906.00649v1

    • [cs.CV]Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations
    Vincent Sitzmann, Michael Zollhöfer, Gordon Wetzstein
    http://arxiv.org/abs/1906.01618v1

    • [cs.CV]Selective Style Transfer for Text
    Raul Gomez, Ali Furkan Biten, Lluis Gomez, Jaume Gibert, Marçal Rusiñol, Dimosthenis Karatzas
    http://arxiv.org/abs/1906.01466v1

    • [cs.CV]Semi- and Weakly-supervised Human Pose Estimation
    Norimichi Ukita, Yusuke Uematsu
    http://arxiv.org/abs/1906.01399v1

    • [cs.CV]Separate from Observation: Unsupervised Single Image Layer Separation
    Yunfei Liu, Feng Lu
    http://arxiv.org/abs/1906.00734v1

    • [cs.CV]State-aware Re-identification Feature for Multi-target Multi-camera Tracking
    Peng Li, Jiabin Zhang, Zheng Zhu, Yanwei Li, Lu Jiang, Guan Huang
    http://arxiv.org/abs/1906.01357v1

    • [cs.CV]Style Transfer With Adaptation to the Central Objects of the Scene
    Alexey Schekalev, Victor Kitov
    http://arxiv.org/abs/1906.01134v1

    • [cs.CV]Text-based Editing of Talking-head Video
    Ohad Fried, Ayush Tewari, Michael Zollhöfer, Adam Finkelstein, Eli Shechtman, Dan B Goldman, Kyle Genova, Zeyu Jin, Christian Theobalt, Maneesh Agrawala
    http://arxiv.org/abs/1906.01524v1

    • [cs.CV]The iMet Collection 2019 Challenge Dataset
    Chenyang Zhang, Christine Kaeser-Chen, Grace Vesom, Jennie Choi, Maria Kessler, Serge Belongie
    http://arxiv.org/abs/1906.00901v2

    • [cs.CV]Towards better Validity: Dispersion based Clustering for Unsupervised Person Re-identification
    Guodong Ding, Salman Khan, Zhenmin Tang, Jian Zhang, Fatih Porikli
    http://arxiv.org/abs/1906.01308v1

    • [cs.CV]Transfer Learning with intelligent training data selection for prediction of Alzheimer’s Disease
    Naimul Mefraz Khan, Marcia Hon, Nabila Abraham
    http://arxiv.org/abs/1906.01160v1

    • [cs.CV]Triangulation Learning Network: from Monocular to Stereo 3D Object Detection
    Zengyi Qin, Jinglu Wang, Yan Lu
    http://arxiv.org/abs/1906.01193v1

    • [cs.CV]Visual Diagnosis of Dermatological Disorders: Human and Machine Performance
    Jeremy Kawahara, Ghassan Hamarneh
    http://arxiv.org/abs/1906.01256v1

    • [cs.CV]Visual Tree Convolutional Neural Network in Image Classification
    Yuntao Liu, Yong Dou, Ruochun Jin, Peng Qiao
    http://arxiv.org/abs/1906.01536v1

    • [cs.CV]Zero-Shot Semantic Segmentation
    Maxime Bucher, Tuan-Hung Vu, Matthieu Cord, Patrick Pérez
    http://arxiv.org/abs/1906.00817v1

    • [cs.CV]cGANs with Conditional Convolution Layer
    Min-Cheol Sagong, Yong-Goo Shin, Yoon-Jae Yeo, Seung Park, Sung-Jea Ko
    http://arxiv.org/abs/1906.00709v1

    • [cs.CY]Apprentissage de la pensée informatique : de la formation des enseignant$\cdot$e$\cdot$s à la formation de tou$\cdot$te$\cdot$s les citoyen$\cdot$ne$\cdot$s
    Corinne Atlan, Jean-Pierre Archambault, Olivier Banus, Frédéric Bardeau, Amélie Blandeau, Antonin Cois, Martine Courbin, Gérard Giraudon, Saint-Clair Lefèvre, Valérie Letard, Bastien Masse, Florent Masseglia, Benjamin Ninassi, Sophie de Quatrebarbes, Margarida Romero, Didier Roy, Thierry Vieville
    http://arxiv.org/abs/1906.00647v1

    • [cs.CY]Grade prediction with course and student specific models
    Agoritsa Polyzou, George Karypis
    http://arxiv.org/abs/1906.00792v1

    • [cs.CY]Peut-on former les enseignant$\cdot$e$\cdot$s en un rien de temps ?
    Christelle Mariais, David Roche, Laurence Farhi, Sabrina Barnabé, Sonia Cruchon, Sophie de Quatrebarbes, Thierry Vieville
    http://arxiv.org/abs/1906.00633v1

    • [cs.DB]Efficient Algorithms for Densest Subgraph Discovery
    Yixiang Fang, Kaiqiang Yu, Reynold Cheng, Laks V. S. Lakshmanan, Xuemin Lin
    http://arxiv.org/abs/1906.00341v1

    • [cs.DB]Motivo: fast motif counting via succinct color coding and adaptive sampling
    Marco Bressan, Stefano Leucci, Alessandro Panconesi
    http://arxiv.org/abs/1906.01599v1

    • [cs.DC]A Hybrid Cache Architecture for Meeting Per-Tenant Performance Goals in a Private Cloud
    Taejoon Kim, Yu Gu, Jinoh Kim
    http://arxiv.org/abs/1906.01260v1

    • [cs.DC]A Technique for Finding Optimal Program Launch Parameters Targeting Manycore Accelerators
    Alexander Brandt, Davood Mohajerani, Marc Moreno Maza, Jeeva Paudel, Lin-Xiao Wang
    http://arxiv.org/abs/1906.00142v1

    • [cs.DC]Assessing Performance Implications of Deep Copy Operations via Microbenchmarking
    Millad Ghane, Sunita Chandrasekaran, Margaret S. Cheung
    http://arxiv.org/abs/1906.01128v1

    • [cs.DC]Mutable Locks: Combining the Best of Spin and Sleep Locks
    Romolo Marotta, Davide Tiriticco, Pierangelo Di Sanzo, Alessandro Pellegrini, Francesco Quaglia
    http://arxiv.org/abs/1906.00490v1

    • [cs.DC]Optimal Register Construction in M&M Systems
    Vassos Hadzilacos, Xing Hu, Sam Toueg
    http://arxiv.org/abs/1906.00298v1

    • [cs.DC]Patterns for Blockchain Migration
    HMN Dilum Bandara, Xiwei Xu, Ingo Weber
    http://arxiv.org/abs/1906.00239v1

    • [cs.DC]Probabilistic Top-k Dominating Query Monitoring over Multiple Uncertain IoT Data Streams in Edge Computing Environments
    Chuan-Chi Lai, Tien-Chun Wang, Chuan-Ming Liu, Li-Chun Wang
    http://arxiv.org/abs/1906.00219v1

    • [cs.DC]Proximity Neighbor Selection in Blockchain Networks
    Yusuke Aoki, Kazuyuki Shudo
    http://arxiv.org/abs/1906.00719v1

    • [cs.DC]Reconfigurable Atomic Transaction Commit (Extended Version)
    Manuel Bravo, Alexey Gotsman
    http://arxiv.org/abs/1906.01365v1

    • [cs.DS]A Direct $\tilde{O}(1/ε)$ Iteration Parallel Algorithm for Optimal Transport
    Arun Jambulapati, Aaron Sidford, Kevin Tian
    http://arxiv.org/abs/1906.00618v1

    • [cs.DS]Cores and Other Dense Structures in Complex Networks
    Edoardo Galimberti
    http://arxiv.org/abs/1906.01050v1

    • [cs.DS]On the Use of Randomness in Local Distributed Graph Algorithms
    Mohsen Ghaffari, Fabian Kuhn
    http://arxiv.org/abs/1906.00482v1

    • [cs.ET]In-memory hyperdimensional computing
    Geethan Karunaratne, Manuel Le Gallo, Giovanni Cherubini, Luca Benini, Abbas Rahimi, Abu Sebastian
    http://arxiv.org/abs/1906.01548v1

    • [cs.GR]3D Magic Mirror: Automatic Video to 3D Caricature Translation
    Yudong Guo, Luo Jiang, Lin Cai, Juyong Zhang
    http://arxiv.org/abs/1906.00544v1

    • [cs.HC]An Extensive Review of Computational Dance Automation Techniques and Applications
    Manish Joshi, Sangeeta Jadhav
    http://arxiv.org/abs/1906.00606v1

    • [cs.IR]Contextually Propagated Term Weights for Document Representation
    Casper Hansen, Christian Hansen, Stephen Alstrup, Jakob Grue Simonsen, Christina Lioma
    http://arxiv.org/abs/1906.00674v1

    • [cs.IR]Federated Hierarchical Hybrid Networks for Clickbait Detection
    Feng Liao, Hankz Hankui Zhuo, Xiaoling Huang, Yu Zhang
    http://arxiv.org/abs/1906.00638v1

    • [cs.IR]Incorporating System-Level Objectives into Recommender Systems
    Himan Abdollahpouri
    http://arxiv.org/abs/1906.01435v1

    • [cs.IR]Mining Data from the Congressional Record
    Zhengyu Ma, Tianjiao Qi, James Route, Amir Ziai
    http://arxiv.org/abs/1906.00529v1

    • [cs.IR]Personalized Multimedia Item and Key Frame Recommendation
    Le Wu1, Lei Chen1, Yonghui Yang1, Richang Hong1, Yong Ge2, Xing Xie3, Meng Wang1
    http://arxiv.org/abs/1906.00246v1

    • [cs.IR]Sequential Scenario-Specific Meta Learner for Online Recommendation
    Zhengxiao Du, Xiaowei Wang, Hongxia Yang, Jingren Zhou, Jie Tang
    http://arxiv.org/abs/1906.00391v1

    • [cs.IR]Technology Knowledge Graph Based on Patent Data
    Serhad Sarica, Jianxi Luo, Kristin L. Wood
    http://arxiv.org/abs/1906.00411v2

    • [cs.IR]Unsupervised Neural Generative Semantic Hashing
    Casper Hansen, Christian Hansen, Jakob Grue Simonsen, Stephen Alstrup, Christina Lioma
    http://arxiv.org/abs/1906.00671v1

    • [cs.IR]User Profile Feature-Based Approach to Address the Cold Start Problem in Collaborative Filtering for Personalized Movie Recommendation
    Lasitha Uyangoda, Supunmali Ahangama, Tharindu Ranasinghe
    http://arxiv.org/abs/1906.00365v1

    • [cs.IT]Closed-Form Analysis of Non-Linear Age-of-Information in Status Updates with an Energy Harvesting Transmitter
    Xi Zheng, Sheng Zhou, Zhiyuan Jiang, Zhisheng Niu
    http://arxiv.org/abs/1906.00192v1

    • [cs.IT]Cooperative Downlink Interference Transmission and Cancellation for Cellular-Connected UAV: A Divide-and-Conquer Approach
    Weidong Mei, Rui Zhang
    http://arxiv.org/abs/1906.00220v1

    • [cs.IT]Harvest-or-Transmit Policy for Cognitive Radio Networks: A Learning Theoretic Approach
    Kalpant Pathak, Adrish Banerjee
    http://arxiv.org/abs/1906.00548v1

    • [cs.IT]Multi-dimensional Spectral Super-Resolution with Prior Knowledge via Frequency-Selective Vandermonde Decomposition and ADMM
    Yinchuan Li, Xiaodong Wang, Zegang Ding
    http://arxiv.org/abs/1906.00278v1

    • [cs.IT]Performance Evaluation for the Co-existence of eMBB and URLLC Networks: Synchronized versus Unsynchronized TDD
    Ursula Challita, Kimmo Hiltunen, Miurel Tercero
    http://arxiv.org/abs/1906.00287v1

    • [cs.IT]Probabilistic Existence Results for Parent-Identifying Schemes
    Yujie Gu, Minquan Cheng, Grigory Kabatiansky, Ying Miao
    http://arxiv.org/abs/1906.01031v1

    • [cs.IT]The Classical Capacity of a Quantum Erasure Queue-Channel
    Prabha Mandayam, Krishna Jagannathan, Avhishek Chatterjee
    http://arxiv.org/abs/1906.01356v1

    • [cs.IT]Transmit Power Policy and Ergodic Multicast Rate Analysis of Cognitive Radio Networks in Generalized Fading
    Athira Subhash, Muralikrishnan Srinivasan, Sheetal Kalyani, Lajos Hanzo
    http://arxiv.org/abs/1906.00598v1

    • [cs.IT]Two Classes of New MDS Self-dual Codes over Finite Fields
    Xiaolei Fang, Jinquan Luo
    http://arxiv.org/abs/1906.00380v1

    • [cs.LG]A Case for Backward Compatibility for Human-AI Teams
    Gagan Bansal, Besmira Nushi, Ece Kamar, Dan Weld, Walter Lasecki, Eric Horvitz
    http://arxiv.org/abs/1906.01148v1

    • [cs.LG]A Fast-Optimal Guaranteed Algorithm For Learning Sub-Interval Relationships in Time Series
    Saurabh Agrawal, Saurabh Verma, Anuj Karpatne, Stefan Liess, Snigdhansu Chatterjee, Vipin Kumar
    http://arxiv.org/abs/1906.01450v1

    • [cs.LG]A Language-Agnostic Model for Semantic Source Code Labeling
    Ben Gelman, Bryan Hoyle, Jessica Moore, Joshua Saxe, David Slater
    http://arxiv.org/abs/1906.01032v1

    • [cs.LG]A Novel Hyperparameter-free Approach to Decision Tree Construction that Avoids Overfitting by Design
    Rafael Garcia Leiva, Antonio Fernandez Anta, Vincenzo Mancuso, Paolo Casari
    http://arxiv.org/abs/1906.01246v1

    • [cs.LG]A Perspective on Objects and Systematic Generalization in Model-Based RL
    Sjoerd van Steenkiste, Klaus Greff, Jürgen Schmidhuber
    http://arxiv.org/abs/1906.01035v1

    • [cs.LG]A Strong and Robust Baseline for Text-Image Matching
    Fangyu Liu, Rongtian Ye
    http://arxiv.org/abs/1906.01205v1

    • [cs.LG]A necessary and sufficient stability notion for adaptive generalization
    Katrina Ligett, Moshe Shenfeld
    http://arxiv.org/abs/1906.00930v1

    • [cs.LG]Achieving Fairness in Determining Medicaid Eligibility through Fairgroup Construction
    Boli Fang, Miao Jiang, Jerry Shen
    http://arxiv.org/abs/1906.00128v1

    • [cs.LG]Achieving Generalizable Robustness of Deep Neural Networks by Stability Training
    Jan Laermann, Wojciech Samek, Nils Strodthoff
    http://arxiv.org/abs/1906.00735v1

    • [cs.LG]Active Learning for Binary Classification with Abstention
    Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
    http://arxiv.org/abs/1906.00303v1

    • [cs.LG]Adaptive Online Learning for Gradient-Based Optimizers
    Saeed Masoudian, Ali Arabzadeh, Mahdi Jafari Siavoshani, Milad Jalal, Alireza Amouzad
    http://arxiv.org/abs/1906.00290v1

    • [cs.LG]Adversarial Exploitation of Policy Imitation
    Vahid Behzadan, William Hsu
    http://arxiv.org/abs/1906.01121v1

    • [cs.LG]Adversarial Risk Bounds for Neural Networks through Sparsity based Compression
    Emilio Rafael Balda, Arash Behboodi, Niklas Koep, Rudolf Mathar
    http://arxiv.org/abs/1906.00698v1

    • [cs.LG]Adversarial Training Generalizes Data-dependent Spectral Norm Regularization
    Kevin Roth, Yannic Kilcher, Thomas Hofmann
    http://arxiv.org/abs/1906.01527v1

    • [cs.LG]Adversarially Robust Generalization Just Requires More Unlabeled Data
    Runtian Zhai, Tianle Cai, Di He, Chen Dan, Kun He, John Hopcroft, Liwei Wang
    http://arxiv.org/abs/1906.00555v1

    • [cs.LG]An Adaptable Framework for Deep Adversarial Label Learning from Weak Supervision
    Chidubem Arachie, Bert Huang
    http://arxiv.org/abs/1906.00512v1

    • [cs.LG]An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem
    Chaitanya K. Joshi, Thomas Laurent, Xavier Bresson
    http://arxiv.org/abs/1906.01227v1

    • [cs.LG]An Empirical Study on Hyperparameters and their Interdependence for RL Generalization
    Xingyou Song, Yilun Du, Jacob Jackson
    http://arxiv.org/abs/1906.00431v1

    • [cs.LG]An interpretable machine learning framework for modelling human decision behavior
    Mengzhuo Guo, Qingpeng Zhang, Xiuwu Liao, Youhua Chen
    http://arxiv.org/abs/1906.01233v1

    • [cs.LG]Analysis and Improvement of Adversarial Training in DQN Agents With Adversarially-Guided Exploration (AGE)
    Vahid Behzadan, William Hsu
    http://arxiv.org/abs/1906.01119v1

    • [cs.LG]Approximation capability of neural networks on spaces of probability measures and tree-structured domains
    Tomas Pevny, Vojtech Kovarik
    http://arxiv.org/abs/1906.00764v1

    • [cs.LG]Architecture Selection via the Trade-off Between Accuracy and Robustness
    Zhun Deng, Cynthia Dwork, Jialiang Wang, Yao Zhao
    http://arxiv.org/abs/1906.01354v1

    • [cs.LG]Attributed Graph Clustering via Adaptive Graph Convolution
    Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu
    http://arxiv.org/abs/1906.01210v1

    • [cs.LG]Autonomous Reinforcement Learning of Multiple Interrelated Tasks
    Vieri Giuliano Santucci, Gianluca Baldassarre, Emilio Cartoni
    http://arxiv.org/abs/1906.01374v1

    • [cs.LG]Big-Data Clustering: K-Means or K-Indicators?
    Feiyu Chen, Yuchen Yang, Liwei Xu, Taiping Zhang, Yin Zhang
    http://arxiv.org/abs/1906.00938v1

    • [cs.LG]Biomedical Named Entity Recognition via Reference-Set Augmented Bootstrapping
    Joel Mathew, Shobeir Fakhraei, José Luis Ambite
    http://arxiv.org/abs/1906.00282v1

    • [cs.LG]Blow: a single-scale hyperconditioned flow for non-parallel raw-audio voice conversion
    Joan Serrà, Santiago Pascual, Carlos Segura
    http://arxiv.org/abs/1906.00794v1

    • [cs.LG]Breaking Inter-Layer Co-Adaptation by Classifier Anonymization
    Ikuro Sato, Kohta Ishikawa, Guoqing Liu, Masayuki Tanaka
    http://arxiv.org/abs/1906.01150v1

    • [cs.LG]C2P2: A Collective Cryptocurrency Up/Down Price Prediction Engine
    Chongyang Bai, Tommy White, Linda Xiao, V. S. Subrahmanian, Ziheng Zhou
    http://arxiv.org/abs/1906.00564v1

    • [cs.LG]Characterizing and Forecasting User Engagement with In-app Action Graph: A Case Study of Snapchat
    Yozen Liu, Xiaolin Shi, Lucas Pierce, Xiang Ren
    http://arxiv.org/abs/1906.00355v1

    • [cs.LG]Classification of Crop Tolerance to Heat and Drought: A Deep Convolutional Neural Networks Approach
    Saeed Khaki, Zahra Khalilzadeh
    http://arxiv.org/abs/1906.00454v1

    • [cs.LG]Clustering by Orthogonal NMF Model and Non-Convex Penalty Optimization
    Shuai Wang, Tsung-Hui Chang, Ying Cui, Jong-Shi Pang
    http://arxiv.org/abs/1906.00570v1

    • [cs.LG]Conditional Generative Models are not Robust
    Ethan Fetaya, Jörn-Henrik Jacobsen, Richard Zemel
    http://arxiv.org/abs/1906.01171v1

    • [cs.LG]Continual Learning of New Sound Classes using Generative Replay
    Zhepei Wang, Cem Subakan, Efthymios Tzinis, Paris Smaragdis, Laurent Charlin
    http://arxiv.org/abs/1906.00654v1

    • [cs.LG]Continual learning with hypernetworks
    Johannes von Oswald, Christian Henning, João Sacramento, Benjamin F. Grewe
    http://arxiv.org/abs/1906.00695v1

    • [cs.LG]Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification
    Harsh Shrivastava, Eugene Bart, Bob Price, Hanjun Dai, Bo Dai, Srinivas Aluru
    http://arxiv.org/abs/1906.00291v1

    • [cs.LG]Correctness Verification of Neural Networks
    Yichen Yang, Martin Rinard
    http://arxiv.org/abs/1906.01030v1

    • [cs.LG]Coupled VAE: Improved Accuracy and Robustness of a Variational Autoencoder
    Shichen Cao, Jingjing Li, Kenric P. Nelson, Mark A. Kon
    http://arxiv.org/abs/1906.00536v1

    • [cs.LG]DANE: Domain Adaptive Network Embedding
    Yizhou Zhang, Guojie Song, Lun Du, Shuwen Yang, Yilun Jin
    http://arxiv.org/abs/1906.00684v1

    • [cs.LG]Data Sampling for Graph Based Unsupervised Learning: Convex and Greedy Optimization
    Saeed Vahidian, Alexander Cloninger, Baharan Mirzasoleiman
    http://arxiv.org/abs/1906.01021v1

    • [cs.LG]Data-driven Estimation of Sinusoid Frequencies
    Gautier Izacard, Sreyas Mohan, Carlos Fernandez-Granda
    http://arxiv.org/abs/1906.00823v1

    • [cs.LG]Deep Reasoning Networks: Thinking Fast and Slow
    Di Chen, Yiwei Bai, Wenting Zhao, Sebastian Ament, John M. Gregoire, Carla P. Gomes
    http://arxiv.org/abs/1906.00855v2

    • [cs.LG]DiffQue: Estimating Relative Difficulty of Questions in Community Question Answering Services
    Deepak Thukral, Adesh Pandey, Rishabh Gupta, Vikram Goyal, Tanmoy Chakraborty
    http://arxiv.org/abs/1906.00145v1

    • [cs.LG]Dimensionality compression and expansion in Deep Neural Networks
    Stefano Recanatesi, Matthew Farrell, Madhu Advani, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown
    http://arxiv.org/abs/1906.00443v1

    • [cs.LG]Discovering Neural Wirings
    Mitchell Wortsman, Ali Farhadi, Mohammad Rastegari
    http://arxiv.org/abs/1906.00586v1

    • [cs.LG]Discriminative adversarial networks for positive-unlabeled learning
    Fangqing Liu, Hui Chen, Hao Wu
    http://arxiv.org/abs/1906.00642v1

    • [cs.LG]Disparate Vulnerability: on the Unfairness of Privacy Attacks Against Machine Learning
    Mohammad Yaghini, Bogdan Kulynych, Carmela Troncoso
    http://arxiv.org/abs/1906.00389v1

    • [cs.LG]Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards
    Anmol Kagrecha, Jayakrishnan Nair, Krishna Jagannathan
    http://arxiv.org/abs/1906.00569v1

    • [cs.LG]Do place cells dream of conditional probabilities? Learning Neural Nyström representations
    Mariano Tepper
    http://arxiv.org/abs/1906.01102v1

    • [cs.LG]Ease.ml/meter: Quantitative Overfitting Management for Human-in-the-loop ML Application Development
    Frances Ann Hubis, Wentao Wu, Ce Zhang
    http://arxiv.org/abs/1906.00299v2

    • [cs.LG]Embedded hyper-parameter tuning by Simulated Annealing
    Matteo Fischetti, Matteo Stringher
    http://arxiv.org/abs/1906.01504v1

    • [cs.LG]Encoder-Powered Generative Adversarial Networks
    Jiseob Kim, Seungjae Jung, Hyundo Lee, Byoung-Tak Zhang
    http://arxiv.org/abs/1906.00541v1

    • [cs.LG]Encoding Invariances in Deep Generative Models
    Viraj Shah, Ameya Joshi, Sambuddha Ghosal, Balaji Pokuri, Soumik Sarkar, Baskar Ganapathysubramanian, Chinmay Hegde
    http://arxiv.org/abs/1906.01626v1

    • [cs.LG]Enhancing Transformation-based Defenses using a Distribution Classifier
    Connie Kou, Hwee Kuan Lee, Teck Khim Ng, Ee-Chien Chang
    http://arxiv.org/abs/1906.00258v1

    • [cs.LG]Episodic Memory in Lifelong Language Learning
    Cyprien de Masson d’Autume, Sebastian Ruder, Lingpeng Kong, Dani Yogatama
    http://arxiv.org/abs/1906.01076v1

    • [cs.LG]Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision
    Fredrik K. Gustafsson, Martin Danelljan, Thomas B. Schön
    http://arxiv.org/abs/1906.01620v1

    • [cs.LG]Exact Combinatorial Optimization with Graph Convolutional Neural Networks
    Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, Andrea Lodi
    http://arxiv.org/abs/1906.01629v1

    • [cs.LG]Exact inference in structured prediction
    Kevin Bello, Jean Honorio
    http://arxiv.org/abs/1906.00451v1

    • [cs.LG]Factor Graph Neural Network
    Zhen Zhang, Fan Wu, Wee Sun Lee
    http://arxiv.org/abs/1906.00554v1

    • [cs.LG]Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models
    Paweł Morawiecki, Przemysław Spurek, Marek Śmieja, Jacek Tabor
    http://arxiv.org/abs/1906.00628v1

    • [cs.LG]Feature-Based Q-Learning for Two-Player Stochastic Games
    Zeyu Jia, Lin F. Yang, Mengdi Wang
    http://arxiv.org/abs/1906.00423v1

    • [cs.LG]Gated recurrent units viewed through the lens of continuous time dynamical systems
    Ian D. Jordan, Piotr Aleksander Sokol, Il Memming Park
    http://arxiv.org/abs/1906.01005v1

    • [cs.LG]Generating Diverse High-Fidelity Images with VQ-VAE-2
    Ali Razavi, Aaron van den Oord, Oriol Vinyals
    http://arxiv.org/abs/1906.00446v1

    • [cs.LG]Generative Adversarial Networks: A Survey and Taxonomy
    Zhengwei Wang, Qi She, Tomas E. Ward
    http://arxiv.org/abs/1906.01529v1

    • [cs.LG]Graduated Optimization of Black-Box Functions
    Weijia Shao, Christian Geißler, Fikret Sivrikaya
    http://arxiv.org/abs/1906.01279v1

    • [cs.LG]HERA: Partial Label Learning by Combining Heterogeneous Loss with Sparse and Low-Rank Regularization
    Gengyu Lyu, Songhe Feng, Yi Jin, Guojun Dai, Congyan Lang, Yidong Li
    http://arxiv.org/abs/1906.00551v1

    • [cs.LG]Hierarchical Auxiliary Learning
    Jaehoon Cha, Kyeong Soo Kim, Sanghyuk Lee
    http://arxiv.org/abs/1906.00852v1

    • [cs.LG]Implicit Regularization in Deep Matrix Factorization
    Sanjeev Arora, Nadav Cohen, Wei Hu, Yuping Luo
    http://arxiv.org/abs/1905.13655v2

    • [cs.LG]Information Competing Process for Learning Diversified Representations
    Jie Hu, Rongrong Ji, ShengChuan Zhang, Xiaoshuai Sun, Qixiang Ye, Chia-Wen Lin, Qi Tian
    http://arxiv.org/abs/1906.01288v1

    • [cs.LG]Inverse boosting pruning trees for depression detection on Twitter
    Lei Tong, Xiangrong, Qianni Zhang, Abdul Sadka, Ling Li, Huiyu Zhou
    http://arxiv.org/abs/1906.00398v1

    • [cs.LG]Kernel Instrumental Variable Regression
    Rahul Singh, Maneesh Sahani, Arthur Gretton
    http://arxiv.org/abs/1906.00232v1

    • [cs.LG]Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints
    Sebastian Tschiatschek, Ahana Ghosh, Luis Haug, Rati Devidze, Adish Singla
    http://arxiv.org/abs/1906.00429v1

    • [cs.LG]Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs
    Deepak Nathani, Jatin Chauhan, Charu Sharma, Manohar Kaul
    http://arxiv.org/abs/1906.01195v1

    • [cs.LG]Learning Domain Randomization Distributions for Transfer of Locomotion Policies
    Melissa Mozifian, Juan Camilo Gamboa Higuera, David Meger, Gregory Dudek
    http://arxiv.org/abs/1906.00410v1

    • [cs.LG]Learning Interpretable Shapelets for Time Series Classification through Adversarial Regularization
    Yichang Wang, Rémi Emonet, Elisa Fromont, Simon Malinowski, Etienne Menager, Loic Mosser, Romain Tavenard
    http://arxiv.org/abs/1906.00917v1

    • [cs.LG]Learning Representations by Maximizing Mutual Information Across Views
    Philip Bachman, R Devon Hjelm, William Buchwalter
    http://arxiv.org/abs/1906.00910v1

    • [cs.LG]Learning Transferable Cooperative Behavior in Multi-Agent Teams
    Akshat Agarwal, Sumit Kumar, Katia Sycara
    http://arxiv.org/abs/1906.01202v1

    • [cs.LG]Learning low-dimensional state embeddings and metastable clusters from time series data
    Yifan Sun, Yaqi Duan, Hao Gong, Mengdi Wang
    http://arxiv.org/abs/1906.00302v1

    • [cs.LG]Learning to Clear the Market
    Weiran Shen, Sébastien Lahaie, Renato Paes Leme
    http://arxiv.org/abs/1906.01184v1

    • [cs.LG]Load Balancing for Ultra-Dense Networks: A Deep Reinforcement Learning Based Approach
    Yue Xu, Wenjun Xu, Zhi Wang, Jiaru Lin, Shuguang Cui
    http://arxiv.org/abs/1906.00767v1

    • [cs.LG]Low-rank Random Tensor for Bilinear Pooling
    Yan Zhang, Krikamol Muandet, Qianli Ma, Heiko Neumann, Siyu Tang
    http://arxiv.org/abs/1906.01004v1

    • [cs.LG]Metric Learning for Individual Fairness
    Christina Ilvento
    http://arxiv.org/abs/1906.00250v1

    • [cs.LG]Minimax bounds for structured prediction
    Kevin Bello, Asish Ghoshal, Jean Honorio
    http://arxiv.org/abs/1906.00449v1

    • [cs.LG]Model selection for contextual bandits
    Dylan J. Foster, Akshay Krishnamurthy, Haipeng Luo
    http://arxiv.org/abs/1906.00531v1

    • [cs.LG]Modular Universal Reparameterization: Deep Multi-task Learning Across Diverse Domains
    Elliot Meyerson, Risto Miikkulainen
    http://arxiv.org/abs/1906.00097v1

    • [cs.LG]Near-Optimal Online Egalitarian learning in General Sum Repeated Matrix Games
    Aristide Tossou, Christos Dimitrakakis, Jaroslaw Rzepecki, Katja Hofmann
    http://arxiv.org/abs/1906.01609v1

    • [cs.LG]Nemesyst: A Hybrid Parallelism Deep Learning-Based Framework Applied for Internet of Things Enabled Food Retailing Refrigeration Systems
    George Onoufriou, Ronald Bickerton, Simon Pearson, Georgios Leontidis
    http://arxiv.org/abs/1906.01600v1

    • [cs.LG]Neural Network-based Object Classification by Known and Unknown Features (Based on Text Queries)
    A. Artemov, I. Bolokhov, D. Kem, I. Khasenevich
    http://arxiv.org/abs/1906.00800v1

    • [cs.LG]NeuralDivergence: Exploring and Understanding Neural Networks by Comparing Activation Distributions
    Haekyu Park, Fred Hohman, Duen Horng Chau
    http://arxiv.org/abs/1906.00332v1

    • [cs.LG]NodeDrop: A Condition for Reducing Network Size without Effect on Output
    Louis Jensen, Jacob Harer, Sang Chin
    http://arxiv.org/abs/1906.01026v1

    • [cs.LG]Nonstochastic Multiarmed Bandits with Unrestricted Delays
    Tobias Sommer Thune, Nicolò Cesa-Bianchi, Yevgeny Seldin
    http://arxiv.org/abs/1906.00670v1

    • [cs.LG]Off-Policy Evaluation via Off-Policy Classification
    Alex Irpan, Kanishka Rao, Konstantinos Bousmalis, Chris Harris, Julian Ibarz, Sergey Levine
    http://arxiv.org/abs/1906.01624v1

    • [cs.LG]On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems
    Tianyi Lin, Chi Jin, Michael I. Jordan
    http://arxiv.org/abs/1906.00331v1

    • [cs.LG]On Privacy Protection of Latent Dirichlet Allocation Model Training
    Fangyuan Zhao, Xuebin Ren, Shusen Yang, Xinyu Yang
    http://arxiv.org/abs/1906.01178v1

    • [cs.LG]On The Radon—Nikodym Spectral Approach With Optimal Clustering
    Vladislav Gennadievich Malyshkin
    http://arxiv.org/abs/1906.00460v1

    • [cs.LG]On the Correctness and Sample Complexity of Inverse Reinforcement Learning
    Abi Komanduru, Jean Honorio
    http://arxiv.org/abs/1906.00422v1

    • [cs.LG]On the computational complexity of the probabilistic label tree algorithms
    Robert Busa-Fekete, Krzysztof Dembczynski, Alexander Golovnev, Kalina Jasinska, Mikhail Kuznetsov, Maxim Sviridenko, Chao Xu
    http://arxiv.org/abs/1906.00294v1

    • [cs.LG]One-Way Prototypical Networks
    Anna Kruspe
    http://arxiv.org/abs/1906.00820v1

    • [cs.LG]Optimal Learning of Mallows Block Model
    Róbert Busa-Fekete, Dimitris Fotakis, Balázs Szörényi, Manolis Zampetakis
    http://arxiv.org/abs/1906.01009v1

    • [cs.LG]Optimal Transport on the Manifold of SPD Matrices for Domain Adaptation
    Or Yair, Felix Dietrich, Ronen Talmon, Ioannis G. Kevrekidis
    http://arxiv.org/abs/1906.00616v1

    • [cs.LG]Optimal Unsupervised Domain Translation
    Emmanuel de Bézenac, Ibrahim Ayed, Patrick Gallinari
    http://arxiv.org/abs/1906.01292v1

    • [cs.LG]Options as responses: Grounding behavioural hierarchies in multi-agent RL
    Alexander Sasha Vezhnevets, Yuhuai Wu, Remi Leblond, Joel Leibo
    http://arxiv.org/abs/1906.01470v1

    • [cs.LG]PCA-driven Hybrid network design for enabling Intelligence at the Edge
    Indranil Chakraborty, Deboleena Roy, Isha Garg, Aayush Ankit, Kaushik Roy
    http://arxiv.org/abs/1906.01493v1

    • [cs.LG]Posterior Variance Analysis of Gaussian Processes with Application to Average Learning Curves
    Armin Lederer, Jonas Umlauft, Sandra Hirche
    http://arxiv.org/abs/1906.01404v1

    • [cs.LG]Proximal Reliability Optimization for Reinforcement Learning
    Narendra Patwardhan, Zequn Wang
    http://arxiv.org/abs/1906.01127v1

    • [cs.LG]Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel
    Xin Qiu, Elliot Meyerson, Risto Miikkulainen
    http://arxiv.org/abs/1906.00588v1

    • [cs.LG]RL-Based Method for Benchmarking the Adversarial Resilience and Robustness of Deep Reinforcement Learning Policies
    Vahid Behzadan, William Hsu
    http://arxiv.org/abs/1906.01110v1

    • [cs.LG]Radial-Based Undersampling for Imbalanced Data Classification
    Michał Koziarski
    http://arxiv.org/abs/1906.00452v1

    • [cs.LG]Robust Learning Under Label Noise With Iterative Noise-Filtering
    Duc Tam Nguyen, Thi-Phuong-Nhung Ngo, Zhongyu Lou, Michael Klar, Laura Beggel, Thomas Brox
    http://arxiv.org/abs/1906.00216v1

    • [cs.LG]Self-supervised Body Image Acquisition Using a Deep Neural Network for Sensorimotor Prediction
    Alban Laflaquière, Verena V. Hafner
    http://arxiv.org/abs/1906.00825v1

    • [cs.LG]Sequential Triggers for Watermarking of Deep Reinforcement Learning Policies
    Vahid Behzadan, William Hsu
    http://arxiv.org/abs/1906.01126v1

    • [cs.LG]Sparse Representation Classification via Screening for Graphs
    Cencheng Shen, Li Chen, Yuexiao Dong, Carey Priebe
    http://arxiv.org/abs/1906.01601v1

    • [cs.LG]Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction
    Aviral Kumar, Justin Fu, George Tucker, Sergey Levine
    http://arxiv.org/abs/1906.00949v1

    • [cs.LG]Statistically Significant Discriminative Patterns Searching
    Hoang Son Pham, Gwendal Virlet, Dominique Lavenier, Alexandre Termier
    http://arxiv.org/abs/1906.01581v1

    • [cs.LG]Super-resolution of Time-series Labels for Bootstrapped Event Detection
    Ivan Kiskin, Udeepa Meepegama, Steven Roberts
    http://arxiv.org/abs/1906.00254v1

    • [cs.LG]Temporal Density Extrapolation using a Dynamic Basis Approach
    Georg Krempl, Dominik Lang, Vera Hofer
    http://arxiv.org/abs/1906.00912v1

    • [cs.LG]The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies
    Ronen Basri, David Jacobs, Yoni Kasten, Shira Kritchman
    http://arxiv.org/abs/1906.00425v1

    • [cs.LG]The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation
    Zhe Feng, David C. Parkes, Haifeng Xu
    http://arxiv.org/abs/1906.01528v1

    • [cs.LG]The Principle of Unchanged Optimality in Reinforcement Learning Generalization
    Alex Irpan, Xingyou Song
    http://arxiv.org/abs/1906.00336v1

    • [cs.LG]Topological Autoencoders
    Michael Moor, Max Horn, Bastian Rieck, Karsten Borgwardt
    http://arxiv.org/abs/1906.00722v1

    • [cs.LG]Toward Building Conversational Recommender Systems: A Contextual Bandit Approach
    Xiaoying Zhang, Hong Xie, Hang Li, John C. S. Lui
    http://arxiv.org/abs/1906.01219v1

    • [cs.LG]Towards Interactive Training of Non-Player Characters in Video Games
    Igor Borovikov, Jesse Harder, Michael Sadovsky, Ahmad Beirami
    http://arxiv.org/abs/1906.00535v1

    • [cs.LG]Truncated Cauchy Non-negative Matrix Factorization
    Naiyang Guan, Tongliang Liu, Yangmuzi Zhang, Dacheng Tao, Larry S. Davis
    http://arxiv.org/abs/1906.00495v1

    • [cs.LG]Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control
    Armin Lederer, Jonas Umlauft, Sandra Hirche
    http://arxiv.org/abs/1906.01376v1

    • [cs.LG]Unsupervised Emergence of Egocentric Spatial Structure from Sensorimotor Prediction
    Alban Laflaquière, Michael Garcia Ortiz
    http://arxiv.org/abs/1906.01401v1

    • [cs.LG]Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning
    Harm van Seijen, Mehdi Fatemi, Arash Tavakoli
    http://arxiv.org/abs/1906.00572v1

    • [cs.LG]Wasserstein Weisfeiler-Lehman Graph Kernels
    Matteo Togninalli, Elisabetta Ghisu, Felipe Llinares-López, Bastian Rieck, Karsten Borgwardt
    http://arxiv.org/abs/1906.01277v1

    • [cs.LG]Weakly Supervised Disentanglement by Pairwise Similarities
    Junxiang Chen, Kayhan Batmanghelich
    http://arxiv.org/abs/1906.01044v1

    • [cs.LG]Y-GAN: A Generative Adversarial Network for Depthmap Estimation from Multi-camera Stereo Images
    Miguel Alonso Jr
    http://arxiv.org/abs/1906.00932v1

    • [cs.LO]Reasoning about disclosure in data integration in the presence of source constraints
    Michael Benedikt, Pierre Bourhis, Louis Jachiet, Michaël Thomazo
    http://arxiv.org/abs/1906.00624v1

    • [cs.MA]Multiple Drones driven Hexagonally Partitioned Area Exploration: Simulation and Evaluation
    Ayush Datta, Rahul Tallamraju, Kamalakar Karlapalem
    http://arxiv.org/abs/1906.00401v1

    • [cs.NA]Learning Neural PDE Solvers with Convergence Guarantees
    Jun-Ting Hsieh, Shengjia Zhao, Stephan Eismann, Lucia Mirabella, Stefano Ermon
    http://arxiv.org/abs/1906.01200v1

    • [cs.NE]Hamiltonian Neural Networks
    Sam Greydanus, Misko Dzamba, Jason Yosinski
    http://arxiv.org/abs/1906.01563v1

    • [cs.NE]Kinetic Market Model: An Evolutionary Algorithm
    Evandro Luquini, Nizam Omar
    http://arxiv.org/abs/1906.01241v1

    • [cs.NE]Multi-objective Pruning for CNNs using Genetic Algorithm
    Chuanguang Yang, Zhulin An, Chao Li, Boyu Diao, Yongjun Xu
    http://arxiv.org/abs/1906.00399v1

    • [cs.NE]Neural networks grown and self-organized by noise
    Guruprasad Raghavan, Matt Thomson
    http://arxiv.org/abs/1906.01039v1

    • [cs.NE]Push and Pull Search Embedded in an M2M Framework for Solving Constrained Multi-objective Optimization Problems
    Zhun Fan, Zhaojun Wang, Wenji Li, Yutong Yuan, Yugen You, Zhi Yang, Fuzan Sun, Jie Ruan, Zhaocheng Li
    http://arxiv.org/abs/1906.00402v1

    • [cs.NE]SpikeGrad: An ANN-equivalent Computation Model for Implementing Backpropagation with Spikes
    Johannes Christian Thiele, Olivier Bichler, Antoine Dupret
    http://arxiv.org/abs/1906.00851v1

    • [cs.NE]Training Detection-Range-Frugal Cooperative Collision Avoidance Models for Quadcopters via Neuroevolution
    Amir Behjat, Krushang Gabani, Souma Chowdhury
    http://arxiv.org/abs/1906.00052v1

    • [cs.NI]Blockchain for Internet of Things: A Survey
    Hong-Ning Dai, Zibin Zheng, Yan Zhang
    http://arxiv.org/abs/1906.00245v1

    • [cs.NI]Cellular Traffic Prediction and Classification: a comparative evaluation of LSTM and ARIMA
    Amin Azari, Panagiotis Papapetrou, Stojan Denic, Gunnar Peters
    http://arxiv.org/abs/1906.00939v1

    • [cs.NI]On Provisioning Cellular Networks for Distributed Inference
    Sarabjot Singh
    http://arxiv.org/abs/1906.01602v1

    • [cs.NI]Probabilistic QoS-aware Placement of VNF chains at the Edge
    Antonio Brogi, Stefano Forti, Federica Paganelli
    http://arxiv.org/abs/1906.00197v1

    • [cs.OS]Cache Contention on Multicore Systems: An Ontology-based Approach
    Maruthi Rohit Ayyagari
    http://arxiv.org/abs/1906.00834v1

    • [cs.RO]Air Learning: An AI Research Platform for Algorithm-Hardware Benchmarking of Autonomous Aerial Robots
    Srivatsan Krishnan, Behzad Borojerdian, William Fu, Aleksandra Faust, Vijay Janapa Reddi
    http://arxiv.org/abs/1906.00421v1

    • [cs.RO]Analysis of Obstacle based Probabilistic RoadMap Method using Geometric Probability
    Titas Bera, M. Seetharama Bhat, Debasish Ghose
    http://arxiv.org/abs/1906.00136v1

    • [cs.RO]Closed-Loop Control of a Delta-Wing Unmanned Aerial-Aquatic Vehicle
    Joseph Moore
    http://arxiv.org/abs/1906.01532v1

    • [cs.RO]Effects of Different Hand-Grounding Locations on Haptic Performance With a Wearable Kinesthetic Haptic Device
    Sajid Nisar, Melisa Orta Martinez, Takahiro Endo, Fumitoshi Matsuno, Allison M. Okamura
    http://arxiv.org/abs/1906.00430v1

    • [cs.RO]GAMMA: A General Agent Motion Prediction Model for Autonomous Driving
    Yuanfu Luo, Panpan Cai
    http://arxiv.org/abs/1906.01566v1

    • [cs.RO]Grid-based Localization Stack for Inspection Drones towards Automation of Large Scale Warehouse Systems
    Ashwary Anand, Shubh Agrawal, Shivang Agrawal, Aman Chandra, Krishnakant Deshmukh
    http://arxiv.org/abs/1906.01299v1

    • [cs.RO]Harnessing Reinforcement Learning for Neural Motion Planning
    Tom Jurgenson, Aviv Tamar
    http://arxiv.org/abs/1906.00214v1

    • [cs.RO]Knowledge is Never Enough: Towards Web Aided Deep Open World Recognition
    Massimiliano Mancini, Hakan Karaoguz, Elisa Ricci, Patric Jensfelt, Barbara Caputo
    http://arxiv.org/abs/1906.01258v1

    • [cs.RO]Localization Requirements for Autonomous Vehicles
    Tyler G. R. Reid, Sarah E. Houts, Robert Cammarata, Graham Mills, Siddharth Agarwal, Ankit Vora, Gaurav Pandey
    http://arxiv.org/abs/1906.01061v1

    • [cs.RO]Longitudinal Trajectory Prediction of Human-driven Vehicles Near Traffic Lights
    Geunseob Oh, Huei Peng
    http://arxiv.org/abs/1906.00486v1

    • [cs.RO]Rapidly-Exploring Quotient-Space Trees: Motion Planning using Sequential Simplifications
    Andreas Orthey, Marc Toussaint
    http://arxiv.org/abs/1906.01350v1

    • [cs.RO]Socially Inspired Communication in Swarm Robotics
    Nathan White, John Harwell, Maria Gini
    http://arxiv.org/abs/1906.01108v1

    • [cs.RO]Vision-Based Autonomous UAV Navigation and Landing for Urban Search and Rescue
    Mayank Mittal, Rohit Mohan, Wolfram Burgard, Abhinav Valada
    http://arxiv.org/abs/1906.01304v1

    • [cs.SD]A Surprising Density of Illusionable Natural Speech
    Melody Y. Guan, Gregory Valiant
    http://arxiv.org/abs/1906.01040v1

    • [cs.SE]Gamification of Enterprise Systems: A Synthesis of Mechanics, Dynamics, and Risks
    M. Schmidt-Kraepelin, S. Lins, S. Thiebes, A. Sunyaev
    http://arxiv.org/abs/1906.01577v1

    • [cs.SE]Neural Bug Finding: A Study of Opportunities and Challenges
    Andrew Habib, Michael Pradel
    http://arxiv.org/abs/1906.00307v1

    • [cs.SI]Can Women Break the Glass Ceiling?: An Analysis of #MeToo Hashtagged Posts on Twitter
    Naeemul Hassan, Manash Kumar Mandal, Mansurul Bhuiyan, Aparna Moitra, Syed Ishtiaque Ahmed
    http://arxiv.org/abs/1906.00896v1

    • [cs.SI]Evaluating network partitions through visualization
    Chihiro Noguchi, Tatsuro Kawamoto
    http://arxiv.org/abs/1906.00699v2

    • [cs.SI]Implication Avoiding Dynamics for Externally Observed Networks
    Joel Nishimura, Oscar Goodloe
    http://arxiv.org/abs/1906.01118v1

    • [cs.SI]Need for Critical Cyber Defence, Security Strategy and Privacy Policy in Bangladesh - Hype or Reality?
    AKM Bahalul Haque
    http://arxiv.org/abs/1906.01285v1

    • [cs.SI]The Strength of Structural Diversity in Online Social Networks
    Yafei Zhang, Lin Wang, Jonathan J. H. Zhu, Xiaofan Wang, Alex ‘Sandy’ Pentland
    http://arxiv.org/abs/1906.00756v1

    • [cs.SI]Understanding the Silence of Sexual Harassment Victims Through the #WhyIDidntReport Movement
    Abigail Garrett, Naeemul Hassan
    http://arxiv.org/abs/1906.00895v1

    • [cs.SY]Robust stability of moving horizon estimation for nonlinear systems with bounded disturbances using adaptive arrival cost
    Nestor N. Deniz, Marina H. Murillo, Guido Sanchez, Lucas M. Genzelis, Leonardo Giovanini
    http://arxiv.org/abs/1906.01060v1

    • [eess.AS]Evaluating Non-aligned Musical Score Transcriptions with MV2H
    Andrew McLeod
    http://arxiv.org/abs/1906.00566v1

    • [eess.AS]MelNet: A Generative Model for Audio in the Frequency Domain
    Sean Vasquez, Mike Lewis
    http://arxiv.org/abs/1906.01083v1

    • [eess.IV]A Semantic-based Medical Image Fusion Approach
    Fanda Fan, Yunyou Huang, Lei Wang, Xingwang Xiong, Zihan Jiang, Zhifei Zhang, Jianfeng Zhan
    http://arxiv.org/abs/1906.00225v1

    • [eess.IV]Deep Feature Learning from a Hospital-Scale Chest X-ray Dataset with Application to TB Detection on a Small-Scale Dataset
    Ophir Gozes, Hayit Greenspan
    http://arxiv.org/abs/1906.00768v1

    • [eess.IV]Learning Deep Image Priors for Blind Image Denoising
    Xianxu Hou, Hongming Luo, Jingxin Liu, Bolei Xu, Ke Sun, Yuanhao Gong, Bozhi Liu, Guoping Qiu
    http://arxiv.org/abs/1906.01259v1

    • [eess.IV]Lung cancer screening with low-dose CT scans using a deep learning approach
    Jason L. Causey, Yuanfang Guan, Wei Dong, Karl Walker, Jake A. Qualls, Fred Prior, Xiuzhen Huang
    http://arxiv.org/abs/1906.00240v1

    • [eess.IV]Natural Image Noise Dataset
    Benoit Brummer, Christophe De Vleeschouwer
    http://arxiv.org/abs/1906.00270v1

    • [eess.IV]Probabilistic Noise2Void: Unsupervised Content-Aware Denoising
    Alexander Krull, Tomas Vicar, Florian Jug
    http://arxiv.org/abs/1906.00651v2

    • [eess.SP]A Nonlinear Acceleration Method for Iterative Algorithms
    Mahdi Shamsi, Mahmoud Ghandi, Farokh Marvasti
    http://arxiv.org/abs/1906.01595v1

    • [eess.SP]Deep Reinforcement Learning Architecture for Continuous Power Allocation in High Throughput Satellites
    Juan Jose Garau Luis, Markus Guerster, Inigo del Portillo, Edward Crawley, Bruce Cameron
    http://arxiv.org/abs/1906.00571v1

    • [eess.SP]Deterministic and stochastic damage detection via dynamic response analysis
    Michael Oberguggenberger, Martin Schwarz
    http://arxiv.org/abs/1906.00797v1

    • [eess.SP]Gridless Variational Bayesian Channel Estimation for Antenna Array Systems with Low Resolution ADCs
    Jiang Zhu, Chao-kai Wen, Jun Tong, Chongbin Xu, Shi Jin
    http://arxiv.org/abs/1906.00576v1

    • [eess.SP]Sparse Bayesian Learning Approach for Discrete Signal Reconstruction
    Jisheng Dai, An Liu, Hing Cheung So
    http://arxiv.org/abs/1906.00309v1

    • [eess.SP]What, Where and How to Transfer in SAR Target Recognition Based on Deep CNNs
    Zhongling Huang, Zongxu Pan, Bin Lei
    http://arxiv.org/abs/1906.01379v1

    • [hep-ph]Effective LHC measurements with matrix elements and machine learning
    Johann Brehmer, Kyle Cranmer, Irina Espejo, Felix Kling, Gilles Louppe, Juan Pavez
    http://arxiv.org/abs/1906.01578v1

    • [math.AT]A numerical measure of the instability of Mapper-type algorithms
    Francisco Belchí, Jacek Brodzki, Matthew Burfitt, Mahesan Niranjan
    http://arxiv.org/abs/1906.01507v1

    • [math.DG]Optimal transport and information geometry
    Ting-Kam Leonard Wong, Jiaowen Yang
    http://arxiv.org/abs/1906.00030v1

    • [math.NA]Exploiting nested task-parallelism in the $\mathcal{H}-LU$ factorization
    Rocío Carratalá-Sáez, Sven Christophersen, José I. Aliaga, Vicenç Beltran, Steffen Börm, Enrique S. Quintana-Ortí
    http://arxiv.org/abs/1906.00874v1

    • [math.OC]A Generic Acceleration Framework for Stochastic Composite Optimization
    Andrei Kulunchakov, Julien Mairal
    http://arxiv.org/abs/1906.01164v1

    • [math.OC]Adaptive Model Refinement with Batch Bayesian Sampling for Optimization of Bio-inspired Flow Tailoring
    Payam Ghassemi, Sumeet Sanjay Lulekar, Souma Chowdhury
    http://arxiv.org/abs/1906.00793v1

    • [math.OC]Data-Pooling in Stochastic Optimization
    Vishal Gupta, Nathan Kallus
    http://arxiv.org/abs/1906.00255v1

    • [math.OC]Generalized Momentum-Based Methods: A Hamiltonian Perspective
    Jelena Diakonikolas, Michael I. Jordan
    http://arxiv.org/abs/1906.00436v1

    • [math.OC]Higher-Order Accelerated Methods for Faster Non-Smooth Optimization
    Brian Bullins, Richard Peng
    http://arxiv.org/abs/1906.01621v1

    • [math.OC]Proximal Point Approximations Achieving a Convergence Rate of $\mathcal{O}(1/k)$ for Smooth Convex-Concave Saddle Point Problems: Optimistic Gradient and Extra-gradient Methods
    Aryan Mokhtari, Asuman Ozdaglar, Sarath Pattathil
    http://arxiv.org/abs/1906.01115v1

    • [math.OC]Robust exploration in linear quadratic reinforcement learning
    Jack Umenberger, Mina Ferizbegovic, Thomas B. Schön, Håkan Hjalmarsson
    http://arxiv.org/abs/1906.01584v1

    • [math.OC]Towards Unified Acceleration of High-Order Algorithms under Hölder Continuity and Uniform Convexity
    Chaobing Song, Yi Ma
    http://arxiv.org/abs/1906.00582v1

    • [math.ST]A mean-field limit for certain deep neural networks
    Dyego Araújo, Roberto I. Oliveira, Daniel Yukimura
    http://arxiv.org/abs/1906.00193v1

    • [math.ST]A test against trend in random sequences
    Peter Lindqvist
    http://arxiv.org/abs/1906.00752v1

    • [math.ST]Asymptotic Properties of Neural Network Sieve Estimators
    Xiaoxi Shen, Chang Jiang, Lyudmila Sakhanenko, Qing Lu
    http://arxiv.org/abs/1906.00875v1

    • [math.ST]Confidence Regions in Wasserstein Distributionally Robust Estimation
    Jose Blanchet, Karthyek Murthy, Nian Si
    http://arxiv.org/abs/1906.01614v1

    • [math.ST]How many variables should be entered in a principal component regression equation?
    Ji Xu, Daniel Hsu
    http://arxiv.org/abs/1906.01139v1

    • [math.ST]Inference robust to outliers with l1-norm penalization
    Jad Beyhum
    http://arxiv.org/abs/1906.01302v1

    • [math.ST]Multi-reference factor analysis: low-rank covariance estimation under unknown translations
    Boris Landa, Yoel Shkolnisky
    http://arxiv.org/abs/1906.00211v1

    • [math.ST]On Testing for Parameters in Ising Models
    Rajarshi Mukherjee, Gourab Ray
    http://arxiv.org/abs/1906.00456v1

    • [math.ST]Robust Mean Estimation with the Bayesian Median of Means
    Paulo Orenstein
    http://arxiv.org/abs/1906.01204v1

    • [math.ST]Semiparametric Analysis of the Proportional Likelihood Ratio Model and Omnibus Estimation Procedure
    Yair Goldberg, Malka Gorfine
    http://arxiv.org/abs/1906.00723v1

    • [physics.comp-ph]A new nonlocal forward model for diffuse optical tomography
    Wenqi Lu, Jinming Duan, Joshua Deepak Veesa, Iain B. Styles
    http://arxiv.org/abs/1906.00882v1

    • [physics.data-an]Revision of ISO 19229 to support the certification of calibration gases for purity
    Adriaan M. H. van der Veen, Gerard Nieuwenkamp
    http://arxiv.org/abs/1906.01216v1

    • [q-bio.NC]A detailed study of recurrent neural networks used to model tasks in the cerebral cortex
    C. Jarne, R. Laje
    http://arxiv.org/abs/1906.01094v1

    • [q-bio.NC]Learning to solve the credit assignment problem
    Benjamin James Lansdell, Prashanth Prakash, Konrad Paul Kording
    http://arxiv.org/abs/1906.00889v1

    • [q-bio.NC]Signal Coding and Perfect Reconstruction using Spike Trains
    Anik Chattopadhyay, Arunava Banerjee
    http://arxiv.org/abs/1906.00092v1

    • [q-fin.ST]Conditional inference on the asset with maximum Sharpe ratio
    Steven E. Pav
    http://arxiv.org/abs/1906.00573v1

    • [stat.AP]A Dyadic IRT Model
    Brian Gin, Nicholas Sim, Anders Skrondal, Sophia Rabe-Hesketh
    http://arxiv.org/abs/1906.01100v1

    • [stat.AP]Encouraging Equitable Bikeshare: Implications of Docked and Dockless Models for Spatial Equity
    Simon Couch, Heather Kitada Smalley
    http://arxiv.org/abs/1906.00129v1

    • [stat.AP]Generalised linear models for prognosis and intervention: Theory, practice, and implications for machine learning
    Kellyn F. Arnold, Vinny Davies, Marc de Kamps, Peter W. G. Tennant, John Mbotwa, Mark S. Gilthorpe
    http://arxiv.org/abs/1906.01461v1

    • [stat.AP]Joint spatial modeling of significant wave height and wave period using the SPDE approach
    Anders Hildeman, David Bolin, Igor Rychlik
    http://arxiv.org/abs/1906.00286v1

    • [stat.AP]Model Trees for Personalization
    Ali Aouad, Adam N. Elmachtoub, Kris J. Ferreira, Ryan McNellis
    http://arxiv.org/abs/1906.01174v1

    • [stat.AP]Statistical analysis of the water level of Huang He river (Yellow river) in China
    Wang Bo, Zlatinka I. Dimitrova, Nikolay K. Vitanov
    http://arxiv.org/abs/1906.00168v1

    • [stat.AP]Stress Testing Network Reconstruction via Graphical Causal Mode
    Helder Rojas, David Dias
    http://arxiv.org/abs/1906.01468v1

    • [stat.CO]lspartition: Partitioning-Based Least Squares Regression
    Matias D. Cattaneo, Max H. Farrell, Yingjie Feng
    http://arxiv.org/abs/1906.00202v1

    • [stat.CO]nprobust: Nonparametric Kernel-Based Estimation and Robust Bias-Corrected Inference
    Sebastian Calonico, Matias D. Cattaneo, Max H. Farrell
    http://arxiv.org/abs/1906.00198v1

    • [stat.ME]Anchored Causal Inference in the Presence of Measurement Error
    Basil Saeed, Anastasiya Belyaeva, Yuhao Wang, Caroline Uhler
    http://arxiv.org/abs/1906.00928v1

    • [stat.ME]Bayesian Profiling Multiple Imputation for Missing Electronic Health Records
    Yajuan Si, Mari Palta, Maureen Smith
    http://arxiv.org/abs/1906.00042v1

    • [stat.ME]Central Quantile Subspace
    Eliana Christou
    http://arxiv.org/abs/1906.00694v1

    • [stat.ME]Clustering Multivariate Data using Factor Analytic Bayesian Mixtures with an Unknown Number of Components
    Panagiotis Papastamoulis
    http://arxiv.org/abs/1906.00348v1

    • [stat.ME]Combining Heterogeneous Spatial Datasets with Process-based Spatial Fusion Models: A Unifying Framework
    Craig Wang, Reinhard Furrer
    http://arxiv.org/abs/1906.00364v1

    • [stat.ME]Comprehensive cluster validity Index based on structural simplicity
    Anri Mutoh, Masamichi Wada, Kou Amano
    http://arxiv.org/abs/1906.00349v1

    • [stat.ME]Confidence Intervals for Selected Parameters
    Yoav Benjamini, Yotam Hechtlinger, Philip B. Stark
    http://arxiv.org/abs/1906.00505v1

    • [stat.ME]Copula-based functional Bayes classification with principal components and partial least squares
    Wentian Huang, David Ruppert
    http://arxiv.org/abs/1906.00538v1

    • [stat.ME]Covariate-Powered Empirical Bayes Estimation
    Nikolaos Ignatiadis, Stefan Wager
    http://arxiv.org/abs/1906.01611v1

    • [stat.ME]Diagonally-Dominant Principal Component Analysis
    Zheng Tracy Ke, Lingzhou Xue, Fan Yang
    http://arxiv.org/abs/1906.00051v1

    • [stat.ME]Estimating Real Log Canonical Thresholds
    Toru Imai
    http://arxiv.org/abs/1906.01341v1

    • [stat.ME]Estimating Time-Varying Causal Excursion Effect in Mobile Health with Binary Outcomes
    Tianchen Qian, Hyesun Yoo, Predrag Klasnja, Daniel Almirall, Susan A. Murphy
    http://arxiv.org/abs/1906.00528v1

    • [stat.ME]Functional time series prediction under partial observation of the future curve
    Shuhao Jiao
    http://arxiv.org/abs/1906.00281v1

    • [stat.ME]Gap-Measure Tests with Applications to Data Integrity Verification
    Truc Le, Jeffrey Uhlmann
    http://arxiv.org/abs/1906.01465v1

    • [stat.ME]Generating Poisson-Distributed Differentially Private Synthetic Data
    Harrison Quick
    http://arxiv.org/abs/1906.00455v1

    • [stat.ME]Kernel Mean Embedding Based Hypothesis Tests for Comparing Spatial Point Patterns
    Raif M. Rustamov, James T. Klosowski
    http://arxiv.org/abs/1906.00116v1

    • [stat.ME]Mixture of hidden Markov models for accelerometer data
    Marie du Roy de Chaumaray, Matthieu Marbac, Fabien Navarro
    http://arxiv.org/abs/1906.01547v1

    • [stat.ME]Multiplicative Effect Modeling: The General Case
    Jiaqi Yin, Thomas S. Richardson, Linbo Wang
    http://arxiv.org/abs/1906.00558v1

    • [stat.ME]Partial and semi-partial measures of spatial associations for multivariate lattice data
    Matthias Eckardt, Jorge Mateu
    http://arxiv.org/abs/1906.01484v1

    • [stat.ME]Semi-parametric Bayesian variable selection for gene-environment interactions
    Jie Ren, Fei Zhou, Xiaoxi Li, Qi Chen, Hongmei Zhang, Shuangge Ma, Yu Jiang, Cen Wu
    http://arxiv.org/abs/1906.01057v1

    • [stat.ME]Statistical methods for biomarker data pooled from multiple nested case-control studies
    Abigail Sloan, Molin Wang
    http://arxiv.org/abs/1906.00818v1

    • [stat.ME]The performance of the partially overlapping samples t-tests at the limits
    Ben Derrick, Deirdre Toher, Paul White
    http://arxiv.org/abs/1906.01006v1

    • [stat.ME]Transformed Central Quantile Subspace
    Eliana Christou
    http://arxiv.org/abs/1906.00696v1

    • [stat.ME]Unconstrained representation of orthogonal matrices with application to common principle components
    Luca Bagnato, Antonio Punzo
    http://arxiv.org/abs/1906.00587v1

    • [stat.ML]A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off
    Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry
    http://arxiv.org/abs/1906.00771v1

    • [stat.ML]An Evaluation Toolkit to Guide Model Selection and Cohort Definition in Causal Inference
    Yishai Shimoni, Ehud Karavani, Sivan Ravid, Peter Bak, Tan Hung Ng, Sharon Hensley Alford, Denise Meade, Yaara Goldschmidt
    http://arxiv.org/abs/1906.00442v1

    • [stat.ML]Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination
    Nathan Kallus, Xiaojie Mao, Angela Zhou
    http://arxiv.org/abs/1906.00285v1

    • [stat.ML]Assessing Disparate Impacts of Personalized Interventions: Identifiability and Bounds
    Nathan Kallus, Angela Zhou
    http://arxiv.org/abs/1906.01552v1

    • [stat.ML]Bayesian Optimization of Composite Functions
    Raul Astudillo, Peter I. Frazier
    http://arxiv.org/abs/1906.01537v1

    • [stat.ML]Bayesian Prior Networks with PAC Training
    Manuel Haussmann, Sebastian Gerwinn, Melih Kandemir
    http://arxiv.org/abs/1906.00816v1

    • [stat.ML]BreGMN: scaled-Bregman Generative Modeling Networks
    Akash Srivastava, Kristjan Greenewald, Farzaneh Mirzazadeh
    http://arxiv.org/abs/1906.00313v1

    • [stat.ML]Capabilities and Limitations of Time-lagged Autoencoders for Slow Mode Discovery in Dynamical Systems
    Wei Chen, Hythem Sidky, Andrew L. Ferguson
    http://arxiv.org/abs/1906.00325v1

    • [stat.ML]Concept Tree: High-Level Representation of Variables for More Interpretable Surrogate Decision Trees
    Xavier Renard, Nicolas Woloszko, Jonathan Aigrain, Marcin Detyniecki
    http://arxiv.org/abs/1906.01297v1

    • [stat.ML]Deep ReLU Networks Have Surprisingly Few Activation Patterns
    Boris Hanin, David Rolnick
    http://arxiv.org/abs/1906.00904v1

    • [stat.ML]GANchors: Realistic Image Perturbation Distributions for Anchors Using Generative Models
    Kurtis Evan David, Harrison Keane, Jun Min Noh
    http://arxiv.org/abs/1906.00297v1

    • [stat.ML]Graphon Estimation from Partially Observed Network Data
    Soumendu Sundar Mukherjee, Sayak Chakrabarti
    http://arxiv.org/abs/1906.00494v1

    • [stat.ML]Hybrid Machine Learning Forecasts for the FIFA Women’s World Cup 2019
    Andreas Groll, Christophe Ley, Gunther Schauberger, Hans Van Eetvelde, Achim Zeileis
    http://arxiv.org/abs/1906.01131v1

    • [stat.ML]Learning Perceptually-Aligned Representations via Adversarial Robustness
    Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Aleksander Madry
    http://arxiv.org/abs/1906.00945v1

    • [stat.ML]MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning
    Diego Granziol, Binxin Ru, Stefan Zohren, Xiaowen Doing, Michael Osborne, Stephen Roberts
    http://arxiv.org/abs/1906.01101v1

    • [stat.ML]MaxGap Bandit: Adaptive Algorithms for Approximate Ranking
    Sumeet Katariya, Ardhendu Tripathy, Robert Nowak
    http://arxiv.org/abs/1906.00547v1

    • [stat.ML]Nonparametric Functional Approximation with Delaunay Triangulation
    Yehong Liu, Guosheng Yin
    http://arxiv.org/abs/1906.00350v1

    • [stat.ML]Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement
    Ming Lin, Xiaomin Song, Qi Qian, Hao Li, Liang Sun, Shenghuo Zhu, Rong Jin
    http://arxiv.org/abs/1906.01095v1

    • [stat.ML]Robust approximate linear regression without correspondence
    Erdem Varol, Amin Nejatbakhsh
    http://arxiv.org/abs/1906.00273v1

    • [stat.ML]Separable Layers Enable Structured Efficient Linear Substitutions
    Gavin Gray, Elliot J. Crowley, Amos Storkey
    http://arxiv.org/abs/1906.00859v1

    • [stat.ML]Streaming Variational Monte Carlo
    Yuan Zhao, Josue Nassar, Ian Jordan, Mónica Bugallo, Il Memming Park
    http://arxiv.org/abs/1906.01549v1

    • [stat.ML]Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules
    Niklas W. A. Gebauer, Michael Gastegger, Kristof T. Schütt
    http://arxiv.org/abs/1906.00957v1

    • [stat.ML]Tensor Restricted Isometry Property Analysis For a Large Class of Random Measurement Ensembles
    Feng Zhang, Wendong Wang, Jingyao Hou, Jianjun Wang, Jianwen Huang
    http://arxiv.org/abs/1906.01198v1

    • [stat.ML]The Extended Dawid-Skene Model: Fusing Information from Multiple Data Schemas
    Michael P. J. Camilleri, Christopher K. I. Williams
    http://arxiv.org/abs/1906.01251v1

    • [stat.ML]Towards Task and Architecture-Independent Generalization Gap Predictors
    Scott Yak, Javier Gonzalvo, Hanna Mazzawi
    http://arxiv.org/abs/1906.01550v1

    • [stat.ML]Universal Boosting Variational Inference
    Trevor Campbell, Xinglong Li
    http://arxiv.org/abs/1906.01235v1

    • [stat.ML]What do AI algorithms actually learn? - On false structures in deep learning
    Laura Thesing, Vegard Antun, Anders C. Hansen
    http://arxiv.org/abs/1906.01478v1