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