cond-mat.dis-nn - 无序系统与神经网络

    cs.AI - 人工智能 cs.AR - 硬件体系结构 cs.CG - 计算几何学 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DC - 分布式、并行与集群计算 cs.DL - 数字图书馆 cs.ET - 新兴技术 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.MA - 多代理系统 cs.MM - 多媒体 cs.MS - 数学软件 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.HO - 历史与概述 math.NA - 数值分析 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.chem-ph -化学物理 physics.soc-ph - 物理学与社会 q-bio.BM - 生物分子 q-bio.NC - 神经元与认知 q-bio.QM - 定量方法 q-fin.ST - 统计金融学 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cond-mat.dis-nn]Rate Distortion Theorem and the Multicritical Point of Spin Glass
    • [cs.AI]An Empirical Evaluation of Two General Game Systems: Ludii and RBG
    • [cs.AI]An Overview of the Ludii General Game System
    • [cs.AI]Analysis of the Synergy between Modularity and Autonomy in an Artificial Intelligence Based Fleet Competition
    • [cs.AI]Elementary Iterated Revision and the Levi Identity
    • [cs.AI]Investigating The Piece-Wise Linearity And Benchmark Related To Koczy-Hirota Fuzzy Linear Interpolation
    • [cs.AI]Knowledge Graph Embedding for Ecotoxicological Effect Prediction
    • [cs.AI]Ludii and XCSP: Playing and Solving Logic Puzzles
    • [cs.AI]Ludii as a Competition Platform
    • [cs.AI]Neural Network Verification for the Masses (of AI graduates)
    • [cs.AI]Reinforcement Learning with Fairness Constraints for Resource Distribution in Human-Robot Teams
    • [cs.AI]Requisite Variety in Ethical Utility Functions for AI Value Alignment
    • [cs.AI]Visual analytics for team-based invasion sports with significant events and Markov reward process
    • [cs.AR]On the Optimal Refresh Power Allocation for Energy-Efficient Memories
    • [cs.CG]Exploring Feasible Design Spaces for Heterogeneous Constraints
    • [cs.CL]A Neural Grammatical Error Correction System Built On Better Pre-training and Sequential Transfer Learning
    • [cs.CL]A Novel Bi-directional Interrelated Model for Joint Intent Detection and Slot Filling
    • [cs.CL]Analyzing Utility of Visual Context in Multimodal Speech Recognition Under Noisy Conditions
    • [cs.CL]Claim Extraction in Biomedical Publications using Deep Discourse Model and Transfer Learning
    • [cs.CL]Constructing large scale biomedical knowledge bases from scratch with rapid annotation of interpretable patterns
    • [cs.CL]Contextual Phonetic Pretraining for End-to-end Utterance-level Language and Speaker Recognition
    • [cs.CL]Cooperative Generator-Discriminator Networks for Abstractive Summarization with Narrative Flow
    • [cs.CL]Danish Stance Classification and Rumour Resolution
    • [cs.CL]Do Transformer Attention Heads Provide Transparency in Abstractive Summarization?
    • [cs.CL]EGG: a toolkit for research on Emergence of lanGuage in Games
    • [cs.CL]Empirical Evaluation of Sequence-to-Sequence Models for Word Discovery in Low-resource Settings
    • [cs.CL]Evaluating Language Model Finetuning Techniques for Low-resource Languages
    • [cs.CL]Fake News Detection using Stance Classification: A Survey
    • [cs.CL]Few-Shot Representation Learning for Out-Of-Vocabulary Words
    • [cs.CL]GPT-based Generation for Classical Chinese Poetry
    • [cs.CL]How we do things with words: Analyzing text as social and cultural data
    • [cs.CL]HyST: A Hybrid Approach for Flexible and Accurate Dialogue State Tracking
    • [cs.CL]Improving Robustness in Real-World Neural Machine Translation Engines
    • [cs.CL]Inter and Intra Document Attention for Depression Risk Assessment
    • [cs.CL]Is artificial data useful for biomedical Natural Language Processing
    • [cs.CL]Katecheo: A Portable and Modular System for Multi-Topic Question Answering
    • [cs.CL]Latent Dirichlet Allocation Based Acoustic Data Selection for Automatic Speech Recognition
    • [cs.CL]Latent Variable Sentiment Grammar
    • [cs.CL]Leveraging Acoustic Cues and Paralinguistic Embeddings to Detect Expression from Voice
    • [cs.CL]Merge and Label: A novel neural network architecture for nested NER
    • [cs.CL]Modernizing Historical Documents: a User Study
    • [cs.CL]Multilingual Bottleneck Features for Query by Example Spoken Term Detection
    • [cs.CL]Multilingual, Multi-scale and Multi-layer Visualization of Intermediate Representations
    • [cs.CL]Multimodal Transformer Networks for End-to-End Video-Grounded Dialogue Systems
    • [cs.CL]Natural Language Understanding with the Quora Question Pairs Dataset
    • [cs.CL]Neural Machine Reading Comprehension: Methods and Trends
    • [cs.CL]Observing Dialogue in Therapy: Categorizing and Forecasting Behavioral Codes
    • [cs.CL]Post-editese: an Exacerbated Translationese
    • [cs.CL]Self-Supervised Dialogue Learning
    • [cs.CL]Sequence Labeling Parsing by Learning Across Representations
    • [cs.CL]Synchronising audio and ultrasound by learning cross-modal embeddings
    • [cs.CL]The CUED’s Grammatical Error Correction Systems for BEA-2019
    • [cs.CL]The University of Sydney’s Machine Translation System for WMT19
    • [cs.CL]Topic Modeling the Reading and Writing Behavior of Information Foragers
    • [cs.CL]UltraSuite: A Repository of Ultrasound and Acoustic Data from Child Speech Therapy Sessions
    • [cs.CL]Using Database Rule for Weak Supervised Text-to-SQL Generation
    • [cs.CL]Weak Supervision Enhanced Generative Network for Question Generation
    • [cs.CR]An Enhanced Electrocardiogram Biometric Authentication System Using Machine Learning
    • [cs.CR]Collecting and Analyzing Multidimensional Data with Local Differential Privacy
    • [cs.CR]Fooling a Real Car with Adversarial Traffic Signs
    • [cs.CR]Machine Learning for Intelligent Authentication in 5G-and-Beyond Wireless Networks
    • [cs.CR]Methodology for the Automated Metadata-Based Classification of Incriminating Digital Forensic Artefacts
    • [cs.CR]Secure Mobile Technologies for Proactive Critical Infrastructure Situational Awareness
    • [cs.CR]Taint analysis of the Bitcoin network
    • [cs.CV]A Closest Point Proposal for MCMC-based Probabilistic Surface Registration
    • [cs.CV]A Single Video Super-Resolution GAN for Multiple Downsampling Operators based on Pseudo-Inverse Image Formation Models
    • [cs.CV]Adversarially Trained Deep Neural Semantic Hashing Scheme for Subjective Search in Fashion Inventory
    • [cs.CV]An Analysis of Deep Neural Networks with Attention for Action Recognition from a Neurophysiological Perspective
    • [cs.CV]An End-to-End Neural Network for Image Cropping by Learning Composition from Aesthetic Photos
    • [cs.CV]An Integrated Image Filter for Enhancing Change Detection Results
    • [cs.CV]Associative Embedding for Game-Agnostic Team Discrimination
    • [cs.CV]Attribute-Driven Spontaneous Motion in Unpaired Image Translation
    • [cs.CV]Brno Mobile OCR Dataset
    • [cs.CV]CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark
    • [cs.CV]CSSegNet: Fine-Grained Cardiac Structures Segmentation Using Dilated Pyramid Pooling in U-net
    • [cs.CV]Cross-view Relation Networks for Mammogram Mass Detection
    • [cs.CV]DeepTEGINN: Deep Learning Based Tools to Extract Graphs from Images of Neural Networks
    • [cs.CV]Difficulty-aware Meta-Learning for Rare Disease Diagnosis
    • [cs.CV]Diminishing the Effect of Adversarial Perturbations via Refining Feature Representation
    • [cs.CV]Disentangled Makeup Transfer with Generative Adversarial Network
    • [cs.CV]Dynamic Face Video Segmentation via Reinforcement Learning
    • [cs.CV]Estimating brain age based on a healthy population with deep learning and structural MRI
    • [cs.CV]FastDVDnet: Towards Real-Time Video Denoising Without Explicit Motion Estimation
    • [cs.CV]Generative Guiding Block: Synthesizing Realistic Looking Variants Capable of Even Large Change Demands
    • [cs.CV]Going Deeper with Point Networks
    • [cs.CV]HO-3D: A Multi-User, Multi-Object Dataset for Joint 3D Hand-Object Pose Estimation
    • [cs.CV]High-speed Railway Fastener Detection and Localization System
    • [cs.CV]ICDAR 2019 Competition on Scene Text Visual Question Answering
    • [cs.CV]ICDAR2019 Robust Reading Challenge on Multi-lingual Scene Text Detection and Recognition — RRC-MLT-2019
    • [cs.CV]INN: Inflated Neural Networks for IPMN Diagnosis
    • [cs.CV]Improving Borderline Adulthood Facial Age Estimation through Ensemble Learning
    • [cs.CV]Inverse Attention Guided Deep Crowd Counting Network
    • [cs.CV]Landmark Assisted CycleGAN for Cartoon Face Generation
    • [cs.CV]Lane Detection and Classification using Cascaded CNNs
    • [cs.CV]Language2Pose: Natural Language Grounded Pose Forecasting
    • [cs.CV]Large Area 3D Human Pose Detection Via Stereo Reconstruction in Panoramic Cameras
    • [cs.CV]Large-scale, real-time visual-inertial localization revisited
    • [cs.CV]Learnable Gated Temporal Shift Module for Deep Video Inpainting
    • [cs.CV]Learning Objectness from Sonar Images for Class-Independent Object Detection
    • [cs.CV]Learning to Approximate Directional Fields Defined over 2D Planes
    • [cs.CV]Learning to Blindly Assess Image Quality in the Laboratory and Wild
    • [cs.CV]Learning to Find Correlated Features by Maximizing Information Flow in Convolutional Neural Networks
    • [cs.CV]Learning to Generate Synthetic 3D Training Data through Hybrid Gradient
    • [cs.CV]Learning to aggregate feature representations
    • [cs.CV]Multi-Cue Vehicle Detection for Semantic Video Compression In Georegistered Aerial Videos
    • [cs.CV]Multi-scale Template Matching with Scalable Diversity Similarity in an Unconstrained Environment
    • [cs.CV]Multiple Landmark Detection using Multi-Agent Reinforcement Learning
    • [cs.CV]Multiview Aggregation for Learning Category-Specific Shape Reconstruction
    • [cs.CV]Nature Inspired Dimensional Reduction Technique for Fast and Invariant Visual Feature Extraction
    • [cs.CV]Obj-GloVe: Scene-Based Contextual Object Embedding
    • [cs.CV]One Network for Multi-Domains: Domain Adaptive Hashing with Intersectant Generative Adversarial Network
    • [cs.CV]Online Multiple Pedestrian Tracking using Deep Temporal Appearance Matching Association
    • [cs.CV]Pano Popups: Indoor 3D Reconstruction with a Plane-Aware Network
    • [cs.CV]Pathologist-Level Grading of Prostate Biopsies with Artificial Intelligence
    • [cs.CV]Permutohedral Attention Module for Efficient Non-Local Neural Networks
    • [cs.CV]Predicting video saliency using crowdsourced mouse-tracking data
    • [cs.CV]Procedure Planning in Instructional Videos
    • [cs.CV]Proposal, Tracking and Segmentation (PTS): A Cascaded Network for Video Object Segmentation
    • [cs.CV]Random Vector Functional Link Neural Network based Ensemble Deep Learning
    • [cs.CV]Semi-Bagging Based Deep Neural Architecture to Extract Text from High Entropy Images
    • [cs.CV]Spatio-thermal depth correction of RGB-D sensors based on Gaussian Processes in real-time
    • [cs.CV]Stereo relative pose from line and point feature triplets
    • [cs.CV]Symmetry Detection and Classification in Drawings of Graphs
    • [cs.CV]TedEval: A Fair Evaluation Metric for Scene Text Detectors
    • [cs.CV]The Ethical Dilemma when (not) Setting up Cost-based Decision Rules in Semantic Segmentation
    • [cs.CV]The Resale Price Prediction of Secondhand Jewelry Items Using a Multi-modal Deep Model with Iterative Co-Attention
    • [cs.CV]Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-Shot Cross-Dataset Transfer
    • [cs.CV]Training Auto-encoder-based Optimizers for Terahertz Image Reconstruction
    • [cs.CV]Unsupervised Deformable Image Registration Using Cycle-Consistent CNN
    • [cs.CV]Visual Space Optimization for Zero-shot Learning
    • [cs.CV]Where are the Masks: Instance Segmentation with Image-level Supervision
    • [cs.CV]XNect: Real-time Multi-person 3D Human Pose Estimation with a Single RGB Camera
    • [cs.CY]Following wrong suggestions: self-blame in human and computer scenarios
    • [cs.CY]Hidden in Plain Sight For Too Long: Using Text Mining Techniques to Shine a Light on Workplace Sexism and Sexual Harassment
    • [cs.CY]Ich weiß, was du nächsten Sommer getan haben wirst: Predictive Policing in Österreich
    • [cs.CY]Learning to Identify Patients at Risk of Uncontrolled Hypertension Using Electronic Health Records Data
    • [cs.CY]Proof of Witness Presence: Blockchain Consensus for Augmented Democracy in Smart Cities
    • [cs.CY]What, When and Where of petitions submitted to the UK Government during a time of chaos
    • [cs.CY]YouTube Chatter: Understanding Online Comments Discourse on Misinformative and Political YouTube Videos
    • [cs.DC]Asynchronous Communications Library for the Parallel-in-Time Solution of Black-Scholes Equation
    • [cs.DC]Asynchronous Parareal Algorithm Applied to European Option Pricing
    • [cs.DC]Bridging the Architecture Gap: Abstracting Performance-Relevant Properties of Modern Server Processors
    • [cs.DC]Convergence Detection of Asynchronous Iterations based on Modified Recursive Doubling
    • [cs.DC]Creek: a General Mixed-Consistency Transactional Replication Scheme
    • [cs.DC]Distributed-Memory Load Balancing with Cyclic Token-based Work-Stealing Applied to Reverse Time Migration
    • [cs.DC]Fully-Asynchronous Fully-Implicit Variable-Order Variable-Timestep Simulation of Neural Networks
    • [cs.DC]Network-accelerated Distributed Machine Learning Using MLFabric
    • [cs.DC]Open-MPI over MOSIX: paralleled computing in a clustered world
    • [cs.DC]Parallel Performance of Molecular Dynamics Trajectory Analysis
    • [cs.DC]Planting Trees for scalable and efficient Canonical Hub Labeling
    • [cs.DC]State-of-the-Art on Query & Transaction Processing Acceleration
    • [cs.DC]Themis: Fair and Efficient GPU Cluster Scheduling for Machine Learning Workloads
    • [cs.DC]Understanding Fault Scenarios and Impacts through Fault Injection Experiments in Cielo
    • [cs.DL]Infrastructure-Agnostic Hypertext
    • [cs.ET]Composable Rate-Independent Computation in Continuous Chemical Reaction Networks
    • [cs.HC]FVA: Modeling Perceived Friendliness of Virtual Agents Using Movement Characteristics
    • [cs.HC]Simultaneous Achievement of Driver Assistance and Skill Development in Shared and Cooperative Controls
    • [cs.IR]A Capsule Network for Recommendation and Explaining What You Like and Dislike
    • [cs.IR]A Framework for Evaluating Snippet Generation for Dataset Search
    • [cs.IR]A Review-Driven Neural Model for Sequential Recommendation
    • [cs.IR]Dermtrainer: A Decision Support System for Dermatological Diseases
    • [cs.IR]Effects of Foraging in Personalized Content-based Image Recommendation
    • [cs.IR]Extracting Novel Facts from Tables for Knowledge Graph Completion (Extended version)
    • [cs.IR]Learning to Reformulate the Queries on the WEB
    • [cs.IR]Music Performance Analysis: A Survey
    • [cs.IR]On Slicing Sorted Integer Sequences
    • [cs.IR]One Size Does Not Fit All: Modeling Users’ Personal Curiosity in Recommender Systems
    • [cs.IR]Prediction is very hard, especially about conversion. Predicting user purchases from clickstream data in fashion e-commerce
    • [cs.IR]Representation, Exploration and Recommendation of Music Playlists
    • [cs.IR]Semantic Driven Fielded Entity Retrieval
    • [cs.IR]Semantic Product Search
    • [cs.IT]”Machine LLRning”: Learning to Softly Demodulate
    • [cs.IT]5G NR CA-Polar Maximum Likelihood Decoding by GRAND
    • [cs.IT]A Direct Construction of Optimal ZCCS and IGC Code Set With Maximum Column Sequence PMEPR Two For MC-CDMA System
    • [cs.IT]A Local Perspective on the Edge Removal Problem
    • [cs.IT]Bundled Causal History Interaction
    • [cs.IT]From Parameter Estimation to Dispersion of Nonstationary Gauss-Markov Processes
    • [cs.IT]Mathematical Model of Emotional Habituation to Novelty: Modeling with Bayesian Update and Information Theory
    • [cs.IT]Mismatched Guesswork
    • [cs.IT]On an Equivalence Between Single-Server PIR with Side Information and Locally Recoverable Codes
    • [cs.IT]On list decoding of 5G-NR polar codes
    • [cs.IT]On the Sample Complexity of HGR Maximal Correlation Functions
    • [cs.IT]On the list decodability of Rank Metric codes
    • [cs.IT]Polar Codes with Memory
    • [cs.IT]Predictive Network Control in Multi-Connectivity Mobility for URLLC Services
    • [cs.IT]Private Authentication with Physical Identifiers Through Broadcast Channel Measurements
    • [cs.IT]Quantization in Compressive Sensing: A Signal Processing Approach
    • [cs.IT]Spatial Coded Modulation
    • [cs.IT]Study of Rate-Splitting Techniques with Block Diagonalization for Multiuser MIMO Systems
    • [cs.IT]Trading Off Computation with Transmission in Status Update Systems
    • [cs.LG]A Framework For Identifying Group Behavior Of Wild Animals
    • [cs.LG]A Semi-Supervised Self-Organizing Map for Clustering and Classification
    • [cs.LG]A Semi-Supervised Self-Organizing Map with Adaptive Local Thresholds
    • [cs.LG]Active Learning within Constrained Environments through Imitation of an Expert Questioner
    • [cs.LG]An Iteratively Re-weighted Method for Problems with Sparsity-Inducing Norms
    • [cs.LG]An Open Source AutoML Benchmark
    • [cs.LG]An aggregate learning approach for interpretable semi-supervised population prediction and disaggregation using ancillary data
    • [cs.LG]An innovative adaptive kriging approach for efficient binary classification of mechanical problems
    • [cs.LG]Applying Transfer Learning To Deep Learned Models For EEG Analysis
    • [cs.LG]Approximate Sherali-Adams Relaxations for MAP Inference via Entropy Regularization
    • [cs.LG]Astraea: Self-balancing Federated Learning for Improving Classification Accuracy of Mobile Deep Learning Applications
    • [cs.LG]Augmenting Self-attention with Persistent Memory
    • [cs.LG]Avoiding Implementation Pitfalls of “Matrix Capsules with EM Routing” by Hinton et al
    • [cs.LG]Bandit Learning Through Biased Maximum Likelihood Estimation
    • [cs.LG]Best k-layer neural network approximations
    • [cs.LG]Causal Inference Under Interference And Network Uncertainty
    • [cs.LG]Comment on “Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network”
    • [cs.LG]Conservative Q-Improvement: Reinforcement Learning for an Interpretable Decision-Tree Policy
    • [cs.LG]Continual Learning for Robotics
    • [cs.LG]Cosine similarity-based adversarial process
    • [cs.LG]Deep Multi-Task Learning for Anomalous Driving Detection Using CAN Bus Scalar Sensor Data
    • [cs.LG]Deep Residual Neural Networks for Audio Spoofing Detection
    • [cs.LG]Detecting Spiky Corruption in Markov Decision Processes
    • [cs.LG]Dissecting Pruned Neural Networks
    • [cs.LG]Domain Adaptation via Low-Rank Basis Approximation
    • [cs.LG]Efficient Regularized Piecewise-Linear Regression Trees
    • [cs.LG]Equation Discovery for Nonlinear System Identification
    • [cs.LG]Estimating Information-Theoretic Quantities with Random Forests
    • [cs.LG]Exploiting Relevance for Online Decision-Making in High-Dimensions
    • [cs.LG]Exponential Separations in Local Differential Privacy Through Communication Complexity
    • [cs.LG]FRODO: Free rejection of out-of-distribution samples: application to chest x-ray analysis
    • [cs.LG]FiDi-RL: Incorporating Deep Reinforcement Learning with Finite-Difference Policy Search for Efficient Learning of Continuous Control
    • [cs.LG]Gaussian Mixture Marginal Distributions for Modelling Remaining Pipe Wall Thickness of Critical Water Mains in Non-Destructive Evaluation
    • [cs.LG]Generalizing from a few environments in safety-critical reinforcement learning
    • [cs.LG]Improving LSTM Neural Networks for Better Short-Term Wind Power Predictions
    • [cs.LG]Isolation Kernel: The X Factor in Efficient and Effective Large Scale Online Kernel Learning
    • [cs.LG]Learning Representations from Imperfect Time Series Data via Tensor Rank Regularization
    • [cs.LG]Learning World Graphs to Accelerate Hierarchical Reinforcement Learning
    • [cs.LG]Learning the Arrow of Time
    • [cs.LG]Learning to Traverse Latent Spaces for Musical Score Inpainting
    • [cs.LG]Location Anomalies Detection for Connected and Autonomous Vehicles
    • [cs.LG]ML-based Fault Injection for Autonomous Vehicles: A Case for Bayesian Fault Injection
    • [cs.LG]MULEX: Disentangling Exploitation from Exploration in Deep RL
    • [cs.LG]Mechanisms of Artistic Creativity in Deep Learning Neural Networks
    • [cs.LG]Mincut pooling in Graph Neural Networks
    • [cs.LG]Mixed-Variable Bayesian Optimization
    • [cs.LG]Modeling Tabular data using Conditional GAN
    • [cs.LG]Modified Actor-Critics
    • [cs.LG]Multi-Label Product Categorization Using Multi-Modal Fusion Models
    • [cs.LG]Multiplicative Models for Recurrent Language Modeling
    • [cs.LG]Nearest-Neighbour-Induced Isolation Similarity and its Impact on Density-Based Clustering
    • [cs.LG]Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks
    • [cs.LG]Neural Logic Rule Layers
    • [cs.LG]On Symmetry and Initialization for Neural Networks
    • [cs.LG]On mechanisms for transfer using landmark value functions in multi-task lifelong reinforcement learning
    • [cs.LG]Open Problem: The Oracle Complexity of Convex Optimization with Limited Memory
    • [cs.LG]Operationalizing Individual Fairness with Pairwise Fair Representations
    • [cs.LG]Predicting Treatment Initiation from Clinical Time Series Data via Graph-Augmented Time-Sensitive Model
    • [cs.LG]Progressive Fashion Attribute Extraction
    • [cs.LG]Rare Disease Detection by Sequence Modeling with Generative Adversarial Networks
    • [cs.LG]Reproducibility in Machine Learning for Health
    • [cs.LG]Robust Tensor Completion Using Transformed Tensor SVD
    • [cs.LG]Robust and Resource Efficient Identification of Two Hidden Layer Neural Networks
    • [cs.LG]Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points
    • [cs.LG]Single-Path Mobile AutoML: Efficient ConvNet Design and NAS Hyperparameter Optimization
    • [cs.LG]Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model
    • [cs.LG]The Ramanujan Machine: Automatically Generated Conjectures on Fundamental Constants
    • [cs.LG]The Sensitivity of Counterfactual Fairness to Unmeasured Confounding
    • [cs.LG]The SpectACl of Nonconvex Clustering: A Spectral Approach to Density-Based Clustering
    • [cs.LG]The Trustworthy Pal: Controlling the False Discovery Rate in Boolean Matrix Factorization
    • [cs.LG]Tight Sensitivity Bounds For Smaller Coresets
    • [cs.LG]Treant: Training Evasion-Aware Decision Trees
    • [cs.LG]Two-stage Optimization for Machine Learning Workflow
    • [cs.LG]Understanding Memory Modules on Learning Simple Algorithms
    • [cs.LG]Universal audio synthesizer control with normalizing flows
    • [cs.LG]Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments
    • [cs.LG]Variational Quantum Circuits and Deep Reinforcement Learning
    • [cs.LG]Voting-Based Multi-Agent Reinforcement Learning
    • [cs.LG]Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog
    • [cs.LG]Weight Normalization based Quantization for Deep Neural Network Compression
    • [cs.LG]iPool — Information-based Pooling in Hierarchical Graph Neural Networks
    • [cs.MA]Collaboration of AI Agents via Cooperative Multi-Agent Deep Reinforcement Learning
    • [cs.MM]Adaptive Music Composition for Games
    • [cs.MS]GPU-based Parallel Computation Support for Stan
    • [cs.MS]Solving Polynomial Systems with phcpy
    • [cs.NE]A Hybrid Learning Rule for Efficient and Rapid Inference with Spiking Neural Networks
    • [cs.NE]A Note On The Popularity of Stochastic Optimization Algorithms in Different Fields: A Quantitative Analysis from 2007 to 2017
    • [cs.NE]ACM-DE: Adaptive p-best Cauchy Mutation with linear failure threshold reduction for Differential Evolution in numerical optimization
    • [cs.NE]Multi-objective multi-generation Gaussian process optimizer for design optimization
    • [cs.NE]On-chip learning in a conventional silicon MOSFET based Analog Hardware Neural Network
    • [cs.NI]Service-based Routing at the Edge
    • [cs.RO]A Joint Optimization Approach of LiDAR-Camera Fusion for Accurate Dense 3D Reconstructions
    • [cs.RO]Active Learning of Probabilistic Movement Primitives
    • [cs.RO]Asynchronous Behavior Trees with Memory aimed at Aerial Vehicles with Redundancy in Flight Controller
    • [cs.RO]GarmNet: Improving Global with Local Perception for Robotic Laundry Folding
    • [cs.RO]Memory of Motion for Warm-starting Trajectory Optimization
    • [cs.RO]Model-free Friction Observers for Flexible Joint Robots with Torque Measurements
    • [cs.RO]Neural Semantic Parsing with Anonymization for Command Understanding in General-Purpose Service Robots
    • [cs.RO]On Training Flexible Robots using Deep Reinforcement Learning
    • [cs.RO]Persistent Multi-UAV Surveillance with Data Latency Constraints
    • [cs.RO]ROS 2 for RoboCup
    • [cs.RO]Robust and Efficient Quadrotor Trajectory Generation for Fast Autonomous Flight
    • [cs.RO]Teach-Repeat-Replan: A Complete and Robust System for Aggressive Flight in Complex Environments
    • [cs.RO]Toward Asymptotically-Optimal Inspection Planning via Efficient Near-Optimal Graph Search
    • [cs.SD]Can a Robot Hear the Shape and Dimensions of a Room?
    • [cs.SD]Kite: Automatic speech recognition for unmanned aerial vehicles
    • [cs.SD]WHAM!: Extending Speech Separation to Noisy Environments
    • [cs.SE]A Scalable Architecture for Power Consumption Monitoring in Industrial Production Environments
    • [cs.SI]A Semantic Approach for User-Brand Targeting in On-Line Social Networks
    • [cs.SI]Generalized Random Surfer-Pair Models
    • [cs.SI]Predicting the Topical Stance of Media and Popular Twitter Users
    • [cs.SI]Unsupervised Adversarial Graph Alignment with Graph Embedding
    • [econ.EM]Permutation inference with a finite number of heterogeneous clusters
    • [eess.AS]Comparison of Lattice-Free and Lattice-Based Sequence Discriminative Training Criteria for LVCSR
    • [eess.AS]Improving Performance of End-to-End ASR on Numeric Sequences
    • [eess.AS]LSTM Language Models for LVCSR in First-Pass Decoding and Lattice-Rescoring
    • [eess.AS]Speaker-independent classification of phonetic segments from raw ultrasound in child speech
    • [eess.AS]Ultrasound tongue imaging for diarization and alignment of child speech therapy sessions
    • [eess.IV]An Efficient Solution for Breast Tumor Segmentation and Classification in Ultrasound Images Using Deep Adversarial Learning
    • [eess.IV]Automated Image Registration Quality Assessment Utilizing Deep-learning based Ventricle Extraction in Clinical Data
    • [eess.IV]Bayesian Optimization on Large Graphs via a Graph Convolutional Generative Model: Application in Cardiac Model Personalization
    • [eess.IV]Conditional Segmentation in Lieu of Image Registration
    • [eess.IV]Dual Network Architecture for Few-view CT —Trained on ImageNet Data and Transferred for Medical Imaging
    • [eess.IV]Generative Mask Pyramid Network forCT/CBCT Metal Artifact Reduction with Joint Projection-Sinogram Correction
    • [eess.IV]Global Transformer U-Nets for Label-Free Prediction of Fluorescence Images
    • [eess.IV]Improving the generalizability of convolutional neural network-based segmentation on CMR images
    • [eess.IV]MobileGAN: Skin Lesion Segmentation Using a Lightweight Generative Adversarial Network
    • [eess.IV]Multi-scale GANs for Memory-efficient Generation of High Resolution Medical Images
    • [eess.IV]SLAM Endoscopy enhanced by adversarial depth prediction
    • [eess.IV]Seismic data denoising and deblending using deep learning
    • [eess.IV]Self-supervised Hyperspectral Image Restoration using Separable Image Prior
    • [eess.IV]Signed Laplacian Deep Learning with Adversarial Augmentation for Improved Mammography Diagnosis
    • [eess.SP]Base Station Antenna Selection for Low-Resolution ADC Systems
    • [eess.SP]Beam Allocation for Millimeter-Wave MIMO Tracking Systems
    • [eess.SP]Deep Learning for Hybrid 5G Services in Mobile Edge Computing Systems: Learn from a Digital Twin
    • [eess.SP]Improved Circuit Design of Analog Joint Source Channel Coding for Low-power and Low-complexity Wireless Sensors
    • [eess.SY]Automatic Real-time Anomaly Detection for Autonomous Aerial Vehicles
    • [eess.SY]Distributed Global Output-Feedback Control for a Class of Euler-Lagrange Systems
    • [math.HO]Male Under-performance in Undergraduate Engineering Mathematical Courses: Causes and Solution Strategy
    • [math.NA]A data-driven approach for multiscale elliptic PDEs with random coefficients based on intrinsic dimension reduction
    • [math.NA]Lossy Compression for Large Scale PDE Problems
    • [math.OC]Competitive Algorithms for Online Budget-Constrained Continuous DR-Submodular Problems
    • [math.OC]Conjugate Gradients and Accelerated Methods Unified: The Approximate Duality Gap View
    • [math.OC]Efficient Algorithms for Smooth Minimax Optimization
    • [math.OC]Online Continuous DR-Submodular Maximization with Long-Term Budget Constraints
    • [math.OC]The Constrained $L_p$-$L_q$ Basis Pursuit Denoising Problem
    • [math.PR]Constrained Monte Carlo Markov Chains on Graphs
    • [math.ST]A New Lower Bound for Kullback-Leibler Divergence Based on Hammersley-Chapman-Robbins Bound
    • [math.ST]A greedy algorithm for sparse precision matrix approximation
    • [math.ST]Bounding Causes of Effects with Mediators
    • [math.ST]Elicitability and Identifiability of Systemic Risk Measures and other Set-Valued Functionals
    • [math.ST]Geodesic Distance Estimation with Spherelets
    • [math.ST]Large-scale inference with block structure
    • [math.ST]Multidimensional Scaling on Metric Measure Spaces
    • [math.ST]Multiple Bayesian Filtering as Message Passing
    • [math.ST]Power Lindley distribution and software metrics
    • [math.ST]Robust analogues to the Coefficient of Variation
    • [math.ST]Specification testing in semi-parametric transformation models
    • [math.ST]Statistical estimation of the Kullback-Leibler divergence
    • [math.ST]The generalized orthogonal Procrustes problem in the high noise regime
    • [physics.chem-ph]Automatic Routing of Goldstone Diagrams using Genetic Algorithms
    • [physics.chem-ph]Predicting Retrosynthetic Reaction using Self-Corrected Transformer Neural Networks
    • [physics.soc-ph]Identifying vital nodes based on reverse greedy method
    • [physics.soc-ph]Influence measures in subnetworks using vertex centrality
    • [physics.soc-ph]Instability of social network dynamics with stubborn links
    • [physics.soc-ph]The Role of Network Structure and Initial Group Norm Distributions in Norm Conflict
    • [q-bio.BM]Molecular activity prediction using graph convolutional deep neural network considering distance on a molecular graph
    • [q-bio.NC]A Power Efficient Artificial Neuron Using Superconducting Nanowires
    • [q-bio.NC]Simple 1-D Convolutional Networks for Resting-State fMRI Based Classification in Autism
    • [q-bio.NC]Unsupervised predictive coding models may explain visual brain representation
    • [q-bio.QM]Neural parameters estimation for brain tumor growth modeling
    • [q-fin.ST]Improved Forecasting of Cryptocurrency Price using Social Signals
    • [quant-ph]Logical Clifford Synthesis for Stabilizer Codes
    • [quant-ph]Quantum Data-Syndrome Codes
    • [stat.AP]An Intrinsic Geometrical Approach for Statistical Process Control of Surface and Manifold Data
    • [stat.AP]Applying Meta-Analytic Predictive Priors with the R Bayesian evidence synthesis tools
    • [stat.AP]ICU Disparnumerophobia and Triskaidekaphobia: The ‘Irrational Care Unit’?
    • [stat.AP]Large Volatility Matrix Prediction with High-Frequency Data
    • [stat.AP]Wave-shape oscillatory model for biomedical time series with applications
    • [stat.CO]trialr: Bayesian Clinical Trial Designs in R and Stan
    • [stat.ME]Adaptive Partitioning Design and Analysis for Emulation of a Complex Computer Code
    • [stat.ME]An outlier-robust Kalman filter with mixture correntropy
    • [stat.ME]Bayesian Analysis of High-dimensional Discrete Graphical Models
    • [stat.ME]Coupling techniques for nonlinear ensemble filtering
    • [stat.ME]Estimating Treatment Effect under Additive Hazards Models with High-dimensional Covariates
    • [stat.ME]Frequentist performances of Bayesian prediction intervals for random-effects meta-analysis
    • [stat.ME]Multiple competition based FDR control
    • [stat.ME]On Global-local Shrinkage Priors for Count Data
    • [stat.ME]Penalized Variable Selection in Multi-Parameter Regression Survival Modelling
    • [stat.ME]State-of-the-art in selection of variables and functional forms in multivariable analysis — outstanding issues
    • [stat.ME]Transformed Naive Ratio and Product Based Estimators for Estimating Population Mode in Simple Random Sampling
    • [stat.ME]Using Subset Log-Likelihoods to Trim Outliers in Gaussian Mixture Models
    • [stat.ME]Volatility Analysis with Realized GARCH-Ito Models
    • [stat.ML]A Kernel Stein Test for Comparing Latent Variable Models
    • [stat.ML]A Unified Approach to Robust Mean Estimation
    • [stat.ML]Accurate, reliable and fast robustness evaluation
    • [stat.ML]Augmenting and Tuning Knowledge Graph Embeddings
    • [stat.ML]Radial Bayesian Neural Networks: Robust Variational Inference In Big Models
    • [stat.ML]Sparse regular variation
    • [stat.ML]Time-to-Event Prediction with Neural Networks and Cox Regression

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

    • [cond-mat.dis-nn]Rate Distortion Theorem and the Multicritical Point of Spin Glass
    Tatsuto Murayama, Asaki Saito, Peter Davis
    http://arxiv.org/abs/1907.01048v1

    • [cs.AI]An Empirical Evaluation of Two General Game Systems: Ludii and RBG
    Éric Piette, Matthew Stephenson, Dennis J. N. J. Soemers, Cameron Browne
    http://arxiv.org/abs/1907.00244v1

    • [cs.AI]An Overview of the Ludii General Game System
    Matthew Stephenson, Éric Piette, Dennis J. N. J. Soemers, Cameron Browne
    http://arxiv.org/abs/1907.00240v1

    • [cs.AI]Analysis of the Synergy between Modularity and Autonomy in an Artificial Intelligence Based Fleet Competition
    Xingyu Li, Mainak Mitra, Bogdan I. Epureanu
    http://arxiv.org/abs/1907.01405v1

    • [cs.AI]Elementary Iterated Revision and the Levi Identity
    Jake Chandler, Richard Booth
    http://arxiv.org/abs/1907.01224v1

    • [cs.AI]Investigating The Piece-Wise Linearity And Benchmark Related To Koczy-Hirota Fuzzy Linear Interpolation
    Maen Alzubi, Szilvester Kovács
    http://arxiv.org/abs/1907.01047v1

    • [cs.AI]Knowledge Graph Embedding for Ecotoxicological Effect Prediction
    Erik B. Myklebust, Ernesto Jimenez-Ruiz, Jiaoyan Chen, Raoul Wolf, Knut Erik Tollefsen
    http://arxiv.org/abs/1907.01328v1

    • [cs.AI]Ludii and XCSP: Playing and Solving Logic Puzzles
    Cédric Piette, Éric Piette, Matthew Stephenson, Dennis J. N. J. Soemers, Cameron Browne
    http://arxiv.org/abs/1907.00245v1

    • [cs.AI]Ludii as a Competition Platform
    Matthew Stephenson, Éric Piette, Dennis J. N. J. Soemers, Cameron Browne
    http://arxiv.org/abs/1907.00246v1

    • [cs.AI]Neural Network Verification for the Masses (of AI graduates)
    Ekaterina Komendantskaya, Rob Stewart, Kirsy Duncan, Daniel Kienitz, Pierre Le Hen, Pascal Bacchus
    http://arxiv.org/abs/1907.01297v1

    • [cs.AI]Reinforcement Learning with Fairness Constraints for Resource Distribution in Human-Robot Teams
    Houston Claure, Yifang Chen, Jignesh Modi, Malte Jung, Stefanos Nikolaidis
    http://arxiv.org/abs/1907.00313v1

    • [cs.AI]Requisite Variety in Ethical Utility Functions for AI Value Alignment
    Nadisha-Marie Aliman, Leon Kester
    http://arxiv.org/abs/1907.00430v1

    • [cs.AI]Visual analytics for team-based invasion sports with significant events and Markov reward process
    Kun Zhao, Takayuki Osogami, Tetsuro Morimura
    http://arxiv.org/abs/1907.01221v1

    • [cs.AR]On the Optimal Refresh Power Allocation for Energy-Efficient Memories
    Yongjune Kim, Won Ho Choi, Cyril Guyot, Yuval Cassuto
    http://arxiv.org/abs/1907.01112v1

    • [cs.CG]Exploring Feasible Design Spaces for Heterogeneous Constraints
    Amir M. Mirzendehdel, Morad Behandish, Saigopal Nelaturi
    http://arxiv.org/abs/1907.01117v1

    • [cs.CL]A Neural Grammatical Error Correction System Built On Better Pre-training and Sequential Transfer Learning
    Yo Joong Choe, Jiyeon Ham, Kyubyong Park, Yeoil Yoon
    http://arxiv.org/abs/1907.01256v1

    • [cs.CL]A Novel Bi-directional Interrelated Model for Joint Intent Detection and Slot Filling
    Haihong E, Peiqing Niu, Zhongfu Chen, Meina Song
    http://arxiv.org/abs/1907.00390v1

    • [cs.CL]Analyzing Utility of Visual Context in Multimodal Speech Recognition Under Noisy Conditions
    Tejas Srinivasan, Ramon Sanabria, Florian Metze
    http://arxiv.org/abs/1907.00477v1

    • [cs.CL]Claim Extraction in Biomedical Publications using Deep Discourse Model and Transfer Learning
    Titipat Achakulvisut, Chandra Bhagavatula, Daniel Acuna, Konrad Kording
    http://arxiv.org/abs/1907.00962v1

    • [cs.CL]Constructing large scale biomedical knowledge bases from scratch with rapid annotation of interpretable patterns
    Julien Fauqueur, Ashok Thillaisundara, Theodosia Togia
    http://arxiv.org/abs/1907.01417v1

    • [cs.CL]Contextual Phonetic Pretraining for End-to-end Utterance-level Language and Speaker Recognition
    Shaoshi Ling, Julian Salazar, Katrin Kirchhoff
    http://arxiv.org/abs/1907.00457v1

    • [cs.CL]Cooperative Generator-Discriminator Networks for Abstractive Summarization with Narrative Flow
    Saadia Gabriel, Antoine Bosselut, Ari Holtzman, Kyle Lo, Asli Celikyilmaz, Yejin Choi
    http://arxiv.org/abs/1907.01272v1

    • [cs.CL]Danish Stance Classification and Rumour Resolution
    Anders Edelbo Lillie, Emil Refsgaard Middelboe
    http://arxiv.org/abs/1907.01304v1

    • [cs.CL]Do Transformer Attention Heads Provide Transparency in Abstractive Summarization?
    Joris Baan, Maartje ter Hoeve, Marlies van der Wees, Anne Schuth, Maarten de Rijke
    http://arxiv.org/abs/1907.00570v1

    • [cs.CL]EGG: a toolkit for research on Emergence of lanGuage in Games
    Eugene Kharitonov, Rahma Chaabouni, Diane Bouchacourt, Marco Baroni
    http://arxiv.org/abs/1907.00852v1

    • [cs.CL]Empirical Evaluation of Sequence-to-Sequence Models for Word Discovery in Low-resource Settings
    Marcely Zanon Boito, Aline Villavicencio, Laurent Besacier
    http://arxiv.org/abs/1907.00184v1

    • [cs.CL]Evaluating Language Model Finetuning Techniques for Low-resource Languages
    Jan Christian Blaise Cruz, Charibeth Cheng
    http://arxiv.org/abs/1907.00409v1

    • [cs.CL]Fake News Detection using Stance Classification: A Survey
    Anders Edelbo Lillie, Emil Refsgaard Middelboe
    http://arxiv.org/abs/1907.00181v1

    • [cs.CL]Few-Shot Representation Learning for Out-Of-Vocabulary Words
    Ziniu Hu, Ting Chen, Kai-Wei Chang, Yizhou Sun
    http://arxiv.org/abs/1907.00505v1

    • [cs.CL]GPT-based Generation for Classical Chinese Poetry
    Yi Liao, Yasheng Wang, Qun Liu, Xin Jiang
    http://arxiv.org/abs/1907.00151v2

    • [cs.CL]How we do things with words: Analyzing text as social and cultural data
    Dong Nguyen, Maria Liakata, Simon DeDeo, Jacob Eisenstein, David Mimno, Rebekah Tromble, Jane Winters
    http://arxiv.org/abs/1907.01468v1

    • [cs.CL]HyST: A Hybrid Approach for Flexible and Accurate Dialogue State Tracking
    Rahul Goel, Shachi Paul, Dilek Hakkani-Tür
    http://arxiv.org/abs/1907.00883v1

    • [cs.CL]Improving Robustness in Real-World Neural Machine Translation Engines
    Rohit Gupta, Patrik Lambert, Raj Nath Patel, John Tinsley
    http://arxiv.org/abs/1907.01279v1

    • [cs.CL]Inter and Intra Document Attention for Depression Risk Assessment
    Diego Maupomé, Marc Queudot, Marie-Jean Meurs
    http://arxiv.org/abs/1907.00462v1

    • [cs.CL]Is artificial data useful for biomedical Natural Language Processing
    Zixu Wang, Julia Ive, Sumithra Velupillai, Lucia Specia
    http://arxiv.org/abs/1907.01055v1

    • [cs.CL]Katecheo: A Portable and Modular System for Multi-Topic Question Answering
    Shirish Hirekodi, Seban Sunny, Leonard Topno, Alwin Daniel, Daniel Whitenack, Reuben Skewes, Stuart Cranney
    http://arxiv.org/abs/1907.00854v1

    • [cs.CL]Latent Dirichlet Allocation Based Acoustic Data Selection for Automatic Speech Recognition
    Mortaza, Doulaty, Thomas Hain
    http://arxiv.org/abs/1907.01302v1

    • [cs.CL]Latent Variable Sentiment Grammar
    Liwen Zhang, Kewei Tu, Yue Zhang
    http://arxiv.org/abs/1907.00218v1

    • [cs.CL]Leveraging Acoustic Cues and Paralinguistic Embeddings to Detect Expression from Voice
    Vikramjit Mitra, Sue Booker, Erik Marchi, David Scott Farrar, Ute Dorothea Peitz, Bridget Cheng, Ermine Teves, Anuj Mehta, Devang Naik
    http://arxiv.org/abs/1907.00112v1

    • [cs.CL]Merge and Label: A novel neural network architecture for nested NER
    Joseph Fisher, Andreas Vlachos
    http://arxiv.org/abs/1907.00464v1

    • [cs.CL]Modernizing Historical Documents: a User Study
    Miguel Domingo, Francisco Casacuberta
    http://arxiv.org/abs/1907.00659v1

    • [cs.CL]Multilingual Bottleneck Features for Query by Example Spoken Term Detection
    Dhananjay Ram, Lesly Miculicich, Hervé Bourlard
    http://arxiv.org/abs/1907.00443v1

    • [cs.CL]Multilingual, Multi-scale and Multi-layer Visualization of Intermediate Representations
    Carlos Escolano, Marta R. Costa-jussà, Elora Lacroux, Pere-Pau Vázquez
    http://arxiv.org/abs/1907.00810v1

    • [cs.CL]Multimodal Transformer Networks for End-to-End Video-Grounded Dialogue Systems
    Hung Le, Doyen Sahoo, Nancy F. Chen, Steven C. H. Hoi
    http://arxiv.org/abs/1907.01166v1

    • [cs.CL]Natural Language Understanding with the Quora Question Pairs Dataset
    Lakshay Sharma, Laura Graesser, Nikita Nangia, Utku Evci
    http://arxiv.org/abs/1907.01041v1

    • [cs.CL]Neural Machine Reading Comprehension: Methods and Trends
    Shanshan Liu, Xin Zhang, Sheng Zhang, Hui Wang, Weiming Zhang
    http://arxiv.org/abs/1907.01118v1

    • [cs.CL]Observing Dialogue in Therapy: Categorizing and Forecasting Behavioral Codes
    Jie Cao, Michael Tanana, Zac E. Imel, Eric Poitras, David C. Atkins, Vivek Srikumar
    http://arxiv.org/abs/1907.00326v1

    • [cs.CL]Post-editese: an Exacerbated Translationese
    Antonio Toral
    http://arxiv.org/abs/1907.00900v1

    • [cs.CL]Self-Supervised Dialogue Learning
    Jiawei Wu, Xin Wang, William Yang Wang
    http://arxiv.org/abs/1907.00448v1

    • [cs.CL]Sequence Labeling Parsing by Learning Across Representations
    Michalina Strzyz, David Vilares, Carlos Gómez-Rodríguez
    http://arxiv.org/abs/1907.01339v1

    • [cs.CL]Synchronising audio and ultrasound by learning cross-modal embeddings
    Aciel Eshky, Manuel Sam Ribeiro, Korin Richmond, Steve Renals
    http://arxiv.org/abs/1907.00758v1

    • [cs.CL]The CUED’s Grammatical Error Correction Systems for BEA-2019
    Felix Stahlberg, Bill Byrne
    http://arxiv.org/abs/1907.00168v1

    • [cs.CL]The University of Sydney’s Machine Translation System for WMT19
    Liang Ding, Dacheng Tao
    http://arxiv.org/abs/1907.00494v1

    • [cs.CL]Topic Modeling the Reading and Writing Behavior of Information Foragers
    Jaimie Murdock
    http://arxiv.org/abs/1907.00488v1

    • [cs.CL]UltraSuite: A Repository of Ultrasound and Acoustic Data from Child Speech Therapy Sessions
    Aciel Eshky, Manuel Sam Ribeiro, Joanne Cleland, Korin Richmond, Zoe Roxburgh, James Scobbie, Alan Wrench
    http://arxiv.org/abs/1907.00835v1

    • [cs.CL]Using Database Rule for Weak Supervised Text-to-SQL Generation
    Tong Guo, Huilin Gao
    http://arxiv.org/abs/1907.00620v1

    • [cs.CL]Weak Supervision Enhanced Generative Network for Question Generation
    Yutong Wang, Jiyuan Zheng, Qijiong Liu, Zhou Zhao, Jun Xiao, Yueting Zhuang
    http://arxiv.org/abs/1907.00607v1

    • [cs.CR]An Enhanced Electrocardiogram Biometric Authentication System Using Machine Learning
    Ebrahim Al Alkeem, Song-Kyoo Kim, Chan Yeob Yeun, M. Jamal Zemerly, Kin Poon, Paul D. Yoo
    http://arxiv.org/abs/1907.00366v1

    • [cs.CR]Collecting and Analyzing Multidimensional Data with Local Differential Privacy
    Ning Wang, Xiaokui Xiao, Yin Yang, Jun Zhao, Siu Cheung Hui, Hyejin Shin, Junbum Shin, Ge Yu
    http://arxiv.org/abs/1907.00782v1

    • [cs.CR]Fooling a Real Car with Adversarial Traffic Signs
    Nir Morgulis, Alexander Kreines, Shachar Mendelowitz, Yuval Weisglass
    http://arxiv.org/abs/1907.00374v1

    • [cs.CR]Machine Learning for Intelligent Authentication in 5G-and-Beyond Wireless Networks
    He Fang, Xianbin Wang, Stefano Tomasin
    http://arxiv.org/abs/1907.00429v1

    • [cs.CR]Methodology for the Automated Metadata-Based Classification of Incriminating Digital Forensic Artefacts
    Xiaoyu Du, Mark Scanlon
    http://arxiv.org/abs/1907.01421v1

    • [cs.CR]Secure Mobile Technologies for Proactive Critical Infrastructure Situational Awareness
    Gabriel Salles-Loustau, Vidyasagar Sadhu, Dario Pompili, Saman Zonouz, Vincent Sritapan
    http://arxiv.org/abs/1907.00332v1

    • [cs.CR]Taint analysis of the Bitcoin network
    Uroš Hercog, Andraž Povše
    http://arxiv.org/abs/1907.01538v1

    • [cs.CV]A Closest Point Proposal for MCMC-based Probabilistic Surface Registration
    Dennis Madsen, Andreas Morel-Forster, Patrick Kahr, Dana Rahbani, Thomas Vetter, Marcel Lüthi
    http://arxiv.org/abs/1907.01414v1

    • [cs.CV]A Single Video Super-Resolution GAN for Multiple Downsampling Operators based on Pseudo-Inverse Image Formation Models
    Santiago López-Tapia, Alice Lucas, Rafael Molina, Aggelos K. Katsaggelos
    http://arxiv.org/abs/1907.01399v1

    • [cs.CV]Adversarially Trained Deep Neural Semantic Hashing Scheme for Subjective Search in Fashion Inventory
    Saket Singh, Debdoot Sheet, Mithun Dasgupta
    http://arxiv.org/abs/1907.00382v1

    • [cs.CV]An Analysis of Deep Neural Networks with Attention for Action Recognition from a Neurophysiological Perspective
    Swathikiran Sudhakaran, Oswald Lanz
    http://arxiv.org/abs/1907.01273v1

    • [cs.CV]An End-to-End Neural Network for Image Cropping by Learning Composition from Aesthetic Photos
    Peng Lu, Hao Zhang, Xujun Peng, Xiaofu Jin
    http://arxiv.org/abs/1907.01432v1

    • [cs.CV]An Integrated Image Filter for Enhancing Change Detection Results
    Dawei Li, Siyuan Yan, Xin Cai, Yan Cao, Sifan Wang
    http://arxiv.org/abs/1907.01301v1

    • [cs.CV]Associative Embedding for Game-Agnostic Team Discrimination
    Maxime Istasse, Julien Moreau, Christophe De Vleeschouwer
    http://arxiv.org/abs/1907.01058v1

    • [cs.CV]Attribute-Driven Spontaneous Motion in Unpaired Image Translation
    Ruizheng Wu, Xin Tao, Xiaodong Gu, Xiaoyong Shen, Jiaya Jia
    http://arxiv.org/abs/1907.01452v1

    • [cs.CV]Brno Mobile OCR Dataset
    Martin Kišš, Michal Hradiš, Oldřich Kodym
    http://arxiv.org/abs/1907.01307v1

    • [cs.CV]CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark
    Alan Lukežič, Ugur Kart, Jani Käpylä, Ahmed Durmush, Joni-Kristian Kämäräinen, Jiří Matas, Matej Kristan
    http://arxiv.org/abs/1907.00618v1

    • [cs.CV]CSSegNet: Fine-Grained Cardiac Structures Segmentation Using Dilated Pyramid Pooling in U-net
    Fei Feng, Jiajia Luo
    http://arxiv.org/abs/1907.01390v1

    • [cs.CV]Cross-view Relation Networks for Mammogram Mass Detection
    Jiechao Ma, Sen Liang, Xiang Li, Hongwei Li, Bjoern H Menze, Rongguo Zhang, Wei-Shi Zheng
    http://arxiv.org/abs/1907.00528v1

    • [cs.CV]DeepTEGINN: Deep Learning Based Tools to Extract Graphs from Images of Neural Networks
    Gustavo Borges Moreno e Mello, Vibeke Devold Valderhaug, Sidney Pontes-Filho, Evi Zouganeli, Ioanna Sandvig, Stefano Nichele
    http://arxiv.org/abs/1907.01062v1

    • [cs.CV]Difficulty-aware Meta-Learning for Rare Disease Diagnosis
    Xiaomeng Li, Lequan Yu, Chi-Wing Fu, Pheng-Ann Heng
    http://arxiv.org/abs/1907.00354v1

    • [cs.CV]Diminishing the Effect of Adversarial Perturbations via Refining Feature Representation
    Nader Asadi, AmirMohammad Sarfi, Sahba Tahsini, Mahdi Eftekhari
    http://arxiv.org/abs/1907.01023v1

    • [cs.CV]Disentangled Makeup Transfer with Generative Adversarial Network
    Honglun Zhang, Wenqing Chen, Hao He, Yaohui Jin
    http://arxiv.org/abs/1907.01144v1

    • [cs.CV]Dynamic Face Video Segmentation via Reinforcement Learning
    Yujiang Wang, Jie Shen, Mingzhi Dong, Yang Wu, Shiyang Cheng, Maja Pantic
    http://arxiv.org/abs/1907.01296v1

    • [cs.CV]Estimating brain age based on a healthy population with deep learning and structural MRI
    Xinyang Feng, Zachary C. Lipton, Jie Yang, Scott A. Small, Frank A. Provenzano
    http://arxiv.org/abs/1907.00943v1

    • [cs.CV]FastDVDnet: Towards Real-Time Video Denoising Without Explicit Motion Estimation
    Matias Tassano, Julie Delon, Thomas Veit
    http://arxiv.org/abs/1907.01361v1

    • [cs.CV]Generative Guiding Block: Synthesizing Realistic Looking Variants Capable of Even Large Change Demands
    Minho Park, Hak Gu Kim, Yong Man Ro
    http://arxiv.org/abs/1907.01187v1

    • [cs.CV]Going Deeper with Point Networks
    Eric-Tuan Le, Iasonas Kokkinos, Niloy J. Mitra
    http://arxiv.org/abs/1907.00960v1

    • [cs.CV]HO-3D: A Multi-User, Multi-Object Dataset for Joint 3D Hand-Object Pose Estimation
    Shreyas Hampali, Markus Oberweger, Mahdi Rad, Vincent Lepetit
    http://arxiv.org/abs/1907.01481v1

    • [cs.CV]High-speed Railway Fastener Detection and Localization System
    Qing Song, Yao Guo, Lu Yang, Jianan Jiang, Chun Liu, Mengjie Hu
    http://arxiv.org/abs/1907.01141v1

    • [cs.CV]ICDAR 2019 Competition on Scene Text Visual Question Answering
    Ali Furkan Biten, Rubèn Tito, Andres Mafla, Lluis Gomez, Marçal Rusiñol, Minesh Mathew, C. V. Jawahar, Ernest Valveny, Dimosthenis Karatzas
    http://arxiv.org/abs/1907.00490v1

    • [cs.CV]ICDAR2019 Robust Reading Challenge on Multi-lingual Scene Text Detection and Recognition — RRC-MLT-2019
    Nibal Nayef, Yash Patel, Michal Busta, Pinaki Nath Chowdhury, Dimosthenis Karatzas, Wafa Khlif, Jiri Matas, Umapada Pal, Jean-Christophe Burie, Cheng-lin Liu, Jean-Marc Ogier
    http://arxiv.org/abs/1907.00945v1

    • [cs.CV]INN: Inflated Neural Networks for IPMN Diagnosis
    Rodney LaLonde, Irene Tanner, Katerina Nikiforaki, Georgios Z. Papadakis, Pujan Kandel, Candice W. Bolan, Michael B. Wallace, Ulas Bagci
    http://arxiv.org/abs/1907.00437v1

    • [cs.CV]Improving Borderline Adulthood Facial Age Estimation through Ensemble Learning
    Felix Anda, David Lillis, Aikaterini Kanta, Brett A. Becker, Elias Bou-Harb, Nhien-An Le-Khac, Mark Scanlon
    http://arxiv.org/abs/1907.01427v1

    • [cs.CV]Inverse Attention Guided Deep Crowd Counting Network
    Vishwanath A. Sindagi, Vishal M. Patel
    http://arxiv.org/abs/1907.01193v1

    • [cs.CV]Landmark Assisted CycleGAN for Cartoon Face Generation
    Ruizheng Wu, Xiaodong Gu, Xin Tao, Xiaoyong Shen, Yu-Wing Tai, Jiaya Jia
    http://arxiv.org/abs/1907.01424v1

    • [cs.CV]Lane Detection and Classification using Cascaded CNNs
    Fabio Pizzati, Marco Allodi, Alejandro Barrera, Fernando García
    http://arxiv.org/abs/1907.01294v1

    • [cs.CV]Language2Pose: Natural Language Grounded Pose Forecasting
    Chaitanya Ahuja, Louis-Philippe Morency
    http://arxiv.org/abs/1907.01108v1

    • [cs.CV]Large Area 3D Human Pose Detection Via Stereo Reconstruction in Panoramic Cameras
    Christoph Heindl, Thomas Pönitz, Andreas Pichler, Josef Scharinger
    http://arxiv.org/abs/1907.00534v1

    • [cs.CV]Large-scale, real-time visual-inertial localization revisited
    Simon Lynen, Bernhard Zeisl, Dror Aiger, Michael Bosse, Joel Hesch, Marc Pollefeys, Roland Siegwart, Torsten Sattler
    http://arxiv.org/abs/1907.00338v1

    • [cs.CV]Learnable Gated Temporal Shift Module for Deep Video Inpainting
    Ya-Liang Chang, Zhe Yu Liu, Kuan-Ying Lee, Winston Hsu
    http://arxiv.org/abs/1907.01131v1

    • [cs.CV]Learning Objectness from Sonar Images for Class-Independent Object Detection
    Matias Valdenegro-Toro
    http://arxiv.org/abs/1907.00734v1

    • [cs.CV]Learning to Approximate Directional Fields Defined over 2D Planes
    Maria Taktasheva, Albert Matveev, Alexey Artemov, Evgeny Burnaev
    http://arxiv.org/abs/1907.00559v1

    • [cs.CV]Learning to Blindly Assess Image Quality in the Laboratory and Wild
    Weixia Zhang, Kede Ma, Xiaokang Yang
    http://arxiv.org/abs/1907.00516v1

    • [cs.CV]Learning to Find Correlated Features by Maximizing Information Flow in Convolutional Neural Networks
    Wei Shen, Fei Li, Rujie Liu
    http://arxiv.org/abs/1907.00348v1

    • [cs.CV]Learning to Generate Synthetic 3D Training Data through Hybrid Gradient
    Dawei Yang, Jia Deng
    http://arxiv.org/abs/1907.00267v1

    • [cs.CV]Learning to aggregate feature representations
    Guy Gaziv
    http://arxiv.org/abs/1907.01034v1

    • [cs.CV]Multi-Cue Vehicle Detection for Semantic Video Compression In Georegistered Aerial Videos
    Noor Al-Shakarji, Filiz Bunyak, Hadi Aliakbarpour, Guna Seetharaman, Kannappan Palaniappan
    http://arxiv.org/abs/1907.01176v1

    • [cs.CV]Multi-scale Template Matching with Scalable Diversity Similarity in an Unconstrained Environment
    Yi Zhang, Chao Zhang, Takuya Akashi
    http://arxiv.org/abs/1907.01150v1

    • [cs.CV]Multiple Landmark Detection using Multi-Agent Reinforcement Learning
    Athanasios Vlontzos, Amir Alansary, Konstantinos Kamnitsas, Daniel Rueckert, Bernhard Kainz
    http://arxiv.org/abs/1907.00318v1

    • [cs.CV]Multiview Aggregation for Learning Category-Specific Shape Reconstruction
    Srinath Sridhar, Davis Rempe, Julien Valentin, Sofien Bouaziz, Leonidas J. Guibas
    http://arxiv.org/abs/1907.01085v1

    • [cs.CV]Nature Inspired Dimensional Reduction Technique for Fast and Invariant Visual Feature Extraction
    Ravimal Bandara, Lochandaka Ranathunga, Nor Aniza Abdullah
    http://arxiv.org/abs/1907.01102v1

    • [cs.CV]Obj-GloVe: Scene-Based Contextual Object Embedding
    Canwen Xu, Zhenzhong Chen, Chenliang Li
    http://arxiv.org/abs/1907.01478v1

    • [cs.CV]One Network for Multi-Domains: Domain Adaptive Hashing with Intersectant Generative Adversarial Network
    Tao He, Yuan-Fang Li, Lianli Gao, Dongxiang Zhang, Jingkuan Song
    http://arxiv.org/abs/1907.00612v1

    • [cs.CV]Online Multiple Pedestrian Tracking using Deep Temporal Appearance Matching Association
    Young-Chul Yoon, Du Yong Kim, Kwangjin Yoon, Young-min Song, Moongu Jeon
    http://arxiv.org/abs/1907.00831v1

    • [cs.CV]Pano Popups: Indoor 3D Reconstruction with a Plane-Aware Network
    Marc Eder, Pierre Moulon, Li Guan
    http://arxiv.org/abs/1907.00939v1

    • [cs.CV]Pathologist-Level Grading of Prostate Biopsies with Artificial Intelligence
    Peter Ström, Kimmo Kartasalo, Henrik Olsson, Leslie Solorzano, Brett Delahunt, Daniel M. Berney, David G. Bostwick, Andrew J. Evans, David J. Grignon, Peter A. Humphrey, Kenneth A. Iczkowski, James G. Kench, Glen Kristiansen, Theodorus H. van der Kwast, Katia R. M. Leite, Jesse K. McKenney, Jon Oxley, Chin-Chen Pan, Hemamali Samaratunga, John R. Srigley, Hiroyuki Takahashi, Toyonori Tsuzuki, Murali Varma, Ming Zhou, Johan Lindberg, Cecilia Bergström, Pekka Ruusuvuori, Carolina Wählby, Henrik Grönberg, Mattias Rantalainen, Lars Egevad, Martin Eklund
    http://arxiv.org/abs/1907.01368v1

    • [cs.CV]Permutohedral Attention Module for Efficient Non-Local Neural Networks
    Samuel Joutard, Reuben Dorent, Amanda Isaac, Sebastien Ourselin, Tom Vercauteren, Marc Modat
    http://arxiv.org/abs/1907.00641v1

    • [cs.CV]Predicting video saliency using crowdsourced mouse-tracking data
    Vitaliy Lyudvichenko, Dmitriy Vatolin
    http://arxiv.org/abs/1907.00480v1

    • [cs.CV]Procedure Planning in Instructional Videos
    Chien-Yi Chang, De-An Huang, Danfei Xu, Ehsan Adeli, Li Fei-Fei, Juan Carlos Niebles
    http://arxiv.org/abs/1907.01172v1

    • [cs.CV]Proposal, Tracking and Segmentation (PTS): A Cascaded Network for Video Object Segmentation
    Qiang Zhou, Zilong Huang, Xinggang Wang, Yongchao Gong, Han Shen, Lichao Huang, Chang Huang, Wenyu Liu
    http://arxiv.org/abs/1907.01203v1

    • [cs.CV]Random Vector Functional Link Neural Network based Ensemble Deep Learning
    Rakesh Katuwal, P. N. Suganthan, M. Tanveer
    http://arxiv.org/abs/1907.00350v1

    • [cs.CV]Semi-Bagging Based Deep Neural Architecture to Extract Text from High Entropy Images
    Pranay Dugar, Anirban Chatterjee, Rajesh Shreedhar Bhat, Saswata Sahoo
    http://arxiv.org/abs/1907.01284v1

    • [cs.CV]Spatio-thermal depth correction of RGB-D sensors based on Gaussian Processes in real-time
    Christoph Heindl, Thomas Pönitz, Gernot Stübl, Andreas Pichler, Josef Scharinger
    http://arxiv.org/abs/1907.00549v1

    • [cs.CV]Stereo relative pose from line and point feature triplets
    Alexander Vakhitov, Victor Lempitsky, Yinqiang Zheng
    http://arxiv.org/abs/1907.00276v1

    • [cs.CV]Symmetry Detection and Classification in Drawings of Graphs
    Felice De Luca, Md Iqbal Hossain, Stephen Kobourov
    http://arxiv.org/abs/1907.01004v1

    • [cs.CV]TedEval: A Fair Evaluation Metric for Scene Text Detectors
    Chae Young Lee, Youngmin Baek, Hwalsuk Lee
    http://arxiv.org/abs/1907.01227v1

    • [cs.CV]The Ethical Dilemma when (not) Setting up Cost-based Decision Rules in Semantic Segmentation
    Robin Chan, Matthias Rottmann, Radin Dardashti, Fabian Hüger, Peter Schlicht, Hanno Gottschalk
    http://arxiv.org/abs/1907.01342v1

    • [cs.CV]The Resale Price Prediction of Secondhand Jewelry Items Using a Multi-modal Deep Model with Iterative Co-Attention
    Yusuke Yamaura, Nobuya Kanemaki, Yukihiro Tsuboshita
    http://arxiv.org/abs/1907.00661v1

    • [cs.CV]Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-Shot Cross-Dataset Transfer
    Katrin Lasinger, René Ranftl, Konrad Schindler, Vladlen Koltun
    http://arxiv.org/abs/1907.01341v1

    • [cs.CV]Training Auto-encoder-based Optimizers for Terahertz Image Reconstruction
    Tak Ming Wong, Matthias Kahl, Peter Haring Bolívar, Andreas Kolb, Michael Möller
    http://arxiv.org/abs/1907.01377v1

    • [cs.CV]Unsupervised Deformable Image Registration Using Cycle-Consistent CNN
    Boah Kim, Jieun Kim, June-Goo Lee, Dong Hwan Kim, Seong Ho Park, Jong Chul Ye
    http://arxiv.org/abs/1907.01319v1

    • [cs.CV]Visual Space Optimization for Zero-shot Learning
    Xinsheng Wang, Shanmin Pang, Jihua Zhu, Zhongyu Li, Zhiqiang Tian, Yaochen Li
    http://arxiv.org/abs/1907.00330v1

    • [cs.CV]Where are the Masks: Instance Segmentation with Image-level Supervision
    Issam H. Laradji, David Vazquez, Mark Schmidt
    http://arxiv.org/abs/1907.01430v1

    • [cs.CV]XNect: Real-time Multi-person 3D Human Pose Estimation with a Single RGB Camera
    Dushyant Mehta, Oleksandr Sotnychenko, Franziska Mueller, Weipeng Xu, Mohamed Elgharib, Pascal Fua, Hans-Peter Seidel, Helge Rhodin, Gerard Pons-Moll, Christian Theobalt
    http://arxiv.org/abs/1907.00837v1

    • [cs.CY]Following wrong suggestions: self-blame in human and computer scenarios
    Andrea Beretta, Massimo Zancanaro, Bruno Lepri
    http://arxiv.org/abs/1907.00850v1

    • [cs.CY]Hidden in Plain Sight For Too Long: Using Text Mining Techniques to Shine a Light on Workplace Sexism and Sexual Harassment
    Amir Karami, Suzanne C. Swan, Cynthia Nicole White, Kayla Ford
    http://arxiv.org/abs/1907.00510v1

    • [cs.CY]Ich weiß, was du nächsten Sommer getan haben wirst: Predictive Policing in Österreich
    Angelika Adensamer, Lukas Daniel Klausner
    http://arxiv.org/abs/1907.00934v1

    • [cs.CY]Learning to Identify Patients at Risk of Uncontrolled Hypertension Using Electronic Health Records Data
    Ramin Mohammadi, Sarthak Jain, Stephen Agboola, Ramya Palacholla, Sagar Kamarthi, Byron C. Wallace
    http://arxiv.org/abs/1907.00089v1

    • [cs.CY]Proof of Witness Presence: Blockchain Consensus for Augmented Democracy in Smart Cities
    Evangelos Pournaras
    http://arxiv.org/abs/1907.00498v1

    • [cs.CY]What, When and Where of petitions submitted to the UK Government during a time of chaos
    Bertie Vidgen, Taha Yasseri
    http://arxiv.org/abs/1907.01536v1

    • [cs.CY]YouTube Chatter: Understanding Online Comments Discourse on Misinformative and Political YouTube Videos
    Aarash Heydari, Janny Zhang, Shaan Appel, Xinyi Wu, Gireeja Ranade
    http://arxiv.org/abs/1907.00435v1

    • [cs.DC]Asynchronous Communications Library for the Parallel-in-Time Solution of Black-Scholes Equation
    Qinmeng Zou, Guillaume Gbikpi-Benissan, Frederic Magoules
    http://arxiv.org/abs/1907.01199v1

    • [cs.DC]Asynchronous Parareal Algorithm Applied to European Option Pricing
    Qinmeng Zou, Guillaume Gbikpi-Benissan, Frederic Magoules
    http://arxiv.org/abs/1907.01198v1

    • [cs.DC]Bridging the Architecture Gap: Abstracting Performance-Relevant Properties of Modern Server Processors
    Johannes Hofmann, Christie L. Alappat, Georg Hager, Dietmar Fey, Gerhard Wellein
    http://arxiv.org/abs/1907.00048v1

    • [cs.DC]Convergence Detection of Asynchronous Iterations based on Modified Recursive Doubling
    Qinmeng Zou, Frederic Magoules
    http://arxiv.org/abs/1907.01201v1

    • [cs.DC]Creek: a General Mixed-Consistency Transactional Replication Scheme
    Tadeusz Kobus, Maciej Kokociński, Paweł T. Wojciechowski
    http://arxiv.org/abs/1907.00748v1

    • [cs.DC]Distributed-Memory Load Balancing with Cyclic Token-based Work-Stealing Applied to Reverse Time Migration
    Ítalo A. S. Assis, Antônio D. S. Oliveira, Tiago Barros, Idalmis M. Sardina, Calebe P. Bianchini, Samuel Xavier-de-Souza
    http://arxiv.org/abs/1907.00879v1

    • [cs.DC]Fully-Asynchronous Fully-Implicit Variable-Order Variable-Timestep Simulation of Neural Networks
    Bruno Magalhães, Michael Hines, Thomas Sterling, Felix Schuermann
    http://arxiv.org/abs/1907.00670v1

    • [cs.DC]Network-accelerated Distributed Machine Learning Using MLFabric
    Raajay Viswanathan, Aditya Akella
    http://arxiv.org/abs/1907.00434v1

    • [cs.DC]Open-MPI over MOSIX: paralleled computing in a clustered world
    Adam Lev-Libfeld, Alex Margolin, Amnon Barak
    http://arxiv.org/abs/1907.00194v1

    • [cs.DC]Parallel Performance of Molecular Dynamics Trajectory Analysis
    Mahzad Khoshlessan, Ioannis Paraskevakos, Geoffrey C. Fox, Shantenu Jha, Oliver Beckstein
    http://arxiv.org/abs/1907.00097v1

    • [cs.DC]Planting Trees for scalable and efficient Canonical Hub Labeling
    Kartik Lakhotia, Qing Dong, Rajgopal Kannan, Viktor Prasanna
    http://arxiv.org/abs/1907.00140v1

    • [cs.DC]State-of-the-Art on Query & Transaction Processing Acceleration
    Bernd Amann, Youry Khmelevsky, Gaetan Hains
    http://arxiv.org/abs/1907.00050v1

    • [cs.DC]Themis: Fair and Efficient GPU Cluster Scheduling for Machine Learning Workloads
    Kshiteej Mahajan, Arjun Singhvi, Arjun Balasubramanian, Varun Batra, Surya Teja Chavali, Shivaram Venkataraman, Aditya Akella, Amar Phanishayee, Shuchi Chawla
    http://arxiv.org/abs/1907.01484v1

    • [cs.DC]Understanding Fault Scenarios and Impacts through Fault Injection Experiments in Cielo
    Valerio Formicola, Saurabh Jha, Daniel Chen, Fei Deng, Amanda Bonnie, Mike Mason, Jim Brandt, Ann Gentile, Larry Kaplan, Jason Repik, Jeremy Enos, Mike Showerman, Annette Greiner, Zbigniew Kalbarczyk, Ravishankar K. Iyer, Bill Krammer
    http://arxiv.org/abs/1907.01019v1

    • [cs.DL]Infrastructure-Agnostic Hypertext
    Jakob Voß
    http://arxiv.org/abs/1907.00259v1

    • [cs.ET]Composable Rate-Independent Computation in Continuous Chemical Reaction Networks
    Cameron Chalk, Niels Kornerup, Wyatt Reeves, David Soloveichik
    http://arxiv.org/abs/1907.00053v1

    • [cs.HC]FVA: Modeling Perceived Friendliness of Virtual Agents Using Movement Characteristics
    Tanmay Randhavane, Aniket Bera, Kyra Kapsaskis, Kurt Gray, Dinesh Manocha
    http://arxiv.org/abs/1907.00377v1

    • [cs.HC]Simultaneous Achievement of Driver Assistance and Skill Development in Shared and Cooperative Controls
    Takahiro Wada
    http://arxiv.org/abs/1907.00802v1

    • [cs.IR]A Capsule Network for Recommendation and Explaining What You Like and Dislike
    Chenliang Li, Cong Quan, Li Peng, Yunwei Qi, Yuming Deng, Libing Wu
    http://arxiv.org/abs/1907.00687v1

    • [cs.IR]A Framework for Evaluating Snippet Generation for Dataset Search
    Xiaxia Wang, Jinchi Chen, Shuxin Li, Gong Cheng, Jeff Z. Pan, Evgeny Kharlamov, Yuzhong Qu
    http://arxiv.org/abs/1907.01183v1

    • [cs.IR]A Review-Driven Neural Model for Sequential Recommendation
    Chenliang Li, Xichuan Niu, Xiangyang Luo, Zhenzhong Chen, Cong Quan
    http://arxiv.org/abs/1907.00590v1

    • [cs.IR]Dermtrainer: A Decision Support System for Dermatological Diseases
    Gernot Salzer, Agata Ciabattoni, Christian Fermüller, Martin Haiduk, Harald Kittler, Arno Lukas, Rosa María Rodríguez Domínguez, Antonia Wesinger, Elisabeth Riedl
    http://arxiv.org/abs/1907.00635v1

    • [cs.IR]Effects of Foraging in Personalized Content-based Image Recommendation
    Amit Kumar Jaiswal, Haiming Liu, Ingo Frommholz
    http://arxiv.org/abs/1907.00483v1

    • [cs.IR]Extracting Novel Facts from Tables for Knowledge Graph Completion (Extended version)
    Benno Kruit, Peter Boncz, Jacopo Urbani
    http://arxiv.org/abs/1907.00083v1

    • [cs.IR]Learning to Reformulate the Queries on the WEB
    Amir H. Jadidinejad
    http://arxiv.org/abs/1907.01300v1

    • [cs.IR]Music Performance Analysis: A Survey
    Alexander Lerch, Claire Arthur, Ashis Pati, Siddharth Gururani
    http://arxiv.org/abs/1907.00178v1

    • [cs.IR]On Slicing Sorted Integer Sequences
    Giulio Ermanno Pibiri
    http://arxiv.org/abs/1907.01032v1

    • [cs.IR]One Size Does Not Fit All: Modeling Users’ Personal Curiosity in Recommender Systems
    Fakhri Abbas, Xi Niu
    http://arxiv.org/abs/1907.00119v1

    • [cs.IR]Prediction is very hard, especially about conversion. Predicting user purchases from clickstream data in fashion e-commerce
    Luca Bigon, Giovanni Cassani, Ciro Greco, Lucas Lacasa, Mattia Pavoni, Andrea Polonioli, Jacopo Tagliabue
    http://arxiv.org/abs/1907.00400v1

    • [cs.IR]Representation, Exploration and Recommendation of Music Playlists
    Piyush Papreja, Hemanth Venkateswara, Sethuraman Panchanathan
    http://arxiv.org/abs/1907.01098v1

    • [cs.IR]Semantic Driven Fielded Entity Retrieval
    Shahrzad Naseri, Sheikh Muhammad Sarwar, James Allan
    http://arxiv.org/abs/1907.01457v1

    • [cs.IR]Semantic Product Search
    Priyanka Nigam, Yiwei Song, Vijai Mohan, Vihan Lakshman, Weitian, Ding, Ankit Shingavi, Choon Hui Teo, Hao Gu, Bing Yin
    http://arxiv.org/abs/1907.00937v1

    • [cs.IT]“Machine LLRning”: Learning to Softly Demodulate
    Ori Shental, Jakob Hoydis
    http://arxiv.org/abs/1907.01512v1

    • [cs.IT]5G NR CA-Polar Maximum Likelihood Decoding by GRAND
    Ken Duffy, Amit Solomon, Kishori M. Konwar, Muriel Medard
    http://arxiv.org/abs/1907.01077v1

    • [cs.IT]A Direct Construction of Optimal ZCCS and IGC Code Set With Maximum Column Sequence PMEPR Two For MC-CDMA System
    Palash Sarkar, Sudhan Majhi
    http://arxiv.org/abs/1907.01308v1

    • [cs.IT]A Local Perspective on the Edge Removal Problem
    Fei Wei, Michael Langberg, Michelle Effros
    http://arxiv.org/abs/1907.01133v1

    • [cs.IT]Bundled Causal History Interaction
    Peishi Jiang, Praveen Kumar
    http://arxiv.org/abs/1907.01159v1

    • [cs.IT]From Parameter Estimation to Dispersion of Nonstationary Gauss-Markov Processes
    Peida Tian, Victoria Kostina
    http://arxiv.org/abs/1907.00304v1

    • [cs.IT]Mathematical Model of Emotional Habituation to Novelty: Modeling with Bayesian Update and Information Theory
    Takahiro Sekoguchi, Yuki Sakai, Hideyoshi Yanagisawa
    http://arxiv.org/abs/1907.01355v1

    • [cs.IT]Mismatched Guesswork
    Salman Salamatian, Litian Liu, Ahmad Beirami, Muriel Médard
    http://arxiv.org/abs/1907.00531v1

    • [cs.IT]On an Equivalence Between Single-Server PIR with Side Information and Locally Recoverable Codes
    Swanand Kadhe, Anoosheh Heidarzadeh, Alex Sprintson, O. Ozan Koyluoglu
    http://arxiv.org/abs/1907.00598v1

    • [cs.IT]On list decoding of 5G-NR polar codes
    Charles Pillet, Valerio Bioglio, Carlo Condo
    http://arxiv.org/abs/1907.00784v1

    • [cs.IT]On the Sample Complexity of HGR Maximal Correlation Functions
    Shao-Lun Huang, Xiangxiang Xu
    http://arxiv.org/abs/1907.00393v1

    • [cs.IT]On the list decodability of Rank Metric codes
    Rocco Trombetti, Ferdinando Zullo
    http://arxiv.org/abs/1907.01289v1

    • [cs.IT]Polar Codes with Memory
    Wenyue Zhou, Qiang Liu, Yifei Shen, Xiaofeng Zhou, Chuan Zhang, Yaohua Xu, Liping Li
    http://arxiv.org/abs/1907.00527v1

    • [cs.IT]Predictive Network Control in Multi-Connectivity Mobility for URLLC Services
    David Guzman, Richard Schoeffauer, Gerhard Wunder
    http://arxiv.org/abs/1907.01349v1

    • [cs.IT]Private Authentication with Physical Identifiers Through Broadcast Channel Measurements
    Onur Günlü, Rafael F. Schaefer, Gerhard Kramer
    http://arxiv.org/abs/1907.01081v1

    • [cs.IT]Quantization in Compressive Sensing: A Signal Processing Approach
    Isidora Stankovic, Milos Brajovic, Milos Dakovic, Cornel Ioana, Ljubisa Stankovic
    http://arxiv.org/abs/1907.01078v1

    • [cs.IT]Spatial Coded Modulation
    Junshan Luo, Shilian Wang, Fanggang Wang
    http://arxiv.org/abs/1907.00365v1

    • [cs.IT]Study of Rate-Splitting Techniques with Block Diagonalization for Multiuser MIMO Systems
    A. Flores, R. C. de Lamare
    http://arxiv.org/abs/1907.00386v1

    • [cs.IT]Trading Off Computation with Transmission in Status Update Systems
    Peng Zou, Omur Ozel, Suresh Subramaniam
    http://arxiv.org/abs/1907.00928v1

    • [cs.LG]A Framework For Identifying Group Behavior Of Wild Animals
    Guido Muscioni, Riccardo Pressiani, Matteo Foglio, Margaret C. Crofoot, Marco D. Santambrogio, Tanya Berger-Wolf
    http://arxiv.org/abs/1907.00932v1

    • [cs.LG]A Semi-Supervised Self-Organizing Map for Clustering and Classification
    Pedro H. M. Braga, Hansenclever F. Bassani
    http://arxiv.org/abs/1907.01070v1

    • [cs.LG]A Semi-Supervised Self-Organizing Map with Adaptive Local Thresholds
    Pedro H. M. Braga, Hansenclever F. Bassani
    http://arxiv.org/abs/1907.01086v1

    • [cs.LG]Active Learning within Constrained Environments through Imitation of an Expert Questioner
    Kalesha Bullard, Yannick Schroecker, Sonia Chernova
    http://arxiv.org/abs/1907.00921v1

    • [cs.LG]An Iteratively Re-weighted Method for Problems with Sparsity-Inducing Norms
    Feiping Nie, Zhanxuan Hu, Xiaoqian Wang, Rong Wang, Xuelong Li, Heng Huang
    http://arxiv.org/abs/1907.01121v1

    • [cs.LG]An Open Source AutoML Benchmark
    Pieter Gijsbers, Erin LeDell, Janek Thomas, Sébastien Poirier, Bernd Bischl, Joaquin Vanschoren
    http://arxiv.org/abs/1907.00909v1

    • [cs.LG]An aggregate learning approach for interpretable semi-supervised population prediction and disaggregation using ancillary data
    Guillaume Derval, Frédéric Docquier, Pierre Schaus
    http://arxiv.org/abs/1907.00270v1

    • [cs.LG]An innovative adaptive kriging approach for efficient binary classification of mechanical problems
    Jan N. Fuhg, Amelie Fau
    http://arxiv.org/abs/1907.01490v1

    • [cs.LG]Applying Transfer Learning To Deep Learned Models For EEG Analysis
    Axel Uran, Coert van Gemeren, Rosanne van Diepen, Ricardo Chavarriaga, José del R. Millán
    http://arxiv.org/abs/1907.01332v1

    • [cs.LG]Approximate Sherali-Adams Relaxations for MAP Inference via Entropy Regularization
    Jonathan N. Lee, Aldo Pacchiano, Michael I. Jordan
    http://arxiv.org/abs/1907.01127v1

    • [cs.LG]Astraea: Self-balancing Federated Learning for Improving Classification Accuracy of Mobile Deep Learning Applications
    Moming Duan
    http://arxiv.org/abs/1907.01132v1

    • [cs.LG]Augmenting Self-attention with Persistent Memory
    Sainbayar Sukhbaatar, Edouard Grave, Guillaume Lample, Herve Jegou, Armand Joulin
    http://arxiv.org/abs/1907.01470v1

    • [cs.LG]Avoiding Implementation Pitfalls of “Matrix Capsules with EM Routing” by Hinton et al
    Ashley Daniel Gritzman
    http://arxiv.org/abs/1907.00652v1

    • [cs.LG]Bandit Learning Through Biased Maximum Likelihood Estimation
    Xi Liu, Ping-Chun Hsieh, Anirban Bhattacharya, P. R. Kumar
    http://arxiv.org/abs/1907.01287v1

    • [cs.LG]Best k-layer neural network approximations
    Lek-Heng Lim, Mateusz Michalek, Yang Qi
    http://arxiv.org/abs/1907.01507v1

    • [cs.LG]Causal Inference Under Interference And Network Uncertainty
    Rohit Bhattacharya, Daniel Malinsky, Ilya Shpitser
    http://arxiv.org/abs/1907.00221v1

    • [cs.LG]Comment on “Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network”
    Roland S. Zimmermann
    http://arxiv.org/abs/1907.00895v1

    • [cs.LG]Conservative Q-Improvement: Reinforcement Learning for an Interpretable Decision-Tree Policy
    Aaron M. Roth, Nicholay Topin, Pooyan Jamshidi, Manuela Veloso
    http://arxiv.org/abs/1907.01180v1

    • [cs.LG]Continual Learning for Robotics
    Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat, Natalia Díaz-Rodríguez
    http://arxiv.org/abs/1907.00182v1

    • [cs.LG]Cosine similarity-based adversarial process
    Hee-Soo Heo, Jee-weon Jung, Hye-jin Shim, IL-Ho Yang, Ha-Jin Yu
    http://arxiv.org/abs/1907.00542v1

    • [cs.LG]Deep Multi-Task Learning for Anomalous Driving Detection Using CAN Bus Scalar Sensor Data
    Vidyasagar Sadhu, Teruhisa Misu, Dario Pompili
    http://arxiv.org/abs/1907.00749v1

    • [cs.LG]Deep Residual Neural Networks for Audio Spoofing Detection
    Moustafa Alzantot, Ziqi Wang, Mani B. Srivastava
    http://arxiv.org/abs/1907.00501v1

    • [cs.LG]Detecting Spiky Corruption in Markov Decision Processes
    Jason Mancuso, Tomasz Kisielewski, David Lindner, Alok Singh
    http://arxiv.org/abs/1907.00452v1

    • [cs.LG]Dissecting Pruned Neural Networks
    Jonathan Frankle, David Bau
    http://arxiv.org/abs/1907.00262v1

    • [cs.LG]Domain Adaptation via Low-Rank Basis Approximation
    Christoph Raab, Frank-Michael Schleif
    http://arxiv.org/abs/1907.01343v1

    • [cs.LG]Efficient Regularized Piecewise-Linear Regression Trees
    Leonidas Lefakis, Oleksandr Zadorozhnyi, Gilles Blanchard
    http://arxiv.org/abs/1907.00275v1

    • [cs.LG]Equation Discovery for Nonlinear System Identification
    Nikola Simidjievski, Ljupčo Todorovski, Juš Kocijan, Sašo Džeroski
    http://arxiv.org/abs/1907.00821v1

    • [cs.LG]Estimating Information-Theoretic Quantities with Random Forests
    Richard Guo, Cencheng Shen, Joshua Vogelstein
    http://arxiv.org/abs/1907.00325v1

    • [cs.LG]Exploiting Relevance for Online Decision-Making in High-Dimensions
    Eralp Turgay, Cem Bulucu, Cem Tekin
    http://arxiv.org/abs/1907.00783v1

    • [cs.LG]Exponential Separations in Local Differential Privacy Through Communication Complexity
    Matthew Joseph, Jieming Mao, Aaron Roth
    http://arxiv.org/abs/1907.00813v1

    • [cs.LG]FRODO: Free rejection of out-of-distribution samples: application to chest x-ray analysis
    Erdi Çallı, Keelin Murphy, Ecem Sogancioglu, Bram van Ginneken
    http://arxiv.org/abs/1907.01253v1

    • [cs.LG]FiDi-RL: Incorporating Deep Reinforcement Learning with Finite-Difference Policy Search for Efficient Learning of Continuous Control
    Longxiang Shi, Shijian Li, Longbing Cao, Long Yang, Gang Zheng, Gang Pan
    http://arxiv.org/abs/1907.00526v1

    • [cs.LG]Gaussian Mixture Marginal Distributions for Modelling Remaining Pipe Wall Thickness of Critical Water Mains in Non-Destructive Evaluation
    Linh Nguyen, Jaime Valls Miro, Lei Shi, Teresa Vidal-Calleja
    http://arxiv.org/abs/1907.01184v1

    • [cs.LG]Generalizing from a few environments in safety-critical reinforcement learning
    Zachary Kenton, Angelos Filos, Owain Evans, Yarin Gal
    http://arxiv.org/abs/1907.01475v1

    • [cs.LG]Improving LSTM Neural Networks for Better Short-Term Wind Power Predictions
    Maximilian Du
    http://arxiv.org/abs/1907.00489v1

    • [cs.LG]Isolation Kernel: The X Factor in Efficient and Effective Large Scale Online Kernel Learning
    Kai Ming Ting, Jonathan R. Wells, Takashi Washio
    http://arxiv.org/abs/1907.01104v1

    • [cs.LG]Learning Representations from Imperfect Time Series Data via Tensor Rank Regularization
    Paul Pu Liang, Zhun Liu, Yao-Hung Hubert Tsai, Qibin Zhao, Ruslan Salakhutdinov, Louis-Philippe Morency
    http://arxiv.org/abs/1907.01011v1

    • [cs.LG]Learning World Graphs to Accelerate Hierarchical Reinforcement Learning
    Wenling Shang, Alex Trott, Stephan Zheng, Caiming Xiong, Richard Socher
    http://arxiv.org/abs/1907.00664v1

    • [cs.LG]Learning the Arrow of Time
    Nasim Rahaman, Steffen Wolf, Anirudh Goyal, Roman Remme, Yoshua Bengio
    http://arxiv.org/abs/1907.01285v1

    • [cs.LG]Learning to Traverse Latent Spaces for Musical Score Inpainting
    Ashis Pati, Alexander Lerch, Gaëtan Hadjeres
    http://arxiv.org/abs/1907.01164v1

    • [cs.LG]Location Anomalies Detection for Connected and Autonomous Vehicles
    Xiaoyang Wang, Ioannis Mavromatis, Andrea Tassi, Raul Santos-Rodriguez, Robert J. Piechocki
    http://arxiv.org/abs/1907.00811v1

    • [cs.LG]ML-based Fault Injection for Autonomous Vehicles: A Case for Bayesian Fault Injection
    Saurabh Jha, Subho S. Banerjee, Timothy Tsai, Siva K. S. Hari, Michael B. Sullivan, Zbigniew T. Kalbarczyk, Stephen W. Keckler, Ravishankar K. Iyer
    http://arxiv.org/abs/1907.01051v1

    • [cs.LG]MULEX: Disentangling Exploitation from Exploration in Deep RL
    Lucas Beyer, Damien Vincent, Olivier Teboul, Sylvain Gelly, Matthieu Geist, Olivier Pietquin
    http://arxiv.org/abs/1907.00868v1

    • [cs.LG]Mechanisms of Artistic Creativity in Deep Learning Neural Networks
    Lonce Wyse
    http://arxiv.org/abs/1907.00321v1

    • [cs.LG]Mincut pooling in Graph Neural Networks
    Filippo Maria Bianchi, Daniele Grattarola, Cesare Alippi
    http://arxiv.org/abs/1907.00481v1

    • [cs.LG]Mixed-Variable Bayesian Optimization
    Erik Daxberger, Anastasia Makarova, Matteo Turchetta, Andreas Krause
    http://arxiv.org/abs/1907.01329v1

    • [cs.LG]Modeling Tabular data using Conditional GAN
    Lei Xu, Maria Skoularidou, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
    http://arxiv.org/abs/1907.00503v1

    • [cs.LG]Modified Actor-Critics
    Erinc Merdivan, Sten Hanke, Matthieu Geist
    http://arxiv.org/abs/1907.01298v1

    • [cs.LG]Multi-Label Product Categorization Using Multi-Modal Fusion Models
    Pasawee Wirojwatanakul, Artit Wangperawong
    http://arxiv.org/abs/1907.00420v1

    • [cs.LG]Multiplicative Models for Recurrent Language Modeling
    Diego Maupomé, Marie-Jean Meurs
    http://arxiv.org/abs/1907.00455v1

    • [cs.LG]Nearest-Neighbour-Induced Isolation Similarity and its Impact on Density-Based Clustering
    Xiaoyu Qin, Kai Ming Ting, Ye Zhu, Vincent CS Lee
    http://arxiv.org/abs/1907.00378v1

    • [cs.LG]Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks
    Qi She, Anqi Wu
    http://arxiv.org/abs/1907.00650v1

    • [cs.LG]Neural Logic Rule Layers
    Jan Niclas Reimann, Andreas Schwung
    http://arxiv.org/abs/1907.00878v1

    • [cs.LG]On Symmetry and Initialization for Neural Networks
    Ido Nachum, Amir Yehudayoff
    http://arxiv.org/abs/1907.00560v1

    • [cs.LG]On mechanisms for transfer using landmark value functions in multi-task lifelong reinforcement learning
    Nick Denis
    http://arxiv.org/abs/1907.00884v1

    • [cs.LG]Open Problem: The Oracle Complexity of Convex Optimization with Limited Memory
    Blake Woodworth, Nathan Srebro
    http://arxiv.org/abs/1907.00762v1

    • [cs.LG]Operationalizing Individual Fairness with Pairwise Fair Representations
    Preethi Lahoti, Krishna P. Gummadi, Gerhard Weikum
    http://arxiv.org/abs/1907.01439v1

    • [cs.LG]Predicting Treatment Initiation from Clinical Time Series Data via Graph-Augmented Time-Sensitive Model
    Fan Zhang, Tong Wu, Yunlong Wang, Yong Cai, Cao Xiao, Emily Zhao, Lucas Glass, Jimeng Sun
    http://arxiv.org/abs/1907.01099v1

    • [cs.LG]Progressive Fashion Attribute Extraction
    Sandeep Singh Adhikari, Sukhneer Singh, Anoop Rajagopal, Aruna Rajan
    http://arxiv.org/abs/1907.00157v1

    • [cs.LG]Rare Disease Detection by Sequence Modeling with Generative Adversarial Networks
    Kezi Yu, Yunlong Wang, Yong Cai, Cao Xiao, Emily Zhao, Lucas Glass, Jimeng Sun
    http://arxiv.org/abs/1907.01022v1

    • [cs.LG]Reproducibility in Machine Learning for Health
    Matthew B. A. McDermott, Shirly Wang, Nikki Marinsek, Rajesh Ranganath, Marzyeh Ghassemi, Luca Foschini
    http://arxiv.org/abs/1907.01463v1

    • [cs.LG]Robust Tensor Completion Using Transformed Tensor SVD
    Guangjing Song, Michael K. Ng, Xiongjun Zhang
    http://arxiv.org/abs/1907.01113v1

    • [cs.LG]Robust and Resource Efficient Identification of Two Hidden Layer Neural Networks
    Massimo Fornasier, Timo Klock, Michael Rauchensteiner
    http://arxiv.org/abs/1907.00485v1

    • [cs.LG]Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points
    Zhibin Li, Jian Zhang, Qiang Wu, Yongshun Gong, Jinfeng Yi, Christina Kirsch
    http://arxiv.org/abs/1907.01162v1

    • [cs.LG]Single-Path Mobile AutoML: Efficient ConvNet Design and NAS Hyperparameter Optimization
    Dimitrios Stamoulis, Ruizhou Ding, Di Wang, Dimitrios Lymberopoulos, Bodhi Priyantha, Jie Liu, Diana Marculescu
    http://arxiv.org/abs/1907.00959v1

    • [cs.LG]Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model
    Alex X. Lee, Anusha Nagabandi, Pieter Abbeel, Sergey Levine
    http://arxiv.org/abs/1907.00953v1

    • [cs.LG]The Ramanujan Machine: Automatically Generated Conjectures on Fundamental Constants
    Gal Raayoni, George Pisha, Yahel Manor, Uri Mendlovic, Doron Haviv, Yaron Hadad, Ido Kaminer
    http://arxiv.org/abs/1907.00205v1

    • [cs.LG]The Sensitivity of Counterfactual Fairness to Unmeasured Confounding
    Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva
    http://arxiv.org/abs/1907.01040v1

    • [cs.LG]The SpectACl of Nonconvex Clustering: A Spectral Approach to Density-Based Clustering
    Sibylle Hess, Wouter Duivesteijn, Philipp Honysz, Katharina Morik
    http://arxiv.org/abs/1907.00680v1

    • [cs.LG]The Trustworthy Pal: Controlling the False Discovery Rate in Boolean Matrix Factorization
    Sibylle Hess, Nico Piatkowski, Katharina Morik
    http://arxiv.org/abs/1907.00697v1

    • [cs.LG]Tight Sensitivity Bounds For Smaller Coresets
    Alaa Maalouf, Adiel Statman, Dan Feldman
    http://arxiv.org/abs/1907.01433v1

    • [cs.LG]Treant: Training Evasion-Aware Decision Trees
    Stefano Calzavara, Claudio Lucchese, Gabriele Tolomei, Seyum Assefa Abebe, Salvatore Orlando
    http://arxiv.org/abs/1907.01197v1

    • [cs.LG]Two-stage Optimization for Machine Learning Workflow
    Alexandre Quemy
    http://arxiv.org/abs/1907.00678v1

    • [cs.LG]Understanding Memory Modules on Learning Simple Algorithms
    Kexin Wang, Yu Zhou, Shaonan Wang, Jiajun Zhang, Chengqing Zong
    http://arxiv.org/abs/1907.00820v1

    • [cs.LG]Universal audio synthesizer control with normalizing flows
    Philippe Esling, Naotake Masuda, Adrien Bardet, Romeo Despres, Axel Chemla—Romeu-Santos
    http://arxiv.org/abs/1907.00971v1

    • [cs.LG]Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments
    Bashar Alhnaity, Simon Pearson, Georgios Leontidis, Stefanos Kollias
    http://arxiv.org/abs/1907.00624v1

    • [cs.LG]Variational Quantum Circuits and Deep Reinforcement Learning
    Samuel Yen-Chi Chen, Hsi-Sheng Goan
    http://arxiv.org/abs/1907.00397v1

    • [cs.LG]Voting-Based Multi-Agent Reinforcement Learning
    Yue Xu, Zengde Deng, Mengdi Wang, Wenjun Xu, Anthony Man-Cho So, Shuguang Cui
    http://arxiv.org/abs/1907.01385v1

    • [cs.LG]Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog
    Natasha Jaques, Asma Ghandeharioun, Judy Hanwen Shen, Craig Ferguson, Agata Lapedriza, Noah Jones, Shixiang Gu, Rosalind Picard
    http://arxiv.org/abs/1907.00456v1

    • [cs.LG]Weight Normalization based Quantization for Deep Neural Network Compression
    Wen-Pu Cai, Wu-Jun Li
    http://arxiv.org/abs/1907.00593v1

    • [cs.LG]iPool — Information-based Pooling in Hierarchical Graph Neural Networks
    Xing Gao, Hongkai Xiong, Pascal Frossard
    http://arxiv.org/abs/1907.00832v1

    • [cs.MA]Collaboration of AI Agents via Cooperative Multi-Agent Deep Reinforcement Learning
    Niranjan Balachandar, Justin Dieter, Govardana Sachithanandam Ramachandran
    http://arxiv.org/abs/1907.00327v1

    • [cs.MM]Adaptive Music Composition for Games
    Patrick Hutchings, Jon McCormack
    http://arxiv.org/abs/1907.01154v1

    • [cs.MS]GPU-based Parallel Computation Support for Stan
    Rok Češnovar, Steve Bronder, Davor Sluga, Jure Demšar, Tadej Ciglarič, Sean Talts, Erik Štrumbelj
    http://arxiv.org/abs/1907.01063v1

    • [cs.MS]Solving Polynomial Systems with phcpy
    Jasmine Otto, Angus Forbes, Jan Verschelde
    http://arxiv.org/abs/1907.00096v1

    • [cs.NE]A Hybrid Learning Rule for Efficient and Rapid Inference with Spiking Neural Networks
    Jibin Wu, Yansong Chua, Malu Zhang, Guoqi Li, Haizhou Li, Kay Chen Tan
    http://arxiv.org/abs/1907.01167v1

    • [cs.NE]A Note On The Popularity of Stochastic Optimization Algorithms in Different Fields: A Quantitative Analysis from 2007 to 2017
    Son Duy Dao
    http://arxiv.org/abs/1907.01453v1

    • [cs.NE]ACM-DE: Adaptive p-best Cauchy Mutation with linear failure threshold reduction for Differential Evolution in numerical optimization
    Tae Jong Choi, Julian Togelius, Yun-Gyung Cheong
    http://arxiv.org/abs/1907.01095v1

    • [cs.NE]Multi-objective multi-generation Gaussian process optimizer for design optimization
    Xiaobiao Huang
    http://arxiv.org/abs/1907.00250v1

    • [cs.NE]On-chip learning in a conventional silicon MOSFET based Analog Hardware Neural Network
    Nilabjo Dey, Janak Sharda, Utkarsh Saxena, Divya Kaushik, Utkarsh Singh, Debanjan Bhowmik
    http://arxiv.org/abs/1907.00625v1

    • [cs.NI]Service-based Routing at the Edge
    Dirk Trossen, Sebastian Robitzsch, Scott Hergenhan, Janne Riihijarvi, Martin Reed, Mays Al-Naday
    http://arxiv.org/abs/1907.01293v1

    • [cs.RO]A Joint Optimization Approach of LiDAR-Camera Fusion for Accurate Dense 3D Reconstructions
    Weikun Zhen, Yaoyu Hu, Jingfeng Liu, Sebastian Scherer
    http://arxiv.org/abs/1907.00930v1

    • [cs.RO]Active Learning of Probabilistic Movement Primitives
    Adam Conkey, Tucker Hermans
    http://arxiv.org/abs/1907.00277v1

    • [cs.RO]Asynchronous Behavior Trees with Memory aimed at Aerial Vehicles with Redundancy in Flight Controller
    Evgenii Safronov, Michael Vilzmann, Dzmitry Tsetserukou, Konstantin Kondak
    http://arxiv.org/abs/1907.00253v1

    • [cs.RO]GarmNet: Improving Global with Local Perception for Robotic Laundry Folding
    Daniel Fernandes Gomes, Shan Luo, Luis F. Teixeira
    http://arxiv.org/abs/1907.00408v1

    • [cs.RO]Memory of Motion for Warm-starting Trajectory Optimization
    Teguh Santoso Lembono, Antonio Paolillo, Emmanuel Pignat, Sylvain Calinon
    http://arxiv.org/abs/1907.01474v1

    • [cs.RO]Model-free Friction Observers for Flexible Joint Robots with Torque Measurements
    Min Jun Kim, Fabian Beck, Christian Ott, Alin Albu-Schaeffer
    http://arxiv.org/abs/1907.00553v1

    • [cs.RO]Neural Semantic Parsing with Anonymization for Command Understanding in General-Purpose Service Robots
    Nick Walker, Yu-Tang Peng, Maya Cakmak
    http://arxiv.org/abs/1907.01115v1

    • [cs.RO]On Training Flexible Robots using Deep Reinforcement Learning
    Zach Dwiel, Madhavun Candadai, Mariano Phielipp
    http://arxiv.org/abs/1907.00269v1

    • [cs.RO]Persistent Multi-UAV Surveillance with Data Latency Constraints
    Jürgen Scherer, Bernhard Rinner
    http://arxiv.org/abs/1907.01205v1

    • [cs.RO]ROS 2 for RoboCup
    Marcus M. Scheunemann, Sander G. van Dijk
    http://arxiv.org/abs/1907.00282v1

    • [cs.RO]Robust and Efficient Quadrotor Trajectory Generation for Fast Autonomous Flight
    Boyu Zhou, Fei Gao, Luqi Wang, Chuhao Liu, Shaojie Shen
    http://arxiv.org/abs/1907.01531v1

    • [cs.RO]Teach-Repeat-Replan: A Complete and Robust System for Aggressive Flight in Complex Environments
    Fei Gao, Luqi Wang, Boyu Zhou, Luxin Han, Jie Pan, Shaojie Shen
    http://arxiv.org/abs/1907.00520v1

    • [cs.RO]Toward Asymptotically-Optimal Inspection Planning via Efficient Near-Optimal Graph Search
    Mengyu Fu, Alan Kuntz, Oren Salzman, Ron Alterovitz
    http://arxiv.org/abs/1907.00506v1

    • [cs.SD]Can a Robot Hear the Shape and Dimensions of a Room?
    Linh Nguyen, Jaime Valls Miro, Xiaojun Qiu
    http://arxiv.org/abs/1907.01169v1

    • [cs.SD]Kite: Automatic speech recognition for unmanned aerial vehicles
    Dan Oneata, Horia Cucu
    http://arxiv.org/abs/1907.01195v1

    • [cs.SD]WHAM!: Extending Speech Separation to Noisy Environments
    Gordon Wichern, Joe Antognini, Michael Flynn, Licheng Richard Zhu, Emmett McQuinn, Dwight Crow, Ethan Manilow, Jonathan Le Roux
    http://arxiv.org/abs/1907.01160v1

    • [cs.SE]A Scalable Architecture for Power Consumption Monitoring in Industrial Production Environments
    Sören Henning, Wilhelm Hasselbring, Armin Möbius
    http://arxiv.org/abs/1907.01046v1

    • [cs.SI]A Semantic Approach for User-Brand Targeting in On-Line Social Networks
    Mariella Bonomo, Gaspare Ciaccio, Andrea De Salve, Simona E. Rombo
    http://arxiv.org/abs/1907.01326v1

    • [cs.SI]Generalized Random Surfer-Pair Models
    Sai Kiran Narayanaswami, Balaraman Ravindran, Venkatesh Ramaiyan
    http://arxiv.org/abs/1907.01420v1

    • [cs.SI]Predicting the Topical Stance of Media and Popular Twitter Users
    Peter Stefanov, Kareem Darwish, Preslav Nakov
    http://arxiv.org/abs/1907.01260v1

    • [cs.SI]Unsupervised Adversarial Graph Alignment with Graph Embedding
    Chaoqi Chen, Weiping Xie, Tingyang Xu, Yu Rong, Wenbing Huang, Xinghao Ding, Yue Huang, Junzhou Huang
    http://arxiv.org/abs/1907.00544v1

    • [econ.EM]Permutation inference with a finite number of heterogeneous clusters
    Andreas Hagemann
    http://arxiv.org/abs/1907.01049v1

    • [eess.AS]Comparison of Lattice-Free and Lattice-Based Sequence Discriminative Training Criteria for LVCSR
    Wilfried Michel, Ralf Schlüter, Hermann Ney
    http://arxiv.org/abs/1907.01409v1

    • [eess.AS]Improving Performance of End-to-End ASR on Numeric Sequences
    Cal Peyser, Hao Zhang, Tara N. Sainath, Zelin Wu
    http://arxiv.org/abs/1907.01372v1

    • [eess.AS]LSTM Language Models for LVCSR in First-Pass Decoding and Lattice-Rescoring
    Eugen Beck, Wei Zhou, Ralf Schlüter, Hermann Ney
    http://arxiv.org/abs/1907.01030v1

    • [eess.AS]Speaker-independent classification of phonetic segments from raw ultrasound in child speech
    Manuel Sam Ribeiro, Aciel Eshky, Korin Richmond, Steve Renals
    http://arxiv.org/abs/1907.01413v1

    • [eess.AS]Ultrasound tongue imaging for diarization and alignment of child speech therapy sessions
    Manuel Sam Ribeiro, Aciel Eshky, Korin Richmond, Steve Renals
    http://arxiv.org/abs/1907.00818v1

    • [eess.IV]An Efficient Solution for Breast Tumor Segmentation and Classification in Ultrasound Images Using Deep Adversarial Learning
    Vivek Kumar Singh, Hatem A. Rashwan, Mohamed Abdel-Nasser, Md. Mostafa Kamal Sarker, Farhan Akram, Nidhi Pandey, Santiago Romani, Domenec Puig
    http://arxiv.org/abs/1907.00887v1

    • [eess.IV]Automated Image Registration Quality Assessment Utilizing Deep-learning based Ventricle Extraction in Clinical Data
    Florian Dubost, Marleen de Bruijne, Marco Nardin, Adrian V. Dalca, Kathleen L. Donahue, Anne-Katrin Giese, Mark R. Etherton, Ona Wu, Marius de Groot, Wiro Niessen, Meike Vernooij, Natalia S. Rost, Markus D. Schirmer
    http://arxiv.org/abs/1907.00695v1

    • [eess.IV]Bayesian Optimization on Large Graphs via a Graph Convolutional Generative Model: Application in Cardiac Model Personalization
    Jwala Dhamala, Sandesh Ghimire, John L. Sapp, B. Milan Horacek, Linwei Wang
    http://arxiv.org/abs/1907.01406v1

    • [eess.IV]Conditional Segmentation in Lieu of Image Registration
    Yipeng Hu, Eli Gibson, Dean C. Barratt, Mark Emberton, J. Alison Noble, Tom Vercauteren
    http://arxiv.org/abs/1907.00438v1

    • [eess.IV]Dual Network Architecture for Few-view CT —Trained on ImageNet Data and Transferred for Medical Imaging
    Huidong Xie, Hongming Shan, Wenxiang Cong, Xiaohua Zhang, Shaohua Liu, Ruola Ning, Ge Wang
    http://arxiv.org/abs/1907.01262v1

    • [eess.IV]Generative Mask Pyramid Network forCT/CBCT Metal Artifact Reduction with Joint Projection-Sinogram Correction
    Haofu Liao, Wei-An Lin, Zhimin Huo, Levon Vogelsang, William J. Sehnert, S. Kevin Zhou, Jiebo Luo
    http://arxiv.org/abs/1907.00294v1

    • [eess.IV]Global Transformer U-Nets for Label-Free Prediction of Fluorescence Images
    Yi Liu, Hao Yuan, Zhengyang Wang, Shuiwang Ji
    http://arxiv.org/abs/1907.00941v2

    • [eess.IV]Improving the generalizability of convolutional neural network-based segmentation on CMR images
    Chen Chen, Wenjia Bai, Rhodri H. Davies, Anish N. Bhuva, Charlotte Manisty, James C. Moon, Nay Aung, Aaron M. Lee, Mihir M. Sanghvi, Kenneth Fung, Jose Miguel Paiva, Steffen E. Petersen, Elena Lukaschuk, Stefan K. Piechnik, Stefan Neubauer, Daniel Rueckert
    http://arxiv.org/abs/1907.01268v1

    • [eess.IV]MobileGAN: Skin Lesion Segmentation Using a Lightweight Generative Adversarial Network
    Md. Mostafa Kamal Sarker, Hatem A. Rashwan, Mohamed Abdel-Nasser, Vivek Kumar Singh, Syeda Furruka Banu, Farhan Akram, Forhad U H Chowdhury, Kabir Ahmed Choudhury, Sylvie Chambon, Petia Radeva, Domenec Puig
    http://arxiv.org/abs/1907.00856v1

    • [eess.IV]Multi-scale GANs for Memory-efficient Generation of High Resolution Medical Images
    Hristina Uzunova, Fabian Jacob, Alex Frydrychowicz, Heinz Handels, Jan Ehrhardt
    http://arxiv.org/abs/1907.01376v1

    • [eess.IV]SLAM Endoscopy enhanced by adversarial depth prediction
    Richard J. Chen, Taylor L. Bobrow, Thomas Athey, Faisal Mahmood, Nicholas J. Durr
    http://arxiv.org/abs/1907.00283v1

    • [eess.IV]Seismic data denoising and deblending using deep learning
    Alan Richardson, Caelen Feller
    http://arxiv.org/abs/1907.01497v1

    • [eess.IV]Self-supervised Hyperspectral Image Restoration using Separable Image Prior
    Ryuji Imamura, Tatsuki Itasaka, Masahiro Okuda
    http://arxiv.org/abs/1907.00651v1

    • [eess.IV]Signed Laplacian Deep Learning with Adversarial Augmentation for Improved Mammography Diagnosis
    Heyi Li, Dongdong Chen, William H. Nailon, Mike E. Davies, David I. Laurenson
    http://arxiv.org/abs/1907.00300v1

    • [eess.SP]Base Station Antenna Selection for Low-Resolution ADC Systems
    Jinseok Choi, Junmo Sung, Narayan Prasad, Xiao-Feng Qi, Brian L. Evans, Alan Gatherer
    http://arxiv.org/abs/1907.00482v1

    • [eess.SP]Beam Allocation for Millimeter-Wave MIMO Tracking Systems
    Deyou Zhang, Ang Li, He Chen, Ning Wei, Ming Ding, Yonghui Li, Branka Vucetic
    http://arxiv.org/abs/1907.00538v1

    • [eess.SP]Deep Learning for Hybrid 5G Services in Mobile Edge Computing Systems: Learn from a Digital Twin
    Rui Dong, Changyang She, Wibowo Hardjawana, Yonghui Li, Branka Vucetic
    http://arxiv.org/abs/1907.01523v1

    • [eess.SP]Improved Circuit Design of Analog Joint Source Channel Coding for Low-power and Low-complexity Wireless Sensors
    Xueyuan Zhao, Vidyasagar Sadhu, Anthony Yang, Dario Pompili
    http://arxiv.org/abs/1907.01442v1

    • [eess.SY]Automatic Real-time Anomaly Detection for Autonomous Aerial Vehicles
    Azarakhsh Keipour, Mohammadreza Mousaei, Sebastian Scherer
    http://arxiv.org/abs/1907.00511v1

    • [eess.SY]Distributed Global Output-Feedback Control for a Class of Euler-Lagrange Systems
    Qingkai Yang, Hao Fang, Jie Chen, Zhong-Ping Jiang, Ming Cao
    http://arxiv.org/abs/1907.00220v1

    • [math.HO]Male Under-performance in Undergraduate Engineering Mathematical Courses: Causes and Solution Strategy
    Luai Al Labadi, Hishyar Khalil, Nida Siddiqui
    http://arxiv.org/abs/1907.00552v1

    • [math.NA]A data-driven approach for multiscale elliptic PDEs with random coefficients based on intrinsic dimension reduction
    Sijing Li, Zhiwen Zhang, Hongkai Zhao
    http://arxiv.org/abs/1907.00806v1

    • [math.NA]Lossy Compression for Large Scale PDE Problems
    Sebastian Götschel, Martin Weiser
    http://arxiv.org/abs/1907.00667v1

    • [math.OC]Competitive Algorithms for Online Budget-Constrained Continuous DR-Submodular Problems
    Omid Sadeghi, Reza Eghbali, Maryam Fazel
    http://arxiv.org/abs/1907.00312v1

    • [math.OC]Conjugate Gradients and Accelerated Methods Unified: The Approximate Duality Gap View
    Jelena Diakonikolas, Lorenzo Orecchia
    http://arxiv.org/abs/1907.00289v1

    • [math.OC]Efficient Algorithms for Smooth Minimax Optimization
    Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh
    http://arxiv.org/abs/1907.01543v1

    • [math.OC]Online Continuous DR-Submodular Maximization with Long-Term Budget Constraints
    Omid Sadeghi, Maryam Fazel
    http://arxiv.org/abs/1907.00316v1

    • [math.OC]The Constrained $L_p$-$L_q$ Basis Pursuit Denoising Problem
    Lei Yang, Xiaojun Chen, Shuhuang Xiang
    http://arxiv.org/abs/1907.00880v1

    • [math.PR]Constrained Monte Carlo Markov Chains on Graphs
    Roy Cerqueti, Emilio De Santis
    http://arxiv.org/abs/1907.00779v1

    • [math.ST]A New Lower Bound for Kullback-Leibler Divergence Based on Hammersley-Chapman-Robbins Bound
    Tomohiro Nishiyama
    http://arxiv.org/abs/1907.00288v1

    • [math.ST]A greedy algorithm for sparse precision matrix approximation
    Didi Lv, Xiaoqun Zhang
    http://arxiv.org/abs/1907.00723v1

    • [math.ST]Bounding Causes of Effects with Mediators
    Philip Dawid, Macartan Humphreys, Monica Musio
    http://arxiv.org/abs/1907.00399v1

    • [math.ST]Elicitability and Identifiability of Systemic Risk Measures and other Set-Valued Functionals
    Tobias Fissler, Jana Hlavinová, Birgit Rudloff
    http://arxiv.org/abs/1907.01306v1

    • [math.ST]Geodesic Distance Estimation with Spherelets
    Didong Li, David B Dunson
    http://arxiv.org/abs/1907.00296v1

    • [math.ST]Large-scale inference with block structure
    Jiyao Kou, Guenther Walther
    http://arxiv.org/abs/1907.00085v1

    • [math.ST]Multidimensional Scaling on Metric Measure Spaces
    Henry Adams, Mark Blumstein, Lara Kassab
    http://arxiv.org/abs/1907.01379v1

    • [math.ST]Multiple Bayesian Filtering as Message Passing
    Giorgio M. Vitetta, Pasquale Di Viesti, Emilio Sirignano, Francesco Montorsi
    http://arxiv.org/abs/1907.01358v1

    • [math.ST]Power Lindley distribution and software metrics
    Mohammed Khalleefah, Sofiya Ostrovska, Mehmet Turan
    http://arxiv.org/abs/1907.00668v1

    • [math.ST]Robust analogues to the Coefficient of Variation
    Chandima N. P. G. Arachchige, Luke A. Prendergast, Robert G. Staudte
    http://arxiv.org/abs/1907.01110v1

    • [math.ST]Specification testing in semi-parametric transformation models
    Nick Kloodt, Natalie Neumeyer, Ingrid Van Keilegom
    http://arxiv.org/abs/1907.01223v1

    • [math.ST]Statistical estimation of the Kullback-Leibler divergence
    Alexander Bulinski, Denis Dimitrov
    http://arxiv.org/abs/1907.00196v1

    • [math.ST]The generalized orthogonal Procrustes problem in the high noise regime
    Thomas Pumir, Amit Singer, Nicolas Boumal
    http://arxiv.org/abs/1907.01145v1

    • [physics.chem-ph]Automatic Routing of Goldstone Diagrams using Genetic Algorithms
    Nils Herrmann, Michael Hanrath
    http://arxiv.org/abs/1907.00426v1

    • [physics.chem-ph]Predicting Retrosynthetic Reaction using Self-Corrected Transformer Neural Networks
    Shuangjia Zheng, Jiahua Rao, Zhongyue Zhang, Jun Xu, Yuedong Yang
    http://arxiv.org/abs/1907.01356v1

    • [physics.soc-ph]Identifying vital nodes based on reverse greedy method
    Tao Ren, Zhe Li, Yi Qi, Yixin Zhang, Simiao Liu, Yanjie Xu, Tao Zhou
    http://arxiv.org/abs/1907.01388v1

    • [physics.soc-ph]Influence measures in subnetworks using vertex centrality
    Roy Cerqueti, Gian Paolo Clemente, Rosanna Grassi
    http://arxiv.org/abs/1907.00431v1

    • [physics.soc-ph]Instability of social network dynamics with stubborn links
    Somaye Sheykhali, Amir Hossein Darooneh, Gholam Reza Jafari
    http://arxiv.org/abs/1907.00352v1

    • [physics.soc-ph]The Role of Network Structure and Initial Group Norm Distributions in Norm Conflict
    Julian Kohne, Natalie Gallagher, Zeynep Melis Kirgil, Rocco Paolillo, Lars Padmos, Fariba Karimi
    http://arxiv.org/abs/1907.00888v1

    • [q-bio.BM]Molecular activity prediction using graph convolutional deep neural network considering distance on a molecular graph
    Masahito Ohue, Ryota Ii, Keisuke Yanagisawa, Yutaka Akiyama
    http://arxiv.org/abs/1907.01103v1

    • [q-bio.NC]A Power Efficient Artificial Neuron Using Superconducting Nanowires
    Emily Toomey, Ken Segall, Karl K. Berggren
    http://arxiv.org/abs/1907.00263v1

    • [q-bio.NC]Simple 1-D Convolutional Networks for Resting-State fMRI Based Classification in Autism
    Ahmed El Gazzar, Leonardo Cerliani, Guido van Wingen, Rajat Mani Thomas
    http://arxiv.org/abs/1907.01288v1

    • [q-bio.NC]Unsupervised predictive coding models may explain visual brain representation
    Marcio Fonseca
    http://arxiv.org/abs/1907.00441v1

    • [q-bio.QM]Neural parameters estimation for brain tumor growth modeling
    Ivan Ezhov, Jana Lipkova, Suprosanna Shit, Florian Kofler, Nore Collomb, Benjamin Lemasson, Emmanuel Barbier, Bjoern Menze
    http://arxiv.org/abs/1907.00973v1

    • [q-fin.ST]Improved Forecasting of Cryptocurrency Price using Social Signals
    Maria Glenski, Tim Weninger, Svitlana Volkova
    http://arxiv.org/abs/1907.00558v1

    • [quant-ph]Logical Clifford Synthesis for Stabilizer Codes
    Narayanan Rengaswamy, Robert Calderbank, Swanand Kadhe, Henry D. Pfister
    http://arxiv.org/abs/1907.00310v1

    • [quant-ph]Quantum Data-Syndrome Codes
    Alexei Ashikhmin, Ching-Yi Lai, Todd A. Brun
    http://arxiv.org/abs/1907.01393v1

    • [stat.AP]An Intrinsic Geometrical Approach for Statistical Process Control of Surface and Manifold Data
    Xueqi Zhao, Enrique del Castillo
    http://arxiv.org/abs/1907.00111v1

    • [stat.AP]Applying Meta-Analytic Predictive Priors with the R Bayesian evidence synthesis tools
    Sebastian Weber, Yue Li, John Seaman, Tomoyuki Kakizume, Heinz Schmidli
    http://arxiv.org/abs/1907.00603v1

    • [stat.AP]ICU Disparnumerophobia and Triskaidekaphobia: The ‘Irrational Care Unit’?
    Ari Ercole
    http://arxiv.org/abs/1907.00846v1

    • [stat.AP]Large Volatility Matrix Prediction with High-Frequency Data
    Xinyu Song
    http://arxiv.org/abs/1907.01196v1

    • [stat.AP]Wave-shape oscillatory model for biomedical time series with applications
    Yu-Ting Lin, John Malik, Hau-Tieng Wu
    http://arxiv.org/abs/1907.00502v1

    • [stat.CO]trialr: Bayesian Clinical Trial Designs in R and Stan
    Kristian Brock
    http://arxiv.org/abs/1907.00161v1

    • [stat.ME]Adaptive Partitioning Design and Analysis for Emulation of a Complex Computer Code
    Sonja Surjanovic, William J. Welch
    http://arxiv.org/abs/1907.01181v1

    • [stat.ME]An outlier-robust Kalman filter with mixture correntropy
    Hongwei Wang, Wei Zhang, Junyi Zuo, Heping Wang
    http://arxiv.org/abs/1907.00307v1

    • [stat.ME]Bayesian Analysis of High-dimensional Discrete Graphical Models
    Anwesha Bhattacharyya, Yves Atchade
    http://arxiv.org/abs/1907.01170v1

    • [stat.ME]Coupling techniques for nonlinear ensemble filtering
    Alessio Spantini, Ricardo Baptista, Youssef Marzouk
    http://arxiv.org/abs/1907.00389v1

    • [stat.ME]Estimating Treatment Effect under Additive Hazards Models with High-dimensional Covariates
    Jue Hou, Jelena Bradic, Ronghui Xu
    http://arxiv.org/abs/1907.00287v1

    • [stat.ME]Frequentist performances of Bayesian prediction intervals for random-effects meta-analysis
    Yuta Hamaguchi, Hisashi Noma, Kengo Nagashima, Tomohide Yamada, Toshi A. Furukawa
    http://arxiv.org/abs/1907.00345v1

    • [stat.ME]Multiple competition based FDR control
    Kristen Emery, Syamand Hasam, William Stafford Noble, Uri Keich
    http://arxiv.org/abs/1907.01458v1

    • [stat.ME]On Global-local Shrinkage Priors for Count Data
    Yasuyuki Hamura, Kaoru Irie, Shonosuke Sugasawa
    http://arxiv.org/abs/1907.01333v1

    • [stat.ME]Penalized Variable Selection in Multi-Parameter Regression Survival Modelling
    Fatima-Zahra Jaouimaa, Il Do Ha, Kevin Burke
    http://arxiv.org/abs/1907.01511v1

    • [stat.ME]State-of-the-art in selection of variables and functional forms in multivariable analysis — outstanding issues
    Willi Sauerbrei, Aris Perperoglou, Matthias Schmid, Michal Abrahamowicz, Heiko Becher, Harald Binder, Daniela Dunkler, Frank E. Harrell Jr, Patrick Royston, Georg Heinze
    http://arxiv.org/abs/1907.00786v1

    • [stat.ME]Transformed Naive Ratio and Product Based Estimators for Estimating Population Mode in Simple Random Sampling
    Sanjay Kumar, Nirmal Tiwari
    http://arxiv.org/abs/1907.00519v1

    • [stat.ME]Using Subset Log-Likelihoods to Trim Outliers in Gaussian Mixture Models
    Katharine M. Clark, Paul D. McNicholas
    http://arxiv.org/abs/1907.01136v1

    • [stat.ME]Volatility Analysis with Realized GARCH-Ito Models
    Xinyu Song, Donggyu Kim, Huiling Yuan, Xiangyu Cui, Zhiping Lu, Young Zhou, Yazhen Wang
    http://arxiv.org/abs/1907.01175v1

    • [stat.ML]A Kernel Stein Test for Comparing Latent Variable Models
    Heishiro Kanagawa, Wittawat Jitkrittum, Lester Mackey, Kenji Fukumizu, Arthur Gretton
    http://arxiv.org/abs/1907.00586v1

    • [stat.ML]A Unified Approach to Robust Mean Estimation
    Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar
    http://arxiv.org/abs/1907.00927v1

    • [stat.ML]Accurate, reliable and fast robustness evaluation
    Wieland Brendel, Jonas Rauber, Matthias Kümmerer, Ivan Ustyuzhaninov, Matthias Bethge
    http://arxiv.org/abs/1907.01003v1

    • [stat.ML]Augmenting and Tuning Knowledge Graph Embeddings
    Robert Bamler, Farnood Salehi, Stephan Mandt
    http://arxiv.org/abs/1907.01068v1

    • [stat.ML]Radial Bayesian Neural Networks: Robust Variational Inference In Big Models
    Sebastian Farquhar, Michael Osborne, Yarin Gal
    http://arxiv.org/abs/1907.00865v1

    • [stat.ML]Sparse regular variation
    Nicolas Meyer, Olivier Wintenberger
    http://arxiv.org/abs/1907.00686v1

    • [stat.ML]Time-to-Event Prediction with Neural Networks and Cox Regression
    Håvard Kvamme, Ørnulf Borgan, Ida Scheel
    http://arxiv.org/abs/1907.00825v1