astro-ph.IM - 仪器仪表和天体物理学方法

    cs.AI - 人工智能 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DL - 数字图书馆 cs.DS - 数据结构与算法 cs.GR - 计算机图形学 cs.GT - 计算机科学与博弈论 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.MA - 多代理系统 cs.MM - 多媒体 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.OH - 其他CS cs.RO - 机器人学 cs.SD - 声音处理 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 econ.GN - 一般经济学 eess.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.CA - 古典分析与常微分方程 math.CO - 组合数学 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.comp-ph - 计算物理学 physics.med-ph - 医学物理学 q-bio.GN - 基因组学 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

    • [astro-ph.IM]LRP2020: Astrostatistics in Canada
    • [cs.AI]A Logic-Based Framework Leveraging Neural Networks for Studying the Evolution of Neurological Disorders
    • [cs.AI]Blameworthiness in Security Games
    • [cs.AI]Neural Logic Networks
    • [cs.AI]Optimal Immunization Policy Using Dynamic Programming
    • [cs.AI]Recurrent neural network approach for cyclic job shop scheduling problem
    • [cs.AI]Redistribution Mechanism Design on Networks
    • [cs.AI]Solving dynamic multi-objective optimization problems via support vector machine
    • [cs.CL]A Neural Entity Coreference Resolution Review
    • [cs.CL]An Improved Historical Embedding without Alignment
    • [cs.CL]Automatic Post-Editing for Machine Translation
    • [cs.CL]Building Dynamic Knowledge Graphs from Text-based Games
    • [cs.CL]Byte-Pair Encoding for Text-to-SQL Generation
    • [cs.CL]Constructing Artificial Data for Fine-tuning for Low-Resource Biomedical Text Tagging with Applications in PICO Annotation
    • [cs.CL]Diamonds in the Rough: Generating Fluent Sentences from Early-Stage Drafts for Academic Writing Assistance
    • [cs.CL]Disambiguating Speech Intention via Audio-Text Co-attention Framework: A Case of Prosody-semantics Interface
    • [cs.CL]Diversify Your Datasets: Analyzing Generalization via Controlled Variance in Adversarial Datasets
    • [cs.CL]Domain-agnostic Question-Answering with Adversarial Training
    • [cs.CL]Enhancing Recurrent Neural Networks with Sememes
    • [cs.CL]Human-Like Decision Making: Document-level Aspect Sentiment Classification via Hierarchical Reinforcement Learning
    • [cs.CL]Improving Word Representations: A Sub-sampled Unigram Distribution for Negative Sampling
    • [cs.CL]Keyphrase Extraction from Scholarly Articles as Sequence Labeling using Contextualized Embeddings
    • [cs.CL]Localization of Fake News Detection via Multitask Transfer Learning
    • [cs.CL]MonaLog: a Lightweight System for Natural Language Inference Based on Monotonicity
    • [cs.CL]Natural Question Generation with Reinforcement Learning Based Graph-to-Sequence Model
    • [cs.CL]On Semi-Supervised Multiple Representation Behavior Learning
    • [cs.CL]PT-CoDE: Pre-trained Context-Dependent Encoder for Utterance-level Emotion Recognition
    • [cs.CL]Predicting the Leading Political Ideology of YouTube Channels Using Acoustic, Textual, and Metadata Information
    • [cs.CL]Semantic Graph Convolutional Network for Implicit Discourse Relation Classification
    • [cs.CL]Sticking to the Facts: Confident Decoding for Faithful Data-to-Text Generation
    • [cs.CL]The Czech Court Decisions Corpus (CzCDC): Availability as the First Step
    • [cs.CL]Towards Learning Cross-Modal Perception-Trace Models
    • [cs.CR]Analysis of Nakamoto Consensus, Revisited
    • [cs.CR]CDAG: A Serialized blockDAG for Permissioned Blockchain
    • [cs.CR]Constructing Privacy Channels from Information Channels
    • [cs.CR]Crypto Mining Makes Noise
    • [cs.CR]Improving Privacy in Graphs Through Node Addition
    • [cs.CR]You Can Run, But You Cannot Hide: Using Elevation Profiles to Breach Location Privacy through Trajectory Prediction
    • [cs.CV]A Survey and Taxonomy of Adversarial Neural Networks for Text-to-Image Synthesis
    • [cs.CV]Active 6D Multi-Object Pose Estimation in Cluttered Scenarios with Deep Reinforcement Learning
    • [cs.CV]Adversarial Skill Networks: Unsupervised Robot Skill Learning from Video
    • [cs.CV]Analysis and a Solution of Momentarily Missed Detection for Anchor-based Object Detectors
    • [cs.CV]Batch Face Alignment using a Low-rank GAN
    • [cs.CV]CNN based Extraction of Panels/Characters from Bengali Comic Book Page Images
    • [cs.CV]CSID: Center, Scale, Identity and Density-aware Pedestrian Detection in a Crowd
    • [cs.CV]Cascaded Generation of High-quality Color Visible Face Images from Thermal Captures
    • [cs.CV]Component Attention Guided Face Super-Resolution Network: CAGFace
    • [cs.CV]Coordinated Joint Multimodal Embeddings for Generalized Audio-Visual Zeroshot Classification and Retrieval of Videos
    • [cs.CV]Correlation Maximized Structural Similarity Loss for Semantic Segmentation
    • [cs.CV]Decoupling Representation and Classifier for Long-Tailed Recognition
    • [cs.CV]Deep Parametric Indoor Lighting Estimation
    • [cs.CV]Depth-wise Decomposition for Accelerating Separable Convolutions in Efficient Convolutional Neural Networks
    • [cs.CV]Directed-Weighting Group Lasso for Eltwise Blocked CNN Pruning
    • [cs.CV]DwNet: Dense warp-based network for pose-guided human video generation
    • [cs.CV]Endowing Deep 3D Models with Rotation Invariance Based on Principal Component Analysis
    • [cs.CV]Fast and Light-weight Portrait Segmentation
    • [cs.CV]Good, Better, Best: Textual Distractors Generation for Multi-Choice VQA via Policy Gradient
    • [cs.CV]Hadamard Codebook Based Deep Hashing
    • [cs.CV]Identity Document and banknote security forensics: a survey
    • [cs.CV]Image Restoration Using Deep Regulated Convolutional Networks
    • [cs.CV]Improving Style Transfer with Calibrated Metrics
    • [cs.CV]Improving Vehicle Re-Identification using CNN Latent Spaces: Metrics Comparison and Track-to-track Extension
    • [cs.CV]KuroNet: Pre-Modern Japanese Kuzushiji Character Recognition with Deep Learning
    • [cs.CV]LinesToFacePhoto: Face Photo Generation from Lines with Conditional Self-Attention Generative Adversarial Network
    • [cs.CV]Looking Ahead: Anticipating Pedestrians Crossing with Future Frames Prediction
    • [cs.CV]MeteorNet: Deep Learning on Dynamic 3D Point Cloud Sequences
    • [cs.CV]MixModule: Mixed CNN Kernel Module for Medical Image Segmentation
    • [cs.CV]Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments
    • [cs.CV]NormGrad: Finding the Pixels that Matter for Training
    • [cs.CV]Object landmark discovery through unsupervised adaptation
    • [cs.CV]Self-supervised classification of dynamic obstacles using the temporal information provided by videos
    • [cs.CV]Semantics for Global and Local Interpretation of Deep Neural Networks
    • [cs.CV]Sketch2Code: Transformation of Sketches to UI in Real-time Using Deep Neural Network
    • [cs.CV]SpatialFlow: Bridging All Tasks for Panoptic Segmentation
    • [cs.CV]Structured Prediction Helps 3D Human Motion Modelling
    • [cs.CV]The Deepfake Detection Challenge (DFDC) Preview Dataset
    • [cs.CV]Transferable Recognition-Aware Image Processing
    • [cs.CV]Tree-gated Deep Mixture-of-Experts For Pose-robust Face Alignment
    • [cs.CV]Unsupervised High-Resolution Depth Learning From Videos With Dual Networks
    • [cs.CY]Digital Democracy: Episode IV — A New Hope, How a Corporation for Public Software Could Transform Digital Engagement for Government and Civil Society
    • [cs.DB]Demystifying Graph Databases: Analysis and Taxonomy of Data Organization, System Designs, and Graph Queries
    • [cs.DC]BatteryLab, A Distributed Power Monitoring Platform For Mobile Devices
    • [cs.DC]DLB: Deep Learning Based Load Balancing
    • [cs.DC]Microservices based Framework to Support Interoperable IoT Applications for Enhanced Data Analytics
    • [cs.DC]RLScheduler: Learn to Schedule HPC Batch Jobs Using Deep Reinforcement Learning
    • [cs.DC]Reconfigurable Lattice Agreement and Applications
    • [cs.DL]Science and Technology Advance through Surprise
    • [cs.DS]Adaptive Learned Bloom Filter (Ada-BF): Efficient Utilization of the Classifier
    • [cs.DS]Temporal Network Sampling
    • [cs.GR]Real-Time Lip Sync for Live 2D Animation
    • [cs.GT]Incentivize Diffusion with Fair Rewards on Networks
    • [cs.GT]Semi-Decentralized Coordinated Online Learning for Continuous Games with Coupled Constraints via Augmented Lagrangian
    • [cs.HC]Toward automatic comparison of visualization techniques: Application to graph visualization
    • [cs.HC]Two Case Studies of Experience Prototyping Machine Learning Systems in the Wild
    • [cs.IR]A Comparison of Semantic Similarity Methods for Maximum Human Interpretability
    • [cs.IR]EQSA: Earthquake Situational Analytics from Social Media
    • [cs.IR]On large-scale genre classification in symbolically encoded music by automatic identification of repeating patterns
    • [cs.IR]Personalizing Graph Neural Networks with Attention Mechanism for Session-based Recommendation
    • [cs.IR]The Bitwise Hashing Trick for Personalized Search
    • [cs.IT]An Open-Source Toolbox for Computer-Aided Investigation on the Fundamental Limits of Information Systems, Version 0.1
    • [cs.IT]Distributed Quantization for Sparse Time Sequences
    • [cs.IT]Dynamic Content Update for Wireless Edge Caching via Deep Reinforcement Learning
    • [cs.IT]Locally Decodable Index Codes
    • [cs.IT]Matrix-Product Codes over Commutative Rings and Constructions Arising from $(σ,δ)$-Codes
    • [cs.IT]Multi-User MABs with User Dependent Rewards for Uncoordinated Spectrum Access
    • [cs.IT]On Self-Orthogonality and Self-Duality of Matrix-Product Codes over Commutative Rings
    • [cs.IT]Secrecy and Covert Communications against UAV Surveillance via Multi-Hop Networks
    • [cs.IT]Sub-Nyquist Sampling of Sparse and Correlated Signals in Array Processing
    • [cs.IT]Trajectory Design for Energy Minimization in UAV-enabled Wireless Communications with Latency Constraints
    • [cs.LG]A $ν$- support vector quantile regression model with automatic accuracy control
    • [cs.LG]A New Framework for Multi-Agent Reinforcement Learning — Centralized Training and Exploration with Decentralized Execution via Policy Distillation
    • [cs.LG]A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning
    • [cs.LG]A game method for improving the interpretability of convolution neural network
    • [cs.LG]Aggregated Gradient Langevin Dynamics
    • [cs.LG]Aleatoric and Epistemic Uncertainty in Machine Learning: A Tutorial Introduction
    • [cs.LG]All-Action Policy Gradient Methods: A Numerical Integration Approach
    • [cs.LG]Amortized Rejection Sampling in Universal Probabilistic Programming
    • [cs.LG]An Alternative Surrogate Loss for PGD-based Adversarial Testing
    • [cs.LG]An Optimal Transport Framework for Zero-Shot Learning
    • [cs.LG]An Unbiased Risk Estimator for Learning with Augmented Classes
    • [cs.LG]Approximate Sampling using an Accelerated Metropolis-Hastings based on Bayesian Optimization and Gaussian Processes
    • [cs.LG]Approximation capabilities of neural networks on unbounded domains
    • [cs.LG]Are Perceptually-Aligned Gradients a General Property of Robust Classifiers?
    • [cs.LG]Boosting Mapping Functionality of Neural Networks via Latent Feature Generation based on Reversible Learning
    • [cs.LG]Boosting Network Weight Separability via Feed-Backward Reconstruction
    • [cs.LG]Context-Driven Data Mining through Bias Removal and Data Incompleteness Mitigation
    • [cs.LG]Contextual Prediction Difference Analysis
    • [cs.LG]CreditPrint: Credit Investigation via Geographic Footprints by Deep Learning
    • [cs.LG]Dealing with Sparse Rewards in Reinforcement Learning
    • [cs.LG]Dictionary Learning with Almost Sure Error Constraints
    • [cs.LG]Differentiable Deep Clustering with Cluster Size Constraints
    • [cs.LG]Discovering the Compositional Structure of Vector Representations with Role Learning Networks
    • [cs.LG]Diverse Behavior Is What Game AI Needs: Generating Varied Human-Like Playing Styles Using Evolutionary Multi-Objective Deep Reinforcement Learning
    • [cs.LG]Explainable AI: Deep Reinforcement Learning Agents for Residential Demand Side Cost Savings in Smart Grids
    • [cs.LG]Fast Exact Matrix Completion: A Unifying Optimization Framework
    • [cs.LG]From Importance Sampling to Doubly Robust Policy Gradient
    • [cs.LG]Generative Hierarchical Models for Parts, Objects, and Scenes
    • [cs.LG]Graph Construction from Data using Non Negative Kernel regression (NNK Graphs)
    • [cs.LG]Identification of Interaction Clusters Using a Semi-supervised Hierarchical Clustering Method
    • [cs.LG]Image Difficulty Curriculum for Generative Adversarial Networks (CuGAN)
    • [cs.LG]Implementation of a modified Nesterov’s Accelerated quasi-Newton Method on Tensorflow
    • [cs.LG]Integrals over Gaussians under Linear Domain Constraints
    • [cs.LG]Introduction to Coresets: Accurate Coresets
    • [cs.LG]LSTM-Assisted Evolutionary Self-Expressive Subspace Clustering
    • [cs.LG]Landing Probabilities of Random Walks for Seed-Set Expansion in Hypergraphs
    • [cs.LG]Learning GANs and Ensembles Using Discrepancy
    • [cs.LG]Learning Hierarchical Feature Space Using CLAss-specific Subspace Multiple Kernel — Metric Learning for Classification
    • [cs.LG]Learning from both experts and data
    • [cs.LG]Learning to Learn by Zeroth-Order Oracle
    • [cs.LG]Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text
    • [cs.LG]Leveraging inductive bias of neural networks for learning without explicit human annotations
    • [cs.LG]Machine Learning Systems for Highly-Distributed and Rapidly-Growing Data
    • [cs.LG]Machine Learning for AC Optimal Power Flow
    • [cs.LG]Making Bayesian Predictive Models Interpretable: A Decision Theoretic Approach
    • [cs.LG]Maximum Probability Principle and Black-Box Priors
    • [cs.LG]Mining GOLD Samples for Conditional GANs
    • [cs.LG]Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach
    • [cs.LG]Momentum in Reinforcement Learning
    • [cs.LG]Movienet: A Movie Multilayer Network Model using Visual and Textual Semantic Cues
    • [cs.LG]Multi-player Multi-Armed Bandits with non-zero rewards on collisions for uncoordinated spectrum access
    • [cs.LG]NASIB: Neural Architecture Search withIn Budget
    • [cs.LG]Neural Spectrum Alignment
    • [cs.LG]Neuro-SERKET: Development of Integrative Cognitive System through the Composition of Deep Probabilistic Generative Models
    • [cs.LG]OffWorld Gym: open-access physical robotics environment for real-world reinforcement learning benchmark and research
    • [cs.LG]On Adaptivity in Information-constrained Online Learning
    • [cs.LG]Online Bagging for Anytime Transfer Learning
    • [cs.LG]Online Pricing with Offline Data: Phase Transition and Inverse Square Law
    • [cs.LG]Perception-Distortion Trade-off with Restricted Boltzmann Machines
    • [cs.LG]Policy Learning for Malaria Control
    • [cs.LG]Predicting ice flow using machine learning
    • [cs.LG]Pricing Mechanism for Resource Sustainability in Competitive Online Learning Multi-Agent Systems
    • [cs.LG]Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations
    • [cs.LG]Recovering Localized Adversarial Attacks
    • [cs.LG]Regularization Matters in Policy Optimization
    • [cs.LG]Reverse Experience Replay
    • [cs.LG]Self-Educated Language Agent With Hindsight Experience Replay For Instruction Following
    • [cs.LG]Separable Convolutional Eigen-Filters (SCEF): Building Efficient CNNs Using Redundancy Analysis
    • [cs.LG]Sparse-Dense Subspace Clustering
    • [cs.LG]Sparsification as a Remedy for Staleness in Distributed Asynchronous SGD
    • [cs.LG]Stochastic Recursive Gradient-Based Methods for Projection-Free Online Learning
    • [cs.LG]Toward Metrics for Differentiating Out-of-Distribution Sets
    • [cs.LG]Towards Further Understanding of Sparse Filtering via Information Bottleneck
    • [cs.LG]Towards Quantifying Intrinsic Generalization of Deep ReLU Networks
    • [cs.LG]Towards User Empowerment
    • [cs.LG]Unsupervised Out-of-Distribution Detection with Batch Normalization
    • [cs.LG]Who wants accurate models? Arguing for a different metrics to take classification models seriously
    • [cs.LG]Zero-shot Learning via Simultaneous Generating and Learning
    • [cs.LO]Computer-supported Analysis of Positive Properties, Ultrafilters and Modal Collapse in Variants of Gödel’s Ontological Argument
    • [cs.MA]Autonomous Industrial Management via Reinforcement Learning: Self-Learning Agents for Decision-Making — A Review
    • [cs.MA]Multi-agent Hierarchical Reinforcement Learning with Dynamic Termination
    • [cs.MM]Automated Composition of Picture-Synched Music Soundtracks for Movies
    • [cs.NE]Evolutionary Dynamic Multi-objective Optimization Via Regression Transfer Learning
    • [cs.NE]S4NN: temporal backpropagation for spiking neural networks with one spike per neuron
    • [cs.NE]Solving Dynamic Multi-objective Optimization Problems Using Incremental Support Vector Machine
    • [cs.NI]Downlink Performance of Dense Antenna Deployment: To Distribute or Concentrate?
    • [cs.OH]Benchmark Dataset for Timetable Optimization of Bus Routes in the City of New Delhi
    • [cs.RO]CAPRICORN: Communication Aware Place Recognition using Interpretable Constellations of Objects in Robot Networks
    • [cs.RO]Electric Sheep Team Description Paper Humanoid League Kid-Size 2019
    • [cs.RO]Modelling Generalized Forces with Reinforcement Learning for Sim-to-Real Transfer
    • [cs.RO]Planning, Learning and Reasoning Framework for Robot Truck Unloading
    • [cs.RO]Self-Supervised Sim-to-Real Adaptation for Visual Robotic Manipulation
    • [cs.SD]Clotho: An Audio Captioning Dataset
    • [cs.SD]Deep speech inpainting of time-frequency masks
    • [cs.SD]Multi-Band Multi-Resolution Fully Convolutional Neural Networks for Singing Voice Separation
    • [cs.SD]Musical Instrument Playing Technique Detection Based on FCN: Using Chinese Bowed-Stringed Instrument as an Example
    • [cs.SD]Representation Learning for Discovering Phonemic Tone Contours
    • [cs.SI]Modelling Online Comment Threads from their Start
    • [cs.SI]Opinion shaping in social networks using reinforcement learning
    • [cs.SI]Towards Interpretable Graph Modeling with Vertex Replacement Grammars
    • [cs.SI]User-Aware Folk Popularity Rank: User-Popularity-Based Tag Recommendation That Can Enhance Social Popularity
    • [cs.SI]Using machine learning and information visualisation for discovering latent topics in Twitter news
    • [econ.EM]Bounds in continuous instrumental variable models
    • [econ.GN]Beating the House: Identifying Inefficiencies in Sports Betting Markets
    • [eess.AS]Adversarial Attacks on Spoofing Countermeasures of automatic speaker verification
    • [eess.AS]Comparative Study between Adversarial Networks and Classical Techniques for Speech Enhancement
    • [eess.IV]Attention Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images
    • [eess.IV]Attention Guided Metal Artifact Correction in MRI using Deep Neural Networks
    • [eess.IV]Automatic Lumbar Spinal CT Image Segmentation with a Dual Densely Connected U-Net
    • [eess.IV]CAI4CAI: The Rise of Contextual Artificial Intelligence in Computer Assisted Interventions
    • [eess.IV]Combining Shape Priors with Conditional Adversarial Networks for Improved Scapula Segmentation in MR images
    • [eess.IV]Deep Mouse: An End-to-end Auto-context Refinement Framework for Brain Ventricle and Body Segmentation in Embryonic Mice Ultrasound Volumes
    • [eess.IV]Gastroscopic Panoramic View: Application to Automatic Polyps Detection under Gastroscopy
    • [eess.IV]Hyperspectral Image Classification Based on Adaptive Sparse Deep Network
    • [eess.IV]KRNET: Image Denoising with Kernel Regulation Network
    • [eess.IV]LEt-SNE: A Hybrid Approach To Data Embedding and Visualization of Hyperspectral Imagery
    • [eess.IV]Learning a Generic Adaptive Wavelet Shrinkage Function for Denoising
    • [eess.IV]MIScnn: A Framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning
    • [eess.IV]Modeling Disease Progression In Retinal OCTs With Longitudinal Self-Supervised Learning
    • [eess.IV]Probabilistic Radiomics: Ambiguous Diagnosis with Controllable Shape Analysis
    • [eess.IV]ProxIQA: A Proxy Approach to Perceptual Optimization of Learned Image Compression
    • [eess.IV]SANet:Superpixel Attention Network for Skin Lesion Attributes Detection
    • [eess.IV]Self-Supervised Physics-Based Deep Learning MRI Reconstruction Without Fully-Sampled Data
    • [eess.IV]Spectral Characterization of functional MRI data on voxel-resolution cortical graphs
    • [eess.IV]Tracking-Assisted Segmentation of Biological Cells
    • [eess.IV]Utilising Low Complexity CNNs to Lift Non-Local Redundancies in Video Coding
    • [eess.IV]i-RIM applied to the fastMRI challenge
    • [eess.IV]ipA-MedGAN: Inpainting of Arbitrarily Regions in Medical Modalities
    • [eess.SP]Model Order Selection in DoA Scenarios via Cross-Entropy based Machine Learning Techniques
    • [eess.SP]UW-SVC: Scalable Video Coding Transmission for In-network Underwater Imagery Analysis
    • [eess.SY]A Dynamic System Model for Personalized Healthcare Delivery and Managed Individual Health Outcomes
    • [eess.SY]Autonomous Control of a Quadrotor-Manipulator; Application of Extended State Disturbance Observer
    • [eess.SY]Ensemble learning based linear power flow
    • [eess.SY]Towards a Reinforcement Learning Environment Toolbox for Intelligent Electric Motor Control
    • [math.CA]Finding duality for Riesz bases of exponentials on multi-tiles
    • [math.CO]An Improved Linear Programming Bound on the Average Distance of a Binary Code
    • [math.OC]A Stochastic Extra-Step Quasi-Newton Method for Nonsmooth Nonconvex Optimization
    • [math.OC]Adaptive gradient descent without descent
    • [math.OC]Exploration via Sample-Efficient Subgoal Design
    • [math.OC]Policy Optimization for $\mathcal{H}2$ Linear Control with $\mathcal{H}\infty$ Robustness Guarantee: Implicit Regularization and Global Convergence
    • [math.OC]Relative Interior Rule in Block-Coordinate Minimization
    • [math.OC]Robust Online Learning for Resource Allocation — Beyond Euclidean Projection and Dynamic Fit
    • [math.PR]Counterexamples for optimal scaling of Metropolis-Hastings chains with rough target densities
    • [math.PR]Empirical Process of Multivariate Gaussian under General Dependency
    • [math.PR]Sampling random graph homomorphisms and applications to network data analysis
    • [math.ST]A General Framework for Empirical Bayes Estimation in Discrete Linear Exponential Family
    • [math.ST]Convex Reconstruction of Structured Matrix Signals from Random Linear Measurements (I): Theoretical Results
    • [math.ST]High-dimensional robust approximated M-estimators for mean regression with asymmetric data
    • [math.ST]On the power of axial tests of uniformity on spheres
    • [math.ST]Online Community Detection by Spectral CUSUM
    • [math.ST]Ordering-Based Causal Structure Learning in the Presence of Latent Variables
    • [math.ST]Quickest Detection of Growing Dynamic Anomalies in Networks
    • [math.ST]Robustifying multiple-set linear canonical analysis with S-estimator
    • [math.ST]Safe-Bayesian Generalized Linear Regression
    • [math.ST]Statistical tests for the Pseudo-Lindley distribution and applications
    • [math.ST]The Generalized-Alpha-Beta-Skew-Normal Distribution: Properties and Applications
    • [physics.comp-ph]Extracting local switching fields in permanent magnets using machine learning
    • [physics.med-ph]Detecting muscle activation using ultrasound speed of sound inversion with deep learning
    • [q-bio.GN]SneakySnake: A Fast and Accurate Universal Genome Pre-Alignment Filter for CPUs, GPUs, and FPGAs
    • [q-bio.QM]Biologic and Prognostic Feature scores from Whole-Slide Histology Images Using Deep Learning
    • [q-fin.ST]CorrGAN: Sampling Realistic Financial Correlation Matrices Using Generative Adversarial Networks
    • [q-fin.ST]Entropic Dynamic Time Warping Kernels for Co-evolving Financial Time Series Analysis
    • [quant-ph]Deep Reinforcement Learning Control of Quantum Cartpoles
    • [quant-ph]On Optimality of CSS Codes for Transversal $T$
    • [stat.AP]A Nonparametric Bayesian Design for Drug Combination Cancer Trials
    • [stat.AP]Application of a new information priority accumulated grey model with time power to predict short-term wind turbine capacity
    • [stat.AP]Returning Scientists and the Emergence of Chinese Science System
    • [stat.AP]Sequential Spatial Point Process Models for Spatio-Temporal Point Processes: A Self-Interactive Model with Application to Forest Tree Data
    • [stat.AP]Supporting Multi-point Fan Design with Dimension Reduction
    • [stat.CO]Particle filter with rejection control and unbiased estimator of the marginal likelihood
    • [stat.ME]An Apparent Paradox: A Classifier Trained from a Partially Classified Sample May Have Smaller Expected Error Rate Than That If the Sample Were Completely Classified
    • [stat.ME]Bayesian Symbolic Regression
    • [stat.ME]Clustering by Optimizing the Average Silhouette Width
    • [stat.ME]Efficient Emulation of Computer Models Utilising Multiple Known Boundaries of Differing Dimensions
    • [stat.ME]Equivalence tests for binary efficacy-toxicity responses
    • [stat.ME]Generalized tensor regression with covariates on multiple modes
    • [stat.ME]Latent Variable Model for Multivariate Data with Measure-specific Sample Weights and Its Application in Hospital Compare
    • [stat.ME]Marginally Interpretable Linear Transformation Models for Clustered Observations
    • [stat.ME]Measuring Causality: The Science of Cause and Effect
    • [stat.ME]Noncrossing structured additive multiple-output Bayesian quantile regression models
    • [stat.ME]Note on the Delta Method for Finite Population Inference with Applications to Causal Inference
    • [stat.ME]Permutation-Based Causal Structure Learning with Unknown Intervention Targets
    • [stat.ME]Targeted Estimation of Heterogeneous Treatment Effect in Observational Survival Analysis
    • [stat.ML]$hv$-Block Cross Validation is not a BIBD: a Note on the Paper by Jeff Racine (2000)
    • [stat.ML]Adversarial Anomaly Detection for Marked Spatio-Temporal Streaming Data
    • [stat.ML]Bayesian Optimization Allowing for Common Random Numbers
    • [stat.ML]Communication Efficient Decentralized Training with Multiple Local Updates
    • [stat.ML]Generalised learning of time-series: Ornstein-Uhlenbeck processes
    • [stat.ML]Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment Problem
    • [stat.ML]Measurement Dependence Inducing Latent Causal Models
    • [stat.ML]Multi-Resolution Weak Supervision for Sequential Data
    • [stat.ML]Online Ranking with Concept Drifts in Streaming Data
    • [stat.ML]Robust Learning Rate Selection for Stochastic Optimization via Splitting Diagnostic
    • [stat.ML]Sparse (group) learning with Lipschitz loss functions: a unified analysis
    • [stat.ML]The Exact Equivalence of Independence Testing and Two-Sample Testing
    • [stat.ML]Towards better healthcare: What could and should be automated?
    • [stat.ML]Variational Integrator Networks for Physically Meaningful Embeddings

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    • [astro-ph.IM]LRP2020: Astrostatistics in Canada
    Gwendolyn Eadie, Arash Bahramian, Pauline Barmby, Radu Craiu, Derek Bingham, Renée Hložek, JJ Kavelaars, David Stenning, Samantha Benincasa, Guillaume Thomas, Karun Thanjavur, Jo Bovy, Jan Cami, Ray Carlberg, Sam Lawler, Adrian Liu, Henry Ngo, Mubdi Rahman, Michael Rupen
    http://arxiv.org/abs/1910.08857v1

    • [cs.AI]A Logic-Based Framework Leveraging Neural Networks for Studying the Evolution of Neurological Disorders
    Francesco Calimeri, Francesco Cauteruccio, Luca Cinelli, Aldo Marzullo, Claudio Stamile, Giorgio Terracina, Francoise Durand-Dubief, Dominique Sappey-Marinier
    http://arxiv.org/abs/1910.09472v1

    • [cs.AI]Blameworthiness in Security Games
    Pavel Naumov, Jia Tao
    http://arxiv.org/abs/1910.08647v1

    • [cs.AI]Neural Logic Networks
    Shaoyun Shi, Hanxiong Chen, Min Zhang, Yongfeng Zhang
    http://arxiv.org/abs/1910.08629v1

    • [cs.AI]Optimal Immunization Policy Using Dynamic Programming
    Atiye Alaeddini, Daniel Klein
    http://arxiv.org/abs/1910.08677v1

    • [cs.AI]Recurrent neural network approach for cyclic job shop scheduling problem
    M-Tahar Kechadi, Kok Seng Low, G. Goncalves
    http://arxiv.org/abs/1910.09437v1

    • [cs.AI]Redistribution Mechanism Design on Networks
    Wen Zhang, Dengji Zhao, Hanyu Chen
    http://arxiv.org/abs/1910.09335v1

    • [cs.AI]Solving dynamic multi-objective optimization problems via support vector machine
    Min Jiang, Weizhen Hu, Liming Qiu, Minghui Shi, Kay Chen Tan
    http://arxiv.org/abs/1910.08747v1

    • [cs.CL]A Neural Entity Coreference Resolution Review
    Nikolaos Stylianou, Ioannis Vlahavas
    http://arxiv.org/abs/1910.09329v1

    • [cs.CL]An Improved Historical Embedding without Alignment
    Xiaofei Xu, Ke Deng, Fei Hu, Li Li
    http://arxiv.org/abs/1910.08692v1

    • [cs.CL]Automatic Post-Editing for Machine Translation
    Rajen Chatterjee
    http://arxiv.org/abs/1910.08592v1

    • [cs.CL]Building Dynamic Knowledge Graphs from Text-based Games
    Mikulas Zelinka, Xingdi Yuan, Marc-Alexandre Cote, Romain Laroche, Adam Trischler
    http://arxiv.org/abs/1910.09532v1

    • [cs.CL]Byte-Pair Encoding for Text-to-SQL Generation
    Samuel Müller, Andreas Vlachos
    http://arxiv.org/abs/1910.08962v1

    • [cs.CL]Constructing Artificial Data for Fine-tuning for Low-Resource Biomedical Text Tagging with Applications in PICO Annotation
    Gaurav Singh, Zahra Sabet, John Shawe-Taylor, James Thomas
    http://arxiv.org/abs/1910.09255v1

    • [cs.CL]Diamonds in the Rough: Generating Fluent Sentences from Early-Stage Drafts for Academic Writing Assistance
    Takumi Ito, Tatsuki Kuribayashi, Hayato Kobayashi, Ana Brassard, Masato Hagiwara, Jun Suzuki, Kentaro Inui
    http://arxiv.org/abs/1910.09180v1

    • [cs.CL]Disambiguating Speech Intention via Audio-Text Co-attention Framework: A Case of Prosody-semantics Interface
    Won Ik Cho, Jeonghwa Cho, Woo Hyun Kang, Nam Soo Kim
    http://arxiv.org/abs/1910.09275v1

    • [cs.CL]Diversify Your Datasets: Analyzing Generalization via Controlled Variance in Adversarial Datasets
    Ohad Rozen, Vered Shwartz, Roee Aharoni, Ido Dagan
    http://arxiv.org/abs/1910.09302v1

    • [cs.CL]Domain-agnostic Question-Answering with Adversarial Training
    Seanie Lee, Donggyu Kim, Jangwon Park
    http://arxiv.org/abs/1910.09342v1

    • [cs.CL]Enhancing Recurrent Neural Networks with Sememes
    Yujia Qin, Fanchao Qi, Sicong Ouyang, Zhiyuan Liu, Cheng Yang, Yasheng Wang, Qun Liu, Maosong Sun
    http://arxiv.org/abs/1910.08910v1

    • [cs.CL]Human-Like Decision Making: Document-level Aspect Sentiment Classification via Hierarchical Reinforcement Learning
    Jingjing Wang, Changlong Sun, Shoushan Li, Jiancheng Wang, Luo Si, Min Zhang, Xiaozhong Liu, Guodong Zhou
    http://arxiv.org/abs/1910.09260v1

    • [cs.CL]Improving Word Representations: A Sub-sampled Unigram Distribution for Negative Sampling
    Wenxiang Jiao, Irwin King, Michael R. Lyu
    http://arxiv.org/abs/1910.09362v1

    • [cs.CL]Keyphrase Extraction from Scholarly Articles as Sequence Labeling using Contextualized Embeddings
    Dhruva Sahrawat, Debanjan Mahata, Mayank Kulkarni, Haimin Zhang, Rakesh Gosangi, Amanda Stent, Agniv Sharma, Yaman Kumar, Rajiv Ratn Shah, Roger Zimmermann
    http://arxiv.org/abs/1910.08840v1

    • [cs.CL]Localization of Fake News Detection via Multitask Transfer Learning
    Jan Christian Blaise Cruz, Julianne Agatha Tan, Charibeth Cheng
    http://arxiv.org/abs/1910.09295v1

    • [cs.CL]MonaLog: a Lightweight System for Natural Language Inference Based on Monotonicity
    Hai Hu, Qi Chen, Kyle Richardson, Atreyee Mukherjee, Lawrence S. Moss, Sandra Kuebler
    http://arxiv.org/abs/1910.08772v1

    • [cs.CL]Natural Question Generation with Reinforcement Learning Based Graph-to-Sequence Model
    Yu Chen, Lingfei Wu, Mohammed J. Zaki
    http://arxiv.org/abs/1910.08832v1

    • [cs.CL]On Semi-Supervised Multiple Representation Behavior Learning
    Ruqian Lu, Shengluan Hou
    http://arxiv.org/abs/1910.09292v1

    • [cs.CL]PT-CoDE: Pre-trained Context-Dependent Encoder for Utterance-level Emotion Recognition
    Wenxiang Jiao, Michael R. Lyu, Irwin King
    http://arxiv.org/abs/1910.08916v1

    • [cs.CL]Predicting the Leading Political Ideology of YouTube Channels Using Acoustic, Textual, and Metadata Information
    Yoan Dinkov, Ahmed Ali, Ivan Koychev, Preslav Nakov
    http://arxiv.org/abs/1910.08948v1

    • [cs.CL]Semantic Graph Convolutional Network for Implicit Discourse Relation Classification
    Yingxue Zhang, Ping Jian, Fandong Meng, Ruiying Geng, Wei Cheng, Jie Zhou
    http://arxiv.org/abs/1910.09183v1

    • [cs.CL]Sticking to the Facts: Confident Decoding for Faithful Data-to-Text Generation
    Ran Tian, Shashi Narayan, Thibault Sellam, Ankur P. Parikh
    http://arxiv.org/abs/1910.08684v1

    • [cs.CL]The Czech Court Decisions Corpus (CzCDC): Availability as the First Step
    Tereza Novotná, Jakub Harašta
    http://arxiv.org/abs/1910.09513v1

    • [cs.CL]Towards Learning Cross-Modal Perception-Trace Models
    Achim Rettinger, Viktoria Bogdanova, Philipp Niemann
    http://arxiv.org/abs/1910.08549v1

    • [cs.CR]Analysis of Nakamoto Consensus, Revisited
    Jianyu Niu, Chen Feng, Hoang Dau, Yu-Chih Huang, Jingge Zhu
    http://arxiv.org/abs/1910.08510v2

    • [cs.CR]CDAG: A Serialized blockDAG for Permissioned Blockchain
    Himanshu Gupta, Dharanipragada Janakiram
    http://arxiv.org/abs/1910.08547v1

    • [cs.CR]Constructing Privacy Channels from Information Channels
    Genqiang Wu
    http://arxiv.org/abs/1910.09235v1

    • [cs.CR]Crypto Mining Makes Noise
    Maurantonio Caprolu, Simone Raponi, Gabriele Oligeri, Roberto Di Pietro
    http://arxiv.org/abs/1910.09272v1

    • [cs.CR]Improving Privacy in Graphs Through Node Addition
    Nazanin Takbiri, Xiaozhe Shao, Lixin Gao, Hossein Pishro-Nik
    http://arxiv.org/abs/1910.08679v1

    • [cs.CR]You Can Run, But You Cannot Hide: Using Elevation Profiles to Breach Location Privacy through Trajectory Prediction
    Ülkü Meteriz, Necip Fazıl Yıldıran, Aziz Mohaisen
    http://arxiv.org/abs/1910.09041v1

    • [cs.CV]A Survey and Taxonomy of Adversarial Neural Networks for Text-to-Image Synthesis
    Jorge Agnese, Jonathan Herrera, Haicheng Tao, Xingquan Zhu
    http://arxiv.org/abs/1910.09399v1

    • [cs.CV]Active 6D Multi-Object Pose Estimation in Cluttered Scenarios with Deep Reinforcement Learning
    Juil Sock, Guillermo Garcia-Hernando, Tae-Kyun Kim
    http://arxiv.org/abs/1910.08811v1

    • [cs.CV]Adversarial Skill Networks: Unsupervised Robot Skill Learning from Video
    Oier Mees, Markus Merklinger, Gabriel Kalweit, Wolfram Burgard
    http://arxiv.org/abs/1910.09430v1

    • [cs.CV]Analysis and a Solution of Momentarily Missed Detection for Anchor-based Object Detectors
    Yusuke Hosoya, Masanori Suganuma, Takayuki Okatani
    http://arxiv.org/abs/1910.09212v1

    • [cs.CV]Batch Face Alignment using a Low-rank GAN
    Jiabo Huang, Xiaohua Xie, Wei-Shi Zheng
    http://arxiv.org/abs/1910.09244v1

    • [cs.CV]CNN based Extraction of Panels/Characters from Bengali Comic Book Page Images
    Arpita Dutta, Samit Biswas
    http://arxiv.org/abs/1910.09233v1

    • [cs.CV]CSID: Center, Scale, Identity and Density-aware Pedestrian Detection in a Crowd
    Jialiang Zhang, Lixiang Lin, Yun-chen Chen, Yao Hu, Steven C. H. Hoi, Jianke Zhu
    http://arxiv.org/abs/1910.09188v1

    • [cs.CV]Cascaded Generation of High-quality Color Visible Face Images from Thermal Captures
    Naser Damer, Fadi Boutros, Khawla Mallat, Florian Kirchbuchner, Jean-Luc Dugelay, Arjan Kuijper
    http://arxiv.org/abs/1910.09524v1

    • [cs.CV]Component Attention Guided Face Super-Resolution Network: CAGFace
    Ratheesh Kalarot, Tao Li, Fatih Porikli
    http://arxiv.org/abs/1910.08761v1

    • [cs.CV]Coordinated Joint Multimodal Embeddings for Generalized Audio-Visual Zeroshot Classification and Retrieval of Videos
    Kranti Kumar Parida, Neeraj Matiyali, Tanaya Guha, Gaurav Sharma
    http://arxiv.org/abs/1910.08732v1

    • [cs.CV]Correlation Maximized Structural Similarity Loss for Semantic Segmentation
    Shuai Zhao, Boxi Wu, Wenqing Chu, Yao Hu, Deng Cai
    http://arxiv.org/abs/1910.08711v1

    • [cs.CV]Decoupling Representation and Classifier for Long-Tailed Recognition
    Bingyi Kang, Saining Xie, Marcus Rohrbach, Zhicheng Yan, Albert Gordo, Jiashi Feng, Yannis Kalantidis
    http://arxiv.org/abs/1910.09217v1

    • [cs.CV]Deep Parametric Indoor Lighting Estimation
    Marc-André Gardner, Yannick Hold-Geoffroy, Kalyan Sunkavalli, Christian Gagné, Jean-François Lalonde
    http://arxiv.org/abs/1910.08812v1

    • [cs.CV]Depth-wise Decomposition for Accelerating Separable Convolutions in Efficient Convolutional Neural Networks
    Yihui He, Jianing Qian, Jianren Wang
    http://arxiv.org/abs/1910.09455v1

    • [cs.CV]Directed-Weighting Group Lasso for Eltwise Blocked CNN Pruning
    Ke Zhan, Shimiao Jiang, Yu Bai, Yi Li, Xu Liu, Zhuoran Xu
    http://arxiv.org/abs/1910.09318v1

    • [cs.CV]DwNet: Dense warp-based network for pose-guided human video generation
    Polina Zablotskaia, Aliaksandr Siarohin, Bo Zhao, Leonid Sigal
    http://arxiv.org/abs/1910.09139v1

    • [cs.CV]Endowing Deep 3D Models with Rotation Invariance Based on Principal Component Analysis
    Zelin Xiao, Hongxin Lin, Renjie Li, Hongyang Chao, Shengyong Ding
    http://arxiv.org/abs/1910.08901v1

    • [cs.CV]Fast and Light-weight Portrait Segmentation
    Yuezun Li, Ao Luo, Siwei Lyu
    http://arxiv.org/abs/1910.08695v1

    • [cs.CV]Good, Better, Best: Textual Distractors Generation for Multi-Choice VQA via Policy Gradient
    Jiaying Lu, Xin Ye, Yi Ren, Yezhou Yang
    http://arxiv.org/abs/1910.09134v1

    • [cs.CV]Hadamard Codebook Based Deep Hashing
    Shen Chen, Liujuan Cao, Mingbao Lin, Yan Wang, Xiaoshuai Sun, Chenglin Wu, Jingfei Qiu, Rongrong Ji
    http://arxiv.org/abs/1910.09182v1

    • [cs.CV]Identity Document and banknote security forensics: a survey
    Albert Berenguel Centeno, Oriol Ramos Terrades, Josep Lladós Canet, Cristina Cañero Morales
    http://arxiv.org/abs/1910.08993v1

    • [cs.CV]Image Restoration Using Deep Regulated Convolutional Networks
    Peng Liu, Xiaoxiao Zhou, Junyi Yang, El Basha Mohammad D, Ruogu Fang
    http://arxiv.org/abs/1910.08853v1

    • [cs.CV]Improving Style Transfer with Calibrated Metrics
    Mao-Chuang Yeh, Shuai Tang, Anand Bhattad, Chuhang Zou, David Forsyth
    http://arxiv.org/abs/1910.09447v1

    • [cs.CV]Improving Vehicle Re-Identification using CNN Latent Spaces: Metrics Comparison and Track-to-track Extension
    Geoffrey Roman-Jimenez, Patrice Guyot, Thierry Malon, Sylvie Chambon, Vincent Charvillat, Alain Crouzil, André Péninou, Julien Pinquier, Florence Sedes, Christine Sénac
    http://arxiv.org/abs/1910.09458v1

    • [cs.CV]KuroNet: Pre-Modern Japanese Kuzushiji Character Recognition with Deep Learning
    Tarin Clanuwat, Alex Lamb, Asanobu Kitamoto
    http://arxiv.org/abs/1910.09433v1

    • [cs.CV]LinesToFacePhoto: Face Photo Generation from Lines with Conditional Self-Attention Generative Adversarial Network
    Yuhang Li, Xuejin Chen, Feng Wu, Zheng-Jun Zha
    http://arxiv.org/abs/1910.08914v1

    • [cs.CV]Looking Ahead: Anticipating Pedestrians Crossing with Future Frames Prediction
    Mohamed Chaabane, Ameni Trabelsi, Nathaniel Blanchard, Ross Beveridge
    http://arxiv.org/abs/1910.09077v1

    • [cs.CV]MeteorNet: Deep Learning on Dynamic 3D Point Cloud Sequences
    Xingyu Liu, Mengyuan Yan, Jeannette Bohg
    http://arxiv.org/abs/1910.09165v1

    • [cs.CV]MixModule: Mixed CNN Kernel Module for Medical Image Segmentation
    Henry H. Yu, Hao Sun, Ziwen Wang
    http://arxiv.org/abs/1910.08728v1

    • [cs.CV]Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments
    Junsheng Zhou, Yuwang Wang, Kaihuai Qin, Wenjun Zeng
    http://arxiv.org/abs/1910.08898v1

    • [cs.CV]NormGrad: Finding the Pixels that Matter for Training
    Sylvestre-Alvise Rebuffi, Ruth Fong, Xu Ji, Hakan Bilen, Andrea Vedaldi
    http://arxiv.org/abs/1910.08823v1

    • [cs.CV]Object landmark discovery through unsupervised adaptation
    Enrique Sanchez, Georgios Tzimiropoulos
    http://arxiv.org/abs/1910.09469v1

    • [cs.CV]Self-supervised classification of dynamic obstacles using the temporal information provided by videos
    Sid Ali Hamideche, Florent Chiaroni, Mohamed-Cherif Rahal
    http://arxiv.org/abs/1910.09094v1

    • [cs.CV]Semantics for Global and Local Interpretation of Deep Neural Networks
    Jindong Gu, Volker Tresp
    http://arxiv.org/abs/1910.09085v1

    • [cs.CV]Sketch2Code: Transformation of Sketches to UI in Real-time Using Deep Neural Network
    Vanita Jain, Piyush Agrawal, Subham Banga, Rishabh Kapoor, Shashwat Gulyani
    http://arxiv.org/abs/1910.08930v1

    • [cs.CV]SpatialFlow: Bridging All Tasks for Panoptic Segmentation
    Qiang Chen, Anda Cheng, Xiangyu He, Peisong Wang, Jian Cheng
    http://arxiv.org/abs/1910.08787v1

    • [cs.CV]Structured Prediction Helps 3D Human Motion Modelling
    Emre Aksan, Manuel Kaufmann, Otmar Hilliges
    http://arxiv.org/abs/1910.09070v1

    • [cs.CV]The Deepfake Detection Challenge (DFDC) Preview Dataset
    Brian Dolhansky, Russ Howes, Ben Pflaum, Nicole Baram, Cristian Canton Ferrer
    http://arxiv.org/abs/1910.08854v1

    • [cs.CV]Transferable Recognition-Aware Image Processing
    Zhuang Liu, Tinghui Zhou, Zhiqiang Shen, Bingyi Kang, Trevor Darrell
    http://arxiv.org/abs/1910.09185v1

    • [cs.CV]Tree-gated Deep Mixture-of-Experts For Pose-robust Face Alignment
    Estephe Arnaud, Arnaud Dapogny, Kevin Bailly
    http://arxiv.org/abs/1910.09450v1

    • [cs.CV]Unsupervised High-Resolution Depth Learning From Videos With Dual Networks
    Junsheng Zhou, Yuwang Wang, Kaihuai Qin, Wenjun Zeng
    http://arxiv.org/abs/1910.08897v1

    • [cs.CY]Digital Democracy: Episode IV — A New Hope, How a Corporation for Public Software Could Transform Digital Engagement for Government and Civil Society
    John Gastil, Todd Davies
    http://arxiv.org/abs/1910.08604v1

    • [cs.DB]Demystifying Graph Databases: Analysis and Taxonomy of Data Organization, System Designs, and Graph Queries
    Maciej Besta, Emanuel Peter, Robert Gerstenberger, Marc Fischer, Michał Podstawski, Claude Barthels, Gustavo Alonso, Torsten Hoefler
    http://arxiv.org/abs/1910.09017v1

    • [cs.DC]BatteryLab, A Distributed Power Monitoring Platform For Mobile Devices
    Matteo Varvello, Kleomenis Katevas, Mihai Plesa, Hamed Haddadi, Benjamin Livshits
    http://arxiv.org/abs/1910.08951v1

    • [cs.DC]DLB: Deep Learning Based Load Balancing
    Xiaoke Zhu, Qi Zhang, Ling Liu, Taining Cheng, Shaowen Yao, Wei Zhou, and Jing He
    http://arxiv.org/abs/1910.08494v2

    • [cs.DC]Microservices based Framework to Support Interoperable IoT Applications for Enhanced Data Analytics
    Sajjad Ali, Muhammad Aslam Jarwar, Ilyoung Chong
    http://arxiv.org/abs/1910.08713v1

    • [cs.DC]RLScheduler: Learn to Schedule HPC Batch Jobs Using Deep Reinforcement Learning
    Di Zhang, Dong Dai, Youbiao He, Forrest Sheng Bao
    http://arxiv.org/abs/1910.08925v1

    • [cs.DC]Reconfigurable Lattice Agreement and Applications
    Petr Kuznetsov, Thibault Rieutord, Sara Tucci-Piergiovanni
    http://arxiv.org/abs/1910.09264v1

    • [cs.DL]Science and Technology Advance through Surprise
    Feng Shi, James Evans
    http://arxiv.org/abs/1910.09370v1

    • [cs.DS]Adaptive Learned Bloom Filter (Ada-BF): Efficient Utilization of the Classifier
    Zhenwei Dai, Anshumali Shrivastava
    http://arxiv.org/abs/1910.09131v1

    • [cs.DS]Temporal Network Sampling
    Nesreen K. Ahmed, Nick Duffield, Ryan A. Rossi
    http://arxiv.org/abs/1910.08657v1

    • [cs.GR]Real-Time Lip Sync for Live 2D Animation
    Deepali Aneja, Wilmot Li
    http://arxiv.org/abs/1910.08685v1

    • [cs.GT]Incentivize Diffusion with Fair Rewards on Networks
    Wen Zhang, Dengji Zhao, Yao Zhang
    http://arxiv.org/abs/1910.09268v1

    • [cs.GT]Semi-Decentralized Coordinated Online Learning for Continuous Games with Coupled Constraints via Augmented Lagrangian
    Ezra Tampubolon, Holger Boche
    http://arxiv.org/abs/1910.09276v1

    • [cs.HC]Toward automatic comparison of visualization techniques: Application to graph visualization
    R. Bourqui, R. Giot, D. Auber
    http://arxiv.org/abs/1910.09477v1

    • [cs.HC]Two Case Studies of Experience Prototyping Machine Learning Systems in the Wild
    Qian Yang
    http://arxiv.org/abs/1910.09137v1

    • [cs.IR]A Comparison of Semantic Similarity Methods for Maximum Human Interpretability
    Pinky Sitikhu, Kritish Pahi, Pujan Thapa, Subarna Shakya
    http://arxiv.org/abs/1910.09129v1

    • [cs.IR]EQSA: Earthquake Situational Analytics from Social Media
    Huyen Nguyen, Tommy Dang
    http://arxiv.org/abs/1910.08881v1

    • [cs.IR]On large-scale genre classification in symbolically encoded music by automatic identification of repeating patterns
    Andres Ferraro, Kjell Lemström
    http://arxiv.org/abs/1910.09242v1

    • [cs.IR]Personalizing Graph Neural Networks with Attention Mechanism for Session-based Recommendation
    Shu Wu, Mengqi Zhang, Xin Jiang, Xu Ke, Liang Wang
    http://arxiv.org/abs/1910.08887v1

    • [cs.IR]The Bitwise Hashing Trick for Personalized Search
    Braddock Gaskill
    http://arxiv.org/abs/1910.08646v1

    • [cs.IT]An Open-Source Toolbox for Computer-Aided Investigation on the Fundamental Limits of Information Systems, Version 0.1
    Chao Tian, James S. Plank, Brent Hurst
    http://arxiv.org/abs/1910.08567v1

    • [cs.IT]Distributed Quantization for Sparse Time Sequences
    Alejandro Cohen, Nir Shlezinger, Salman Salamatian, Yonina C. Eldar, Muriel Médard
    http://arxiv.org/abs/1910.09519v1

    • [cs.IT]Dynamic Content Update for Wireless Edge Caching via Deep Reinforcement Learning
    Pingyang Wu, Jun Li, Long Shi, Ming Ding, Kui Cai, Fuli Yang
    http://arxiv.org/abs/1910.08723v1

    • [cs.IT]Locally Decodable Index Codes
    Lakshmi Natarajan, Prasad Krishnan, V. Lalitha, Hoang Dau
    http://arxiv.org/abs/1910.08745v1

    • [cs.IT]Matrix-Product Codes over Commutative Rings and Constructions Arising from $(σ,δ)$-Codes
    Mhammed Boulagouaz, Abdulaziz Deajim
    http://arxiv.org/abs/1910.08899v1

    • [cs.IT]Multi-User MABs with User Dependent Rewards for Uncoordinated Spectrum Access
    Akshayaa Magesh, Venugopal V. Veeravalli
    http://arxiv.org/abs/1910.09091v1

    • [cs.IT]On Self-Orthogonality and Self-Duality of Matrix-Product Codes over Commutative Rings
    Abdulaziz Deajim, Mohamed Bouye
    http://arxiv.org/abs/1910.08900v1

    • [cs.IT]Secrecy and Covert Communications against UAV Surveillance via Multi-Hop Networks
    Hui-Ming Wang, Yan Zhang, Xu Zhang, Zhetao Li
    http://arxiv.org/abs/1910.09197v1

    • [cs.IT]Sub-Nyquist Sampling of Sparse and Correlated Signals in Array Processing
    Ali Ahmed, Fahad Shamshad
    http://arxiv.org/abs/1910.08792v1

    • [cs.IT]Trajectory Design for Energy Minimization in UAV-enabled Wireless Communications with Latency Constraints
    Dinh-Hieu Tran, Thang X. Vu, Symeon Chatzinotas, Shahram ShahbazPanahi, Björn Ottersten
    http://arxiv.org/abs/1910.08612v1

    • [cs.LG]A $ν$- support vector quantile regression model with automatic accuracy control
    Pritam Anand, Reshma Rastogi, Suresh Chandra
    http://arxiv.org/abs/1910.09168v1

    • [cs.LG]A New Framework for Multi-Agent Reinforcement Learning — Centralized Training and Exploration with Decentralized Execution via Policy Distillation
    Gang Chen
    http://arxiv.org/abs/1910.09152v1

    • [cs.LG]A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning
    Nicolas Carion, Gabriel Synnaeve, Alessandro Lazaric, Nicolas Usunier
    http://arxiv.org/abs/1910.08809v1

    • [cs.LG]A game method for improving the interpretability of convolution neural network
    Jinwei Zhao, Qizhou Wang, Fuqiang Zhang, Wanli Qiu, Yufei Wang, Yu Liu, Guo Xie, Weigang Ma, Bin Wang, Xinhong Hei
    http://arxiv.org/abs/1910.09090v1

    • [cs.LG]Aggregated Gradient Langevin Dynamics
    Chao Zhang, Jiahao Xie, Zebang Shen, Peilin Zhao, Tengfei Zhou, Hui Qian
    http://arxiv.org/abs/1910.09223v1

    • [cs.LG]Aleatoric and Epistemic Uncertainty in Machine Learning: A Tutorial Introduction
    Eyke Hüllermeier, Willem Waegeman
    http://arxiv.org/abs/1910.09457v1

    • [cs.LG]All-Action Policy Gradient Methods: A Numerical Integration Approach
    Benjamin Petit, Loren Amdahl-Culleton, Yao Liu, Jimmy Smith, Pierre-Luc Bacon
    http://arxiv.org/abs/1910.09093v1

    • [cs.LG]Amortized Rejection Sampling in Universal Probabilistic Programming
    Saeid Naderiparizi, Adam Ścibior, Andreas Munk, Mehrdad Ghadiri, Atılım Güneş Baydin, Bradley Gram-Hansen, Christian Schroeder de Witt, Robert Zinkov, Philip H. S. Torr, Tom Rainforth, Yee Whye Teh, Frank Wood
    http://arxiv.org/abs/1910.09056v1

    • [cs.LG]An Alternative Surrogate Loss for PGD-based Adversarial Testing
    Sven Gowal, Jonathan Uesato, Chongli Qin, Po-Sen Huang, Timothy Mann, Pushmeet Kohli
    http://arxiv.org/abs/1910.09338v1

    • [cs.LG]An Optimal Transport Framework for Zero-Shot Learning
    Wenlin Wang, Hongteng Xu, Guoyin Wang, Wenqi Wang, Lawrence Carin
    http://arxiv.org/abs/1910.09057v1

    • [cs.LG]An Unbiased Risk Estimator for Learning with Augmented Classes
    Yu-Jie Zhang, Peng Zhao, Zhi-Hua Zhou
    http://arxiv.org/abs/1910.09388v1

    • [cs.LG]Approximate Sampling using an Accelerated Metropolis-Hastings based on Bayesian Optimization and Gaussian Processes
    Asif J. Chowdhury, Gabriel Terejanu
    http://arxiv.org/abs/1910.09347v1

    • [cs.LG]Approximation capabilities of neural networks on unbounded domains
    Yang Qu, Ming-Xi Wang
    http://arxiv.org/abs/1910.09293v1

    • [cs.LG]Are Perceptually-Aligned Gradients a General Property of Robust Classifiers?
    Simran Kaur, Jeremy Cohen, Zachary C. Lipton
    http://arxiv.org/abs/1910.08640v1

    • [cs.LG]Boosting Mapping Functionality of Neural Networks via Latent Feature Generation based on Reversible Learning
    Jongmin Yu
    http://arxiv.org/abs/1910.09108v1

    • [cs.LG]Boosting Network Weight Separability via Feed-Backward Reconstruction
    Jongmin Yu, Younkwan Lee, Moongu Jeon
    http://arxiv.org/abs/1910.09024v1

    • [cs.LG]Context-Driven Data Mining through Bias Removal and Data Incompleteness Mitigation
    Feras A. Batarseh, Ajay Kulkarni
    http://arxiv.org/abs/1910.08670v1

    • [cs.LG]Contextual Prediction Difference Analysis
    Jindong Gu, Volker Tresp
    http://arxiv.org/abs/1910.09086v1

    • [cs.LG]CreditPrint: Credit Investigation via Geographic Footprints by Deep Learning
    Xiao Han, Ruiqing Ding, Leye Wang, Hailiang Huang
    http://arxiv.org/abs/1910.08734v1

    • [cs.LG]Dealing with Sparse Rewards in Reinforcement Learning
    Joshua Hare
    http://arxiv.org/abs/1910.09281v1

    • [cs.LG]Dictionary Learning with Almost Sure Error Constraints
    Mohammed Rayyan Sheriff, Debasish Chatterjee
    http://arxiv.org/abs/1910.08828v1

    • [cs.LG]Differentiable Deep Clustering with Cluster Size Constraints
    Aude Genevay, Gabriel Dulac-Arnold, Jean-Philippe Vert
    http://arxiv.org/abs/1910.09036v1

    • [cs.LG]Discovering the Compositional Structure of Vector Representations with Role Learning Networks
    Paul Soulos, Tom McCoy, Tal Linzen, Paul Smolensky
    http://arxiv.org/abs/1910.09113v1

    • [cs.LG]Diverse Behavior Is What Game AI Needs: Generating Varied Human-Like Playing Styles Using Evolutionary Multi-Objective Deep Reinforcement Learning
    Yan Zheng, Ruimin Shen, Jianye Hao, Yinfeng Chen, Changjie Fan
    http://arxiv.org/abs/1910.09022v1

    • [cs.LG]Explainable AI: Deep Reinforcement Learning Agents for Residential Demand Side Cost Savings in Smart Grids
    Hareesh Kumar
    http://arxiv.org/abs/1910.08719v1

    • [cs.LG]Fast Exact Matrix Completion: A Unifying Optimization Framework
    Dimitris Bertsimas, Michael Lingzhi Li
    http://arxiv.org/abs/1910.09092v1

    • [cs.LG]From Importance Sampling to Doubly Robust Policy Gradient
    Jiawei Huang, Nan Jiang
    http://arxiv.org/abs/1910.09066v1

    • [cs.LG]Generative Hierarchical Models for Parts, Objects, and Scenes
    Fei Deng, Zhuo Zhi, Sungjin Ahn
    http://arxiv.org/abs/1910.09119v1

    • [cs.LG]Graph Construction from Data using Non Negative Kernel regression (NNK Graphs)
    Sarath Shekkizhar, Antonio Ortega
    http://arxiv.org/abs/1910.09383v1

    • [cs.LG]Identification of Interaction Clusters Using a Semi-supervised Hierarchical Clustering Method
    Yu Chen, Yuanyuan Yang, Yaochu Jin, Xiufen Zou
    http://arxiv.org/abs/1910.08864v1

    • [cs.LG]Image Difficulty Curriculum for Generative Adversarial Networks (CuGAN)
    Petru Soviany, Claudiu Ardei, Radu Tudor Ionescu, Marius Leordeanu
    http://arxiv.org/abs/1910.08967v1

    • [cs.LG]Implementation of a modified Nesterov’s Accelerated quasi-Newton Method on Tensorflow
    S. Indrapriyadarsini, Shahrzad Mahboubi, Hiroshi Ninomiya, Hideki Asai
    http://arxiv.org/abs/1910.09158v1

    • [cs.LG]Integrals over Gaussians under Linear Domain Constraints
    Alexandra Gessner, Oindrila Kanjilal, Philipp Hennig
    http://arxiv.org/abs/1910.09328v1

    • [cs.LG]Introduction to Coresets: Accurate Coresets
    Ibrahim Jubran, Alaa Maalouf, Dan Feldman
    http://arxiv.org/abs/1910.08707v1

    • [cs.LG]LSTM-Assisted Evolutionary Self-Expressive Subspace Clustering
    Di Xu, Tianhang Long, Junbin Gao
    http://arxiv.org/abs/1910.08862v1

    • [cs.LG]Landing Probabilities of Random Walks for Seed-Set Expansion in Hypergraphs
    Eli Chien, Pan Li, Olgica Milenkovic
    http://arxiv.org/abs/1910.09040v1

    • [cs.LG]Learning GANs and Ensembles Using Discrepancy
    Ben Adlam, Corinna Cortes, Mehryar Mohri, Ningshan Zhang
    http://arxiv.org/abs/1910.08965v1

    • [cs.LG]Learning Hierarchical Feature Space Using CLAss-specific Subspace Multiple Kernel — Metric Learning for Classification
    Yinan Yu, Tomas McKelvey
    http://arxiv.org/abs/1910.09309v1

    • [cs.LG]Learning from both experts and data
    Rémi Besson, Erwan Le Pennec, Stéphanie Allassonnière
    http://arxiv.org/abs/1910.09043v1

    • [cs.LG]Learning to Learn by Zeroth-Order Oracle
    Yangjun Ruan, Yuanhao Xiong, Sashank Reddi, Sanjiv Kumar, Cho-Jui Hsieh
    http://arxiv.org/abs/1910.09464v1

    • [cs.LG]Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text
    Oluwaseyi Feyisetan, Tom Diethe, Thomas Drake
    http://arxiv.org/abs/1910.08917v1

    • [cs.LG]Leveraging inductive bias of neural networks for learning without explicit human annotations
    Fatih Furkan Yilmaz, Reinhard Heckel
    http://arxiv.org/abs/1910.09055v1

    • [cs.LG]Machine Learning Systems for Highly-Distributed and Rapidly-Growing Data
    Kevin Hsieh
    http://arxiv.org/abs/1910.08663v1

    • [cs.LG]Machine Learning for AC Optimal Power Flow
    Neel Guha, Zhecheng Wang, Matt Wytock, Arun Majumdar
    http://arxiv.org/abs/1910.08842v1

    • [cs.LG]Making Bayesian Predictive Models Interpretable: A Decision Theoretic Approach
    Homayun Afrabandpey, Tomi Peltola, Juho Piironen, Aki Vehtari, Samuel Kaski
    http://arxiv.org/abs/1910.09358v1

    • [cs.LG]Maximum Probability Principle and Black-Box Priors
    Amir Emad Marvasti, Ehsan Emad Marvasti, Hassan Foroosh
    http://arxiv.org/abs/1910.09417v1

    • [cs.LG]Mining GOLD Samples for Conditional GANs
    Sangwoo Mo, Chiheon Kim, Sungwoong Kim, Minsu Cho, Jinwoo Shin
    http://arxiv.org/abs/1910.09170v1

    • [cs.LG]Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach
    Nan Lu, Tianyi Zhang, Gang Niu, Masashi Sugiyama
    http://arxiv.org/abs/1910.08974v1

    • [cs.LG]Momentum in Reinforcement Learning
    Nino Vieillard, Bruno Scherrer, Olivier Pietquin, Matthieu Geist
    http://arxiv.org/abs/1910.09322v1

    • [cs.LG]Movienet: A Movie Multilayer Network Model using Visual and Textual Semantic Cues
    Youssef Mourchid, Benjamin Renoust, Olivier Roupin, Le Van, Hocine Cherifi, Mohammed El Hassouni
    http://arxiv.org/abs/1910.09368v1

    • [cs.LG]Multi-player Multi-Armed Bandits with non-zero rewards on collisions for uncoordinated spectrum access
    Akshayaa Magesh, Venugopal V. Veeravalli
    http://arxiv.org/abs/1910.09089v1

    • [cs.LG]NASIB: Neural Architecture Search withIn Budget
    Abhishek Singh, Anubhav Garg, Jinan Zhou, Shiv Ram Dubey, Debo Dutta
    http://arxiv.org/abs/1910.08665v1

    • [cs.LG]Neural Spectrum Alignment
    Dmitry Kopitkov, Vadim Indelman
    http://arxiv.org/abs/1910.08720v1

    • [cs.LG]Neuro-SERKET: Development of Integrative Cognitive System through the Composition of Deep Probabilistic Generative Models
    Tadahiro Taniguchi, Tomoaki Nakamura, Masahiro Suzuki, Ryo Kuniyasu, Kaede Hayashi, Akira Taniguchi, Takato Horii, Takayuki Nagai
    http://arxiv.org/abs/1910.08918v1

    • [cs.LG]OffWorld Gym: open-access physical robotics environment for real-world reinforcement learning benchmark and research
    Ashish Kumar, Toby Buckley, Qiaozhi Wang, Alicia Kavelaars, Ilya Kuzovkin
    http://arxiv.org/abs/1910.08639v1

    • [cs.LG]On Adaptivity in Information-constrained Online Learning
    Siddharth Mitra, Aditya Gopalan
    http://arxiv.org/abs/1910.08805v1

    • [cs.LG]Online Bagging for Anytime Transfer Learning
    Guokun Chi, Min Jiang, Xing Gao, Weizhen Hu, Shihui Guo, Kay Chen Tan
    http://arxiv.org/abs/1910.08945v1

    • [cs.LG]Online Pricing with Offline Data: Phase Transition and Inverse Square Law
    Jinzhi Bu, David Simchi-Levi, Yunzong Xu
    http://arxiv.org/abs/1910.08693v1

    • [cs.LG]Perception-Distortion Trade-off with Restricted Boltzmann Machines
    Chris Cannella, Jie Ding, Mohammadreza Soltani, Vahid Tarokh
    http://arxiv.org/abs/1910.09122v1

    • [cs.LG]Policy Learning for Malaria Control
    Van Bach Nguyen, Belaid Mohamed Karim, Bao Long Vu, Jörg Schlötterer, Michael Granitzer
    http://arxiv.org/abs/1910.08926v1

    • [cs.LG]Predicting ice flow using machine learning
    Yimeng Min, S. Karthik Mukkavilli, Yoshua Bengio
    http://arxiv.org/abs/1910.08922v1

    • [cs.LG]Pricing Mechanism for Resource Sustainability in Competitive Online Learning Multi-Agent Systems
    Ezra Tampubolon, Holger Boche
    http://arxiv.org/abs/1910.09314v1

    • [cs.LG]Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations
    Oluwaseyi Feyisetan, Borja Balle, Thomas Drake, Tom Diethe
    http://arxiv.org/abs/1910.08902v1

    • [cs.LG]Recovering Localized Adversarial Attacks
    Jan Philip Göpfert, Heiko Wersing, Barbara Hammer
    http://arxiv.org/abs/1910.09239v1

    • [cs.LG]Regularization Matters in Policy Optimization
    Zhuang Liu, Xuanlin Li, Bingyi Kang, Trevor Darrell
    http://arxiv.org/abs/1910.09191v1

    • [cs.LG]Reverse Experience Replay
    Egor Rotinov
    http://arxiv.org/abs/1910.08780v1

    • [cs.LG]Self-Educated Language Agent With Hindsight Experience Replay For Instruction Following
    Geoffrey Cideron, Mathieu Seurin, Florian Strub, Olivier Pietquin
    http://arxiv.org/abs/1910.09451v1

    • [cs.LG]Separable Convolutional Eigen-Filters (SCEF): Building Efficient CNNs Using Redundancy Analysis
    Samuel Scheidegger, Yinan Yu, Tomas McKelvey
    http://arxiv.org/abs/1910.09359v1

    • [cs.LG]Sparse-Dense Subspace Clustering
    Shuai Yang, Wenqi Zhu, Yuesheng Zhu
    http://arxiv.org/abs/1910.08909v1

    • [cs.LG]Sparsification as a Remedy for Staleness in Distributed Asynchronous SGD
    Rosa Candela, Giulio Franzese, Maurizio Filippone, Pietro Michiardi
    http://arxiv.org/abs/1910.09466v1

    • [cs.LG]Stochastic Recursive Gradient-Based Methods for Projection-Free Online Learning
    Jiahao Xie, Zebang Shen, Chao Zhang, Hui Qian, Boyu Wang
    http://arxiv.org/abs/1910.09396v1

    • [cs.LG]Toward Metrics for Differentiating Out-of-Distribution Sets
    Mahdieh Abbasi, Changjian Shui, Arezoo Rajabi, Christian Gagne, Rakesh Bobba
    http://arxiv.org/abs/1910.08650v1

    • [cs.LG]Towards Further Understanding of Sparse Filtering via Information Bottleneck
    Fabio Massimo Zennaro, Ke Chen
    http://arxiv.org/abs/1910.08964v1

    • [cs.LG]Towards Quantifying Intrinsic Generalization of Deep ReLU Networks
    Shaeke Salman, Canlin Zhang, Xiuwen Liu, Washington Mio
    http://arxiv.org/abs/1910.08581v1

    • [cs.LG]Towards User Empowerment
    Martin Pawelczyk, Johannes Haug, Klaus Broelemann, Gjergji Kasneci
    http://arxiv.org/abs/1910.09398v1

    • [cs.LG]Unsupervised Out-of-Distribution Detection with Batch Normalization
    Jiaming Song, Yang Song, Stefano Ermon
    http://arxiv.org/abs/1910.09115v1

    • [cs.LG]Who wants accurate models? Arguing for a different metrics to take classification models seriously
    Federico Cabitza, Andrea Campagner
    http://arxiv.org/abs/1910.09246v1

    • [cs.LG]Zero-shot Learning via Simultaneous Generating and Learning
    Hyeonwoo Yu, Beomhee Lee
    http://arxiv.org/abs/1910.09446v1

    • [cs.LO]Computer-supported Analysis of Positive Properties, Ultrafilters and Modal Collapse in Variants of Gödel’s Ontological Argument
    Christoph Benzmüller, David Fuenmayor
    http://arxiv.org/abs/1910.08955v1

    • [cs.MA]Autonomous Industrial Management via Reinforcement Learning: Self-Learning Agents for Decision-Making — A Review
    Leonardo A. Espinosa Leal, Magnus Westerlund, Anthony Chapman
    http://arxiv.org/abs/1910.08942v1

    • [cs.MA]Multi-agent Hierarchical Reinforcement Learning with Dynamic Termination
    Dongge Han, Wendelin Boehmer, Michael Wooldridge, Alex Rogers
    http://arxiv.org/abs/1910.09508v1

    • [cs.MM]Automated Composition of Picture-Synched Music Soundtracks for Movies
    Vansh Dassani, Jon Bird, Dave Cliff
    http://arxiv.org/abs/1910.08773v1

    • [cs.NE]Evolutionary Dynamic Multi-objective Optimization Via Regression Transfer Learning
    Zhengzhong Wang, Min Jiang, Xing Gao, Liang Feng, Weizhen Hu, Kay Chen Tan
    http://arxiv.org/abs/1910.08753v1

    • [cs.NE]S4NN: temporal backpropagation for spiking neural networks with one spike per neuron
    Saeed Reza Kheradpisheh, Timothée Masquelier
    http://arxiv.org/abs/1910.09495v1

    • [cs.NE]Solving Dynamic Multi-objective Optimization Problems Using Incremental Support Vector Machine
    Weizhen Hu, Min Jiang, Xing Gao, Kay Chen Tan, Yiu-ming Cheung
    http://arxiv.org/abs/1910.08751v1

    • [cs.NI]Downlink Performance of Dense Antenna Deployment: To Distribute or Concentrate?
    Mounia Hamidouche, Ejder Baştuğ, Jihong Park, Laura Cottatellucci, Mérouane Debbah
    http://arxiv.org/abs/1910.08868v1

    • [cs.OH]Benchmark Dataset for Timetable Optimization of Bus Routes in the City of New Delhi
    Anubhav Jain, Avdesh Kumar, Saumya Balodi, Pravesh Biyani
    http://arxiv.org/abs/1910.08903v1

    • [cs.RO]CAPRICORN: Communication Aware Place Recognition using Interpretable Constellations of Objects in Robot Networks
    Benjamin Ramtoula, Ricardo de Azambuja, Giovanni Beltrame
    http://arxiv.org/abs/1910.08810v1

    • [cs.RO]Electric Sheep Team Description Paper Humanoid League Kid-Size 2019
    Daniel Barry, Andrew Curtis-Black, Merel Keijsers, Munir Shah, Matthew Young, Humayun Khan, Banon Hopman
    http://arxiv.org/abs/1910.08949v1

    • [cs.RO]Modelling Generalized Forces with Reinforcement Learning for Sim-to-Real Transfer
    Rae Jeong, Jackie Kay, Francesco Romano, Thomas Lampe, Tom Rothorl, Abbas Abdolmaleki, Tom Erez, Yuval Tassa, Francesco Nori
    http://arxiv.org/abs/1910.09471v1

    • [cs.RO]Planning, Learning and Reasoning Framework for Robot Truck Unloading
    Fahad Islam, Anirudh Vemula, Sung-Kyun Kim, Andrew Dornbush, Oren Salzman, Maxim Likhachev
    http://arxiv.org/abs/1910.09453v1

    • [cs.RO]Self-Supervised Sim-to-Real Adaptation for Visual Robotic Manipulation
    Rae Jeong, Yusuf Aytar, David Khosid, Yuxiang Zhou, Jackie Kay, Thomas Lampe, Konstantinos Bousmalis, Francesco Nori
    http://arxiv.org/abs/1910.09470v1

    • [cs.SD]Clotho: An Audio Captioning Dataset
    Konstantinos Drossos, Samuel Lipping, Tuomas Virtanen
    http://arxiv.org/abs/1910.09387v1

    • [cs.SD]Deep speech inpainting of time-frequency masks
    Mikolaj Kegler, Pierre Beckmann, Milos Cernak
    http://arxiv.org/abs/1910.09058v1

    • [cs.SD]Multi-Band Multi-Resolution Fully Convolutional Neural Networks for Singing Voice Separation
    Emad M. Grais, Fei Zhao, Mark D. Plumbley
    http://arxiv.org/abs/1910.09266v1

    • [cs.SD]Musical Instrument Playing Technique Detection Based on FCN: Using Chinese Bowed-Stringed Instrument as an Example
    Zehao Wang, Jingru Li, Xiaoou Chen, Zijin Li, Shicheng Zhang, Baoqiang Han, Deshun Yang
    http://arxiv.org/abs/1910.09021v1

    • [cs.SD]Representation Learning for Discovering Phonemic Tone Contours
    Bai Li, Jing Yi Xie, Frank Rudzicz
    http://arxiv.org/abs/1910.08987v1

    • [cs.SI]Modelling Online Comment Threads from their Start
    Rachel Krohn, Tim Weninger
    http://arxiv.org/abs/1910.08575v1

    • [cs.SI]Opinion shaping in social networks using reinforcement learning
    Vivek Borkar, Alexandre Reiffers-Masson
    http://arxiv.org/abs/1910.08802v1

    • [cs.SI]Towards Interpretable Graph Modeling with Vertex Replacement Grammars
    Justus Hibshman, Satyaki Sikdar, Tim Weninger
    http://arxiv.org/abs/1910.08579v1

    • [cs.SI]User-Aware Folk Popularity Rank: User-Popularity-Based Tag Recommendation That Can Enhance Social Popularity
    Xueting Wang, Yiwei Zhang, Toshihiko Yamasaki
    http://arxiv.org/abs/1910.09307v1

    • [cs.SI]Using machine learning and information visualisation for discovering latent topics in Twitter news
    Vladimir Vargas-Calderón, Marlon Steibeck Dominguez, N. Parra-A., Herbert Vinck-Posada, Jorge E. Camargo
    http://arxiv.org/abs/1910.09114v1

    • [econ.EM]Bounds in continuous instrumental variable models
    Florian Gunsilius
    http://arxiv.org/abs/1910.09502v1

    • [econ.GN]Beating the House: Identifying Inefficiencies in Sports Betting Markets
    Sathya Ramesh, Ragib Mostofa, Marco Bornstein, John Dobelman
    http://arxiv.org/abs/1910.08858v1

    • [eess.AS]Adversarial Attacks on Spoofing Countermeasures of automatic speaker verification
    Songxiang Liu, Haibin Wu, Hung-yi Lee, Helen Meng
    http://arxiv.org/abs/1910.08716v1

    • [eess.AS]Comparative Study between Adversarial Networks and Classical Techniques for Speech Enhancement
    Tito Spadini, Ricardo Suyama
    http://arxiv.org/abs/1910.09522v1

    • [eess.IV]Attention Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images
    Aleksandar Vakanski, Min Xian, Phoebe Freer
    http://arxiv.org/abs/1910.08978v1

    • [eess.IV]Attention Guided Metal Artifact Correction in MRI using Deep Neural Networks
    Jee Won Kim, Kinam Kwon, Byungjai Kim, HyunWook Park
    http://arxiv.org/abs/1910.08705v1

    • [eess.IV]Automatic Lumbar Spinal CT Image Segmentation with a Dual Densely Connected U-Net
    He Tang, Xiaobing Pei, Shilong Huang, Xin Li, Chao Liu
    http://arxiv.org/abs/1910.09198v1

    • [eess.IV]CAI4CAI: The Rise of Contextual Artificial Intelligence in Computer Assisted Interventions
    Tom Vercauteren, Mathias Unberath, Nicolas Padoy, Nassir Navab
    http://arxiv.org/abs/1910.09031v1

    • [eess.IV]Combining Shape Priors with Conditional Adversarial Networks for Improved Scapula Segmentation in MR images
    Arnaud Boutillon, Bhushan Borotikar, Valérie Burdin, Pierre-henri Conze
    http://arxiv.org/abs/1910.08963v1

    • [eess.IV]Deep Mouse: An End-to-end Auto-context Refinement Framework for Brain Ventricle and Body Segmentation in Embryonic Mice Ultrasound Volumes
    Tongda Xu, Ziming Qiu, William Das, Chuiyu Wang, Jack Langerman, Nitin Nair, Orlando Aristizabal, Jonathan Mamou, Daniel H. Turnbull, Jeffrey A. Ketterling, Yao Wang
    http://arxiv.org/abs/1910.09061v1

    • [eess.IV]Gastroscopic Panoramic View: Application to Automatic Polyps Detection under Gastroscopy
    Chenfei Shi, Yan Xue, Chuan Jiang, Hui Tian, Bei Liu
    http://arxiv.org/abs/1910.08697v1

    • [eess.IV]Hyperspectral Image Classification Based on Adaptive Sparse Deep Network
    Jingwen Yan, Zixin Xie, Jingyao Chen, Yinan Liu, Lei Liu
    http://arxiv.org/abs/1910.09405v1

    • [eess.IV]KRNET: Image Denoising with Kernel Regulation Network
    Peng Liu, Xiaoxiao Zhou, Junyiyang Li, El Basha Mohammad D, Ruogu Fang
    http://arxiv.org/abs/1910.08867v1

    • [eess.IV]LEt-SNE: A Hybrid Approach To Data Embedding and Visualization of Hyperspectral Imagery
    Megh Shukla, Biplab Banerjee, Krishna Mohan Buddhiraju
    http://arxiv.org/abs/1910.08790v1

    • [eess.IV]Learning a Generic Adaptive Wavelet Shrinkage Function for Denoising
    Tobias Alt, Joachim Weickert
    http://arxiv.org/abs/1910.09234v1

    • [eess.IV]MIScnn: A Framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning
    Dominik Müller, Frank Kramer
    http://arxiv.org/abs/1910.09308v1

    • [eess.IV]Modeling Disease Progression In Retinal OCTs With Longitudinal Self-Supervised Learning
    Antoine Rivail, Ursula Schmidt-Erfurth, Wolf-Dieter Vogel, Sebastian M. Waldstein, Sophie Riedl, Christoph Grechenig, Zhichao Wu, Hrvoje Bogunović
    http://arxiv.org/abs/1910.09420v1

    • [eess.IV]Probabilistic Radiomics: Ambiguous Diagnosis with Controllable Shape Analysis
    Jiancheng Yang, Rongyao Fang, Bingbing Ni, Yamin Li, Yi Xu, Linguo Li
    http://arxiv.org/abs/1910.08878v1

    • [eess.IV]ProxIQA: A Proxy Approach to Perceptual Optimization of Learned Image Compression
    Li-Heng Chen, Christos G. Bampis, Zhi Li, Andrey Norkin, Alan C. Bovik
    http://arxiv.org/abs/1910.08845v1

    • [eess.IV]SANet:Superpixel Attention Network for Skin Lesion Attributes Detection
    Xinzi He, Baiying Lei, Tianfu Wang
    http://arxiv.org/abs/1910.08995v1

    • [eess.IV]Self-Supervised Physics-Based Deep Learning MRI Reconstruction Without Fully-Sampled Data
    Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Steen Moeller, Jutta Ellermann, Kâmil Uǧurbil, Mehmet Akçakaya
    http://arxiv.org/abs/1910.09116v1

    • [eess.IV]Spectral Characterization of functional MRI data on voxel-resolution cortical graphs
    Hamid Behjat, Martin Larsson
    http://arxiv.org/abs/1910.09507v1

    • [eess.IV]Tracking-Assisted Segmentation of Biological Cells
    Deepak K. Gupta, Nathan de Bruijn, Andreas Panteli, Efstratios Gavves
    http://arxiv.org/abs/1910.08735v1

    • [eess.IV]Utilising Low Complexity CNNs to Lift Non-Local Redundancies in Video Coding
    Jan P. Klopp, Liang-Gee Chen, Shao-Yi Chien
    http://arxiv.org/abs/1910.08737v1

    • [eess.IV]i-RIM applied to the fastMRI challenge
    Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan Caan, Max Welling
    http://arxiv.org/abs/1910.08952v1

    • [eess.IV]ipA-MedGAN: Inpainting of Arbitrarily Regions in Medical Modalities
    Karim Armanious, Vijeth Kumar, Sherif Abdulatif, Tobias Hepp, Sergios Gatidis, Bin Yang
    http://arxiv.org/abs/1910.09230v1

    • [eess.SP]Model Order Selection in DoA Scenarios via Cross-Entropy based Machine Learning Techniques
    Andreas Barthelme, Reinhard Wiesmayr, Wolfgang Utschick
    http://arxiv.org/abs/1910.09284v1

    • [eess.SP]UW-SVC: Scalable Video Coding Transmission for In-network Underwater Imagery Analysis
    Mehdi Rahmati, Dario Pompili
    http://arxiv.org/abs/1910.08844v1

    • [eess.SY]A Dynamic System Model for Personalized Healthcare Delivery and Managed Individual Health Outcomes
    Inas S. Khayal, Amro M. Farid
    http://arxiv.org/abs/1910.09104v1

    • [eess.SY]Autonomous Control of a Quadrotor-Manipulator; Application of Extended State Disturbance Observer
    Kabir Abdulmajeed
    http://arxiv.org/abs/1910.09052v1

    • [eess.SY]Ensemble learning based linear power flow
    Ren Hu, QiFeng Li
    http://arxiv.org/abs/1910.08655v1

    • [eess.SY]Towards a Reinforcement Learning Environment Toolbox for Intelligent Electric Motor Control
    Arne Traue, Gerrit Book, Wilhelm Kirchgässner, Oliver Wallscheid
    http://arxiv.org/abs/1910.09434v1

    • [math.CA]Finding duality for Riesz bases of exponentials on multi-tiles
    Christina Frederick, Kasso Okoudjou
    http://arxiv.org/abs/1910.09257v1

    • [math.CO]An Improved Linear Programming Bound on the Average Distance of a Binary Code
    Lei Yu, Vincent Y. F. Tan
    http://arxiv.org/abs/1910.09416v1

    • [math.OC]A Stochastic Extra-Step Quasi-Newton Method for Nonsmooth Nonconvex Optimization
    Minghan Yang, Andre Milzarek, Zaiwen Wen, Tong Zhang
    http://arxiv.org/abs/1910.09373v1

    • [math.OC]Adaptive gradient descent without descent
    Yura Malitsky, Konstantin Mishchenko
    http://arxiv.org/abs/1910.09529v1

    • [math.OC]Exploration via Sample-Efficient Subgoal Design
    Yijia Wang, Matthias Poloczek, Daniel R. Jiang
    http://arxiv.org/abs/1910.09143v1

    • [math.OC]Policy Optimization for $\mathcal{H}2$ Linear Control with $\mathcal{H}\infty$ Robustness Guarantee: Implicit Regularization and Global Convergence
    Kaiqing Zhang, Bin Hu, Tamer Başar
    http://arxiv.org/abs/1910.09496v1

    • [math.OC]Relative Interior Rule in Block-Coordinate Minimization
    Tomáš Werner, Daniel Průša
    http://arxiv.org/abs/1910.09488v1

    • [math.OC]Robust Online Learning for Resource Allocation — Beyond Euclidean Projection and Dynamic Fit
    Ezra Tampubolon, Holger Boche
    http://arxiv.org/abs/1910.09282v1

    • [math.PR]Counterexamples for optimal scaling of Metropolis-Hastings chains with rough target densities
    Jure Vogrinc, Wilfrid Stephen Kendall
    http://arxiv.org/abs/1910.09485v1

    • [math.PR]Empirical Process of Multivariate Gaussian under General Dependency
    Jikai Hou
    http://arxiv.org/abs/1910.09319v1

    • [math.PR]Sampling random graph homomorphisms and applications to network data analysis
    Hanbaek Lyu, Facundo Memoli, David Sivakoff
    http://arxiv.org/abs/1910.09483v1

    • [math.ST]A General Framework for Empirical Bayes Estimation in Discrete Linear Exponential Family
    Trambak Banerjee, Qiang Liu, Gourab Mukherjee, Wenguang Sun
    http://arxiv.org/abs/1910.08997v1

    • [math.ST]Convex Reconstruction of Structured Matrix Signals from Random Linear Measurements (I): Theoretical Results
    Yuan Tian
    http://arxiv.org/abs/1910.08771v1

    • [math.ST]High-dimensional robust approximated M-estimators for mean regression with asymmetric data
    Bin Luo, Xiaoli Gao
    http://arxiv.org/abs/1910.09493v1

    • [math.ST]On the power of axial tests of uniformity on spheres
    Christine Cutting, Davy Paindaveine, Thomas Verdebout
    http://arxiv.org/abs/1910.09391v1

    • [math.ST]Online Community Detection by Spectral CUSUM
    Minghe Zhang, Liyan Xie, Yao Xie
    http://arxiv.org/abs/1910.09083v1

    • [math.ST]Ordering-Based Causal Structure Learning in the Presence of Latent Variables
    Daniel Irving Bernstein, Basil Saeed, Chandler Squires, Caroline Uhler
    http://arxiv.org/abs/1910.09014v1

    • [math.ST]Quickest Detection of Growing Dynamic Anomalies in Networks
    Georgios Rovatsos, Venugopal V. Veeravalli, Don Towsley, Ananthram Swami
    http://arxiv.org/abs/1910.09151v1

    • [math.ST]Robustifying multiple-set linear canonical analysis with S-estimator
    Ulrich Djemby Bivigou, Guy Martial Nkiet
    http://arxiv.org/abs/1910.08690v1

    • [math.ST]Safe-Bayesian Generalized Linear Regression
    Rianne de Heide, Alisa Kirichenko, Nishant Mehta, Peter Grünwald
    http://arxiv.org/abs/1910.09227v1

    • [math.ST]Statistical tests for the Pseudo-Lindley distribution and applications
    Gane Samb Lo, Tchilabalo Abozou Kpanzou, Cheikh Mohamed Haidara
    http://arxiv.org/abs/1910.09211v1

    • [math.ST]The Generalized-Alpha-Beta-Skew-Normal Distribution: Properties and Applications
    Sricharan Shah, Subrata Chakraborty, Partha Jyoti Hazarika, M. Masoom Ali
    http://arxiv.org/abs/1910.09192v1

    • [physics.comp-ph]Extracting local switching fields in permanent magnets using machine learning
    Markus Gusenbauer, Harald Oezelt, Johann Fischbacher, Alexander Kovacs, Panpan Zhao, Thomas George Woodcock, Thomas Schrefl
    http://arxiv.org/abs/1910.09279v1

    • [physics.med-ph]Detecting muscle activation using ultrasound speed of sound inversion with deep learning
    Micha Feigin, Daniel Freedman, Manuel Zwecker, Brian W. Anthony
    http://arxiv.org/abs/1910.09046v1

    • [q-bio.GN]SneakySnake: A Fast and Accurate Universal Genome Pre-Alignment Filter for CPUs, GPUs, and FPGAs
    Mohammed Alser, Taha Shahroodi, Juan Gomez-Luna, Can Alkan, Onur Mutlu
    http://arxiv.org/abs/1910.09020v1

    • [q-bio.QM]Biologic and Prognostic Feature scores from Whole-Slide Histology Images Using Deep Learning
    Okyaz Eminaga, Mahmood Abbas, Yuri Tolkach, Rosalie Nolley, Christian Kunder, Axel Semjonow, Martin Boegemann, Andreas Loening, James Brook, Daniel Rubin
    http://arxiv.org/abs/1910.09100v1

    • [q-fin.ST]CorrGAN: Sampling Realistic Financial Correlation Matrices Using Generative Adversarial Networks
    Gautier Marti
    http://arxiv.org/abs/1910.09504v1

    • [q-fin.ST]Entropic Dynamic Time Warping Kernels for Co-evolving Financial Time Series Analysis
    Lu Bai, Lixin Cui, Lixiang Xu, Yue Wang, Zhihong Zhang, Edwin R. Hancock
    http://arxiv.org/abs/1910.09153v1

    • [quant-ph]Deep Reinforcement Learning Control of Quantum Cartpoles
    Zhikang T. Wang, Yuto Ashida, Masahito Ueda
    http://arxiv.org/abs/1910.09200v1

    • [quant-ph]On Optimality of CSS Codes for Transversal $T$
    Narayanan Rengaswamy, Robert Calderbank, Michael Newman, Henry D. Pfister
    http://arxiv.org/abs/1910.09333v1

    • [stat.AP]A Nonparametric Bayesian Design for Drug Combination Cancer Trials
    Zahra S. Razaee, Galen Wien-Cook, Mourad Tighiouart
    http://arxiv.org/abs/1910.09163v1

    • [stat.AP]Application of a new information priority accumulated grey model with time power to predict short-term wind turbine capacity
    Jie Xia, Xin Ma, Wenqing Wu, Baolian Huang, Wanpeng Li
    http://arxiv.org/abs/1910.08699v1

    • [stat.AP]Returning Scientists and the Emergence of Chinese Science System
    Cong Cao, Jeroen Baas, Caroline S. Wagner, Koen Jonkers
    http://arxiv.org/abs/1910.09461v1

    • [stat.AP]Sequential Spatial Point Process Models for Spatio-Temporal Point Processes: A Self-Interactive Model with Application to Forest Tree Data
    Adil Yazigi, Antti Penttinen, Anna-Kaisa Ylitalo, Matti Maltamo, Petteri Packalen, Lauri Mehtätalo
    http://arxiv.org/abs/1910.08936v1

    • [stat.AP]Supporting Multi-point Fan Design with Dimension Reduction
    Pranay Seshadri, Shaowu Yuchi, Shahrokh Shahpar, Geoffrey Parks
    http://arxiv.org/abs/1910.09030v1

    • [stat.CO]Particle filter with rejection control and unbiased estimator of the marginal likelihood
    Jan Kudlicka, Lawrence M. Murray, Thomas B. Schön, Fredrik Lindsten
    http://arxiv.org/abs/1910.09527v1

    • [stat.ME]An Apparent Paradox: A Classifier Trained from a Partially Classified Sample May Have Smaller Expected Error Rate Than That If the Sample Were Completely Classified
    Daniel Ahfock, Geoffrey J. McLachlan
    http://arxiv.org/abs/1910.09189v1

    • [stat.ME]Bayesian Symbolic Regression
    Ying Jin, Weilin Fu, Jian Kang, Jiadong Guo, Jian Guo
    http://arxiv.org/abs/1910.08892v1

    • [stat.ME]Clustering by Optimizing the Average Silhouette Width
    Fatima Batool, Christian Hennig
    http://arxiv.org/abs/1910.08644v1

    • [stat.ME]Efficient Emulation of Computer Models Utilising Multiple Known Boundaries of Differing Dimensions
    Samuel E. Jackson, Ian Vernon
    http://arxiv.org/abs/1910.08846v1

    • [stat.ME]Equivalence tests for binary efficacy-toxicity responses
    Holger Dette, Kathrin Möllenhoff, Frank Bretz
    http://arxiv.org/abs/1910.08769v1

    • [stat.ME]Generalized tensor regression with covariates on multiple modes
    Zhuoyan Xu, Jiaxin Hu, Miaoyan Wang
    http://arxiv.org/abs/1910.09499v1

    • [stat.ME]Latent Variable Model for Multivariate Data with Measure-specific Sample Weights and Its Application in Hospital Compare
    Chengan Du, Shu-Xia Li, Zhenqiu Lin, Haiqun Lin
    http://arxiv.org/abs/1910.08664v1

    • [stat.ME]Marginally Interpretable Linear Transformation Models for Clustered Observations
    Torsten Hothorn
    http://arxiv.org/abs/1910.09219v1

    • [stat.ME]Measuring Causality: The Science of Cause and Effect
    Aditi Kathpalia, Nithin Nagaraj
    http://arxiv.org/abs/1910.08750v1

    • [stat.ME]Noncrossing structured additive multiple-output Bayesian quantile regression models
    Bruno Santos, Thomas Kneib
    http://arxiv.org/abs/1910.08599v1

    • [stat.ME]Note on the Delta Method for Finite Population Inference with Applications to Causal Inference
    Nicole E. Pashley
    http://arxiv.org/abs/1910.09062v1

    • [stat.ME]Permutation-Based Causal Structure Learning with Unknown Intervention Targets
    Chandler Squires, Yuhao Wang, Caroline Uhler
    http://arxiv.org/abs/1910.09007v1

    • [stat.ME]Targeted Estimation of Heterogeneous Treatment Effect in Observational Survival Analysis
    Jie Zhu, Blanca Gallego
    http://arxiv.org/abs/1910.08877v1

    • [stat.ML]$hv$-Block Cross Validation is not a BIBD: a Note on the Paper by Jeff Racine (2000)
    Wenjie Zheng
    http://arxiv.org/abs/1910.08904v1

    • [stat.ML]Adversarial Anomaly Detection for Marked Spatio-Temporal Streaming Data
    Shixiang Zhu, Henry Shaowu Yuchi, Yao Xie
    http://arxiv.org/abs/1910.09161v1

    • [stat.ML]Bayesian Optimization Allowing for Common Random Numbers
    Michael Pearce, Matthias Poloczek, Juergen Branke
    http://arxiv.org/abs/1910.09259v1

    • [stat.ML]Communication Efficient Decentralized Training with Multiple Local Updates
    Xiang Li, Wenhao Yang, Shusen Wang, Zhihua Zhang
    http://arxiv.org/abs/1910.09126v1

    • [stat.ML]Generalised learning of time-series: Ornstein-Uhlenbeck processes
    Mehmet Süzen, Alper Yegenoglu
    http://arxiv.org/abs/1910.09394v1

    • [stat.ML]Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment Problem
    Etor Arza, Aritz Perez, Ekhine Irurozki, Josu Ceberio
    http://arxiv.org/abs/1910.08800v1

    • [stat.ML]Measurement Dependence Inducing Latent Causal Models
    Alex Markham, Moritz Grosse-Wentrup
    http://arxiv.org/abs/1910.08778v1

    • [stat.ML]Multi-Resolution Weak Supervision for Sequential Data
    Frederic Sala, Paroma Varma, Jason Fries, Daniel Y. Fu, Shiori Sagawa, Saelig Khattar, Ashwini Ramamoorthy, Ke Xiao, Kayvon Fatahalian, James Priest, Christopher Ré
    http://arxiv.org/abs/1910.09505v1

    • [stat.ML]Online Ranking with Concept Drifts in Streaming Data
    Ekhine Irurozki, Jesus Lobo, Aritz Perez, Javier Del Ser
    http://arxiv.org/abs/1910.08795v1

    • [stat.ML]Robust Learning Rate Selection for Stochastic Optimization via Splitting Diagnostic
    Matteo Sordello, Weijie Su
    http://arxiv.org/abs/1910.08597v1

    • [stat.ML]Sparse (group) learning with Lipschitz loss functions: a unified analysis
    Antoine Dedieu
    http://arxiv.org/abs/1910.08880v1

    • [stat.ML]The Exact Equivalence of Independence Testing and Two-Sample Testing
    Cencheng Shen, Carey E. Priebe, Joshua T. Vogelstein
    http://arxiv.org/abs/1910.08883v1

    • [stat.ML]Towards better healthcare: What could and should be automated?
    Wolfgang Frühwirt, Paul Duckworth
    http://arxiv.org/abs/1910.09444v1

    • [stat.ML]Variational Integrator Networks for Physically Meaningful Embeddings
    Steindor Saemundsson, Alexander Terenin, Katja Hofmann, Marc Peter Deisenroth
    http://arxiv.org/abs/1910.09349v1