cs.AI - 人工智能

    cs.AR - 硬件体系结构 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DM - 离散数学 cs.DS - 数据结构与算法 cs.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.MM - 多媒体 cs.MS - 数学软件 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.PF - 计算性能 cs.PL - 编程语言 cs.RO - 机器人学 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.OC - 优化与控制 math.ST - 统计理论 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

    • [cs.AI]Beyond the Grounding Bottleneck: Datalog Techniques for Inference in Probabilistic Logic Programs (Technical Report)
    • [cs.AI]Improving Graph Neural Network Representations of Logical Formulae with Subgraph Pooling
    • [cs.AI]Inducing Cooperation via Team Regret Minimization based Multi-Agent Deep Reinforcement Learning
    • [cs.AI]Learning Efficient Multi-agent Communication: An Information Bottleneck Approach
    • [cs.AI]Learning Query Inseparable ELH Ontologies
    • [cs.AI]Leveraging Decentralized Artificial Intelligence to Enhance Resilience of Energy Networks
    • [cs.AI]Opportunities for artificial intelligence in advancing precision medicine
    • [cs.AI]Pattern-based design applied to cultural heritage knowledge graphs
    • [cs.AI]Sensory Optimization: Neural Networks as a Model for Understanding and Creating Art
    • [cs.AI]Taming Reasoning in Temporal Probabilistic Relational Models
    • [cs.AI]Towards Efficient Anytime Computation and Execution of Decoupled Robustness Envelopes for Temporal Plans
    • [cs.AR]NeuMMU: Architectural Support for Efficient Address Translations in Neural Processing Units
    • [cs.CL]An Annotated Corpus of Reference Resolution for Interpreting Common Grounding
    • [cs.CL]Assigning Medical Codes at the Encounter Level by Paying Attention to Documents
    • [cs.CL]AttaCut: A Fast and Accurate Neural Thai Word Segmenter
    • [cs.CL]CNN-based Dual-Chain Models for Knowledge Graph Learning
    • [cs.CL]Contribution au Niveau de l’Approche Indirecte à Base de Transfert dans la Traduction Automatique
    • [cs.CL]Deep Learning versus Traditional Classifiers on Vietnamese Students’ Feedback Corpus
    • [cs.CL]Dense and Deep Sarcasm Detection
    • [cs.CL]Drug Repurposing for Cancer: An NLP Approach to Identify Low-Cost Therapies
    • [cs.CL]Error Analysis for Vietnamese Named Entity Recognition on Deep Neural Network Models
    • [cs.CL]Evaluating robustness of language models for chief complaint extraction from patient-generated text
    • [cs.CL]Experiments in Detecting Persuasion Techniques in the News
    • [cs.CL]Fine-Grained Static Detection of Obfuscation Transforms Using Ensemble-Learning and Semantic Reasoning
    • [cs.CL]Graph Transformer for Graph-to-Sequence Learning
    • [cs.CL]Improved Document Modelling with a Neural Discourse Parser
    • [cs.CL]Learning Autocomplete Systems as a Communication Game
    • [cs.CL]Multi-Zone Unit for Recurrent Neural Networks
    • [cs.CL]Multi-task Sentence Encoding Model for Semantic Retrieval in Question Answering Systems
    • [cs.CL]Overcoming Practical Issues of Deep Active Learning and its Applications on Named Entity Recognition
    • [cs.CL]Quick and (not so) Dirty: Unsupervised Selection of Justification Sentences for Multi-hop Question Answering
    • [cs.CL]Robust Reading Comprehension with Linguistic Constraints via Posterior Regularization
    • [cs.CL]Short Text Language Identification for Under Resourced Languages
    • [cs.CL]Utterance-to-Utterance Interactive Matching Network for Multi-Turn Response Selection in Retrieval-Based Chatbots
    • [cs.CR]Hacking Neural Networks: A Short Introduction
    • [cs.CV]2nd Place Solution in Google AI Open Images Object Detection Track 2019
    • [cs.CV]AETv2: AutoEncoding Transformations for Self-Supervised Representation Learning by Minimizing Geodesic Distances in Lie Groups
    • [cs.CV]AI-based Pilgrim Detection using Convolutional Neural Networks
    • [cs.CV]AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results
    • [cs.CV]Action Anticipation with RBF KernelizedFeature Mapping RNN
    • [cs.CV]Affine Self Convolution
    • [cs.CV]Aging Deep Face Features: Finding Missing Children
    • [cs.CV]All-In-One: Facial Expression Transfer, Editing and Recognition Using A Single Network
    • [cs.CV]Automatic Annotation of Hip Anatomy in Fluoroscopy for Robust and Efficient 2D/3D Registration
    • [cs.CV]Automatic Image Co-Segmentation: A Survey
    • [cs.CV]BSP-Net: Generating Compact Meshes via Binary Space Partitioning
    • [cs.CV]Bias-Aware Heapified Policy for Active Learning
    • [cs.CV]Capturing Hand Articulations using Recurrent Neural Network for 3D Hand Pose Estimation
    • [cs.CV]Constructing Multiple Tasks for Augmentation: Improving Neural Image Classification With K-means Features
    • [cs.CV]Counterfactual Vision-and-Language Navigation via Adversarial Path Sampling
    • [cs.CV]Countering Inconsistent Labelling by Google’s Vision API for Rotated Images
    • [cs.CV]Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models
    • [cs.CV]DeepPFCN: Deep Parallel Feature Consensus Network For Person Re-Identification
    • [cs.CV]Defensive Few-shot Adversarial Learning
    • [cs.CV]Dense Color Constancy with Effective Edge Augmentation
    • [cs.CV]Detecting F-formations & Roles in Crowded Social Scenes with Wearables: Combining Proxemics & Dynamics using LSTMs
    • [cs.CV]DirectPose: Direct End-to-End Multi-Person Pose Estimation
    • [cs.CV]Distributed Low Precision Training Without Mixed Precision
    • [cs.CV]Distribution Context Aware Loss for Person Re-identification
    • [cs.CV]Domain Generalization Using a Mixture of Multiple Latent Domains
    • [cs.CV]DualVD: An Adaptive Dual Encoding Model for Deep Visual Understanding in Visual Dialogue
    • [cs.CV]Dynamic Instance Normalization for Arbitrary Style Transfer
    • [cs.CV]ELoPE: Fine-Grained Visual Classification with Efficient Localization, Pooling and Embedding
    • [cs.CV]Effectively Unbiased FID and Inception Score and where to find them
    • [cs.CV]Extra Proximal-Gradient Inspired Non-local Network
    • [cs.CV]FFA-Net: Feature Fusion Attention Network for Single Image Dehazing
    • [cs.CV]Fast 3D Pose Refinement with RGB Images
    • [cs.CV]Fast Color Constancy with Patch-wise Bright Pixels
    • [cs.CV]Faster AutoAugment: Learning Augmentation Strategies using Backpropagation
    • [cs.CV]Fine-Grained Neural Architecture Search
    • [cs.CV]GLMNet: Graph Learning-Matching Networks for Feature Matching
    • [cs.CV]Grounding Human-to-Vehicle Advice for Self-driving Vehicles
    • [cs.CV]Instance Shadow Detection
    • [cs.CV]Ladder Loss for Coherent Visual-Semantic Embedding
    • [cs.CV]Large Scale Open-Set Deep Logo Detection
    • [cs.CV]Learning Similarity Attention
    • [cs.CV]Learning to Predict More Accurate Text Instances for Scene Text Detection
    • [cs.CV]Learning to Synthesize Fashion Textures
    • [cs.CV]Learning with Hierarchical Complement Objective
    • [cs.CV]Leveraging Multi-view Image Sets for Unsupervised Intrinsic Image Decomposition and Highlight Separation
    • [cs.CV]Long Range 3D with Quadocular Thermal (LWIR) Camera
    • [cs.CV]Maintaining Discrimination and Fairness in Class Incremental Learning
    • [cs.CV]MaskedFusion: Mask-based 6D Object Pose Detection
    • [cs.CV]Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual Recognition
    • [cs.CV]Modeling Gestalt Visual Reasoning on the Raven’s Progressive Matrices Intelligence Test Using Generative Image Inpainting Techniques
    • [cs.CV]Multi-Task Learning of Height and Semantics from Aerial Images
    • [cs.CV]Multiple Style-Transfer in Real-Time
    • [cs.CV]On the well-posedness of uncalibrated photometric stereo under general lighting
    • [cs.CV]Optimized CNN for PolSAR Image Classification via Differentiable Neural Architecture Search
    • [cs.CV]Oriented Boxes for Accurate Instance Segmentation
    • [cs.CV]Potential Field: Interpretable and Unified Representation for Trajectory Prediction
    • [cs.CV]Preparing Lessons: Improve Knowledge Distillation with Better Supervision
    • [cs.CV]Putting visual object recognition in context
    • [cs.CV]Real-Time Semantic Segmentation via Multiply Spatial Fusion Network
    • [cs.CV]Revisiting Shadow Detection: A New Benchmark Dataset for Complex World
    • [cs.CV]S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search
    • [cs.CV]SA-Text: Simple but Accurate Detector for Text of Arbitrary Shapes
    • [cs.CV]SMART: Skeletal Motion Action Recognition aTtack
    • [cs.CV]SOGNet: Scene Overlap Graph Network for Panoptic Segmentation
    • [cs.CV]Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention
    • [cs.CV]Self-supervised GAN: Analysis and Improvement with Multi-class Minimax Game
    • [cs.CV]SiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Tracking
    • [cs.CV]Signal Clustering with Class-independent Segmentation
    • [cs.CV]Signed Input Regularization
    • [cs.CV]TSRNet: Scalable 3D Surface Reconstruction Network for Point Clouds using Tangent Convolution
    • [cs.CV]The Devil is in the Details: Delving into Unbiased Data Processing for Human Pose Estimation
    • [cs.CV]The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersections
    • [cs.CV]Towards Robust RGB-D Human Mesh Recovery
    • [cs.CV]Towards Visually Explaining Variational Autoencoders
    • [cs.CV]Towards the Automation of Deep Image Prior
    • [cs.CV]Transductive Zero-Shot Hashing for Multi-Label Image Retrieval
    • [cs.CV]Unsupervised Deep Metric Learning via Auxiliary Rotation Loss
    • [cs.CV]Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning
    • [cs.CV]Unsupervised Reinforcement Learning of Transferable Meta-Skills for Embodied Navigation
    • [cs.CV]Unsupervised Representation Learning by Discovering Reliable Image Relations
    • [cs.CV]Unsupervised Representation Learning for Gaze Estimation
    • [cs.CV]Unsupervised Visual Representation Learning with Increasing Object Shape Bias
    • [cs.CV]Weakly Supervised Object Localization with Inter-Intra Regulated CAMs
    • [cs.CY]Adaptive Learning Guidance System (ALGS)
    • [cs.DB]IDEALEM: Statistical Similarity Based Data Reduction
    • [cs.DB]Using Mapping Languages for Building Legal Knowledge Graphs from XML Files
    • [cs.DC]A Code injection Method for Rapid Docker Image Building
    • [cs.DC]Distributed Machine Learning through Heterogeneous Edge Systems
    • [cs.DC]Pangolin: An Efficient and Flexible Graph Mining System on CPU and GPU
    • [cs.DC]Towards Design Methodology of Efficient Fast Algorithms for Accelerating Generative Adversarial Networks on FPGAs
    • [cs.DM]Optimal adaptive group testing
    • [cs.DS]Random Restrictions of High-Dimensional Distributions and Uniformity Testing with Subcube Conditioning
    • [cs.DS]Sparse Hopsets in Congested Clique
    • [cs.DS]Testing Properties of Multiple Distributions with Few Samples
    • [cs.GT]Learning Probably Approximately Correct Maximin Strategies in Simulation-Based Games with Infinite Strategy Spaces
    • [cs.HC]A Sketch-Based System for Human-Guided Constrained Object Manipulation
    • [cs.HC]Developing a Scenario-Based Video Game Generation Framework: Preliminary Results
    • [cs.IR]A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research
    • [cs.IR]Common Artist Music Assistance
    • [cs.IR]Pairwise Interactive Graph Attention Network for Context-Aware Recommendation
    • [cs.IR]Quels corpus d’entraînement pour l’expansion de requêtes par plongement de mots : application à la recherche de microblogs culturels
    • [cs.IR]Rumor Detection on Social Media: Datasets, Methods and Opportunities
    • [cs.IT]Channel Estimation in Massive MIMO under Hardware Non-Linearities: Bayesian Methods versus Deep Learning
    • [cs.IT]Degrees of Freedom of Holographic MIMO Channels
    • [cs.IT]Demand-Private Coded Caching and the Exact Trade-off for N=K=2
    • [cs.IT]Deterministic partial binary circulant compressed sensing matrices
    • [cs.IT]Finding the Exact Distribution of (Peak) Age of Information for Queues of PH/PH/1/1 and M/PH/1/2 Type
    • [cs.IT]Identify Equivalent Frames
    • [cs.IT]Learning The MMSE Channel Predictor
    • [cs.IT]Locally recoverable $J$-affine variety codes
    • [cs.IT]Multiple-Source Ellipsoidal Localization Using Acoustic Energy Measurements
    • [cs.IT]On one-stage recovery for $ΣΔ$-quantized compressed sensing
    • [cs.IT]On q-ary Bent and Plateaued Functions
    • [cs.IT]On the Age of Information in Multi-Source Queueing Models
    • [cs.IT]On the Hamming distances of repeated-root cyclic codes of length $5p^s$
    • [cs.IT]Optimal deployments of UAVs with directional antennas for a power-efficient coverage
    • [cs.IT]Predicting Device-to-Device Channels from Cellular Channel Measurements: A Learning Approach
    • [cs.IT]Projection decoding of some binary optimal linear codes of lengths 36 and 40
    • [cs.IT]Quantized Compressed Sensing by Rectified Linear Units
    • [cs.IT]RIP constants for deterministic compressed sensing matrices-beyond Gershgorin
    • [cs.IT]Secure Communication for Spatially Sparse Millimeter-Wave Massive MIMO Channels via Hybrid Precoding
    • [cs.IT]Sparse Bayesian Multi-Task Learning of Time-Varying Massive MIMO Channels with Dynamic Filtering
    • [cs.IT]Study of Non-Uniform Channel Polarization and Design of Polar Codes with Arbitrary Rates
    • [cs.IT]The Parameters of Minimal Linear Codes
    • [cs.IT]Throughput Maximization with an Average Age of Information Constraint in Fading Channels
    • [cs.IT]Two-weight codes over the integers modulo a prime power
    • [cs.LG]$DC^2$: A Divide-and-conquer Algorithm for Large-scale Kernel Learning with Application to Clustering
    • [cs.LG]A Graph Autoencoder Approach to Causal Structure Learning
    • [cs.LG]A Multi-Task Gradient Descent Method for Multi-Label Learning
    • [cs.LG]A New Ensemble Adversarial Attack Powered by Long-term Gradient Memories
    • [cs.LG]An “outside the box” solution for imbalanced data classification
    • [cs.LG]An Empirical and Comparative Analysis of Data Valuation with Scalable Algorithms
    • [cs.LG]An explanation method for Siamese neural networks
    • [cs.LG]Any-Precision Deep Neural Networks
    • [cs.LG]Bayesian Recurrent Framework for Missing Data Imputation and Prediction with Clinical Time Series
    • [cs.LG]Benanza: Automatic uBenchmark Generation to Compute “Lower-bound” Latency and Inform Optimizations of Deep Learning Models on GPUs
    • [cs.LG]Binary Sine Cosine Algorithms for Feature Selection from Medical Data
    • [cs.LG]Black-Box Adversarial Attack with Transferable Model-based Embedding
    • [cs.LG]Causality-based Feature Selection: Methods and Evaluations
    • [cs.LG]Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis
    • [cs.LG]Convex Formulation of Overparameterized Deep Neural Networks
    • [cs.LG]Coverage Testing of Deep Learning Models using Dataset Characterization
    • [cs.LG]Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learning
    • [cs.LG]Deep geometric matrix completion: Are we doing it right?
    • [cs.LG]Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning
    • [cs.LG]Encouraging an Appropriate Representation Simplifies Training of Neural Networks
    • [cs.LG]Explanatory Masks for Neural Network Interpretability
    • [cs.LG]Fast Machine Learning with Byzantine Workers and Servers
    • [cs.LG]Feedback Control for Online Training of Neural Networks
    • [cs.LG]Gamma-Nets: Generalizing Value Estimation over Timescale
    • [cs.LG]Glyph: Fast and Accurately Training Deep Neural Networks on Encrypted Data
    • [cs.LG]GraLSP: Graph Neural Networks with Local Structural Patterns
    • [cs.LG]Graph Neural Ordinary Differential Equations
    • [cs.LG]Graph-Revised Convolutional Network
    • [cs.LG]Grassmannian Packings in Neural Networks: Learning with Maximal Subspace Packings for Diversity and Anti-Sparsity
    • [cs.LG]Hebbian Synaptic Modifications in Spiking Neurons that Learn
    • [cs.LG]Improved Exploration through Latent Trajectory Optimization in Deep Deterministic Policy Gradient
    • [cs.LG]Inductive Relation Prediction on Knowledge Graphs
    • [cs.LG]Influence-aware Memory for Deep Reinforcement Learning
    • [cs.LG]Information-Theoretic Perspective of Federated Learning
    • [cs.LG]Inverse Reinforcement Learning with Missing Data
    • [cs.LG]Justification-Based Reliability in Machine Learning
    • [cs.LG]Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks
    • [cs.LG]Learning Behavioral Representations from Wearable Sensors
    • [cs.LG]Loss Aware Post-training Quantization
    • [cs.LG]Missingness as Stability: Understanding the Structure of Missingness in Longitudinal EHR data and its Impact on Reinforcement Learning in Healthcare
    • [cs.LG]NAIS: Neural Architecture and Implementation Search and its Applications in Autonomous Driving
    • [cs.LG]Neural Recurrent Structure Search for Knowledge Graph Embedding
    • [cs.LG]Off-Policy Policy Gradient Algorithms by Constraining the State Distribution Shift
    • [cs.LG]On Value Discrepancy of Imitation Learning
    • [cs.LG]Online Adaptive Asymmetric Active Learning with Limited Budgets
    • [cs.LG]Program synthesis performance constrained by non-linear spatial relations in Synthetic Visual Reasoning Test
    • [cs.LG]Prototypical Networks for Multi-Label Learning
    • [cs.LG]Provable Filter Pruning for Efficient Neural Networks
    • [cs.LG]Query Complexity of Bayesian Private Learning
    • [cs.LG]RSM-GAN: A Convolutional Recurrent GAN for Anomaly Detection in Contaminated Seasonal Multivariate Time Series
    • [cs.LG]Rebalancing Learning on Evolving Data Streams
    • [cs.LG]Reinforcement Learning from Imperfect Demonstrations under Soft Expert Guidance
    • [cs.LG]Robust Anomaly Detection and Backdoor Attack Detection Via Differential Privacy
    • [cs.LG]RotationOut as a Regularization Method for Neural Network
    • [cs.LG]Safe squeezing for antisparse coding
    • [cs.LG]Selective sampling for accelerating training of deep neural networks
    • [cs.LG]Smoothed Inference for Adversarially-Trained Models
    • [cs.LG]Sparse $\ell_1$ and $\ell_2$ Center Classifiers
    • [cs.LG]Suspicion-Free Adversarial Attacks on Clustering Algorithms
    • [cs.LG]SySCD: A System-Aware Parallel Coordinate Descent Algorithm
    • [cs.LG]The Effectiveness of Variational Autoencoders for Active Learning
    • [cs.LG]The Proper Care and Feeding of CAMELS: How Limited Training Data Affects Streamflow Prediction
    • [cs.LG]The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks
    • [cs.LG]Towards Making Deep Transfer Learning Never Hurt
    • [cs.LG]Towards Quantification of Bias in Machine Learning for Healthcare: A Case Study of Renal Failure Prediction
    • [cs.LG]Understanding and Improving Layer Normalization
    • [cs.LG]VLUC: An Empirical Benchmark for Video-Like Urban Computing on Citywide Crowd and Traffic Prediction
    • [cs.LG]Vulnerability Analysis for Data Driven Pricing Schemes
    • [cs.LG]Walking the Tightrope: An Investigation of the Convolutional Autoencoder Bottleneck
    • [cs.LG]What Will Your Child Look Like? DNA-Net: Age and Gender Aware Kin Face Synthesizer
    • [cs.LG]Working Memory Graphs
    • [cs.MM]Parametric Graph-based Separable Transforms for Video Coding
    • [cs.MM]Understanding the Teaching Styles by an Attention based Multi-task Cross-media Dimensional modelling
    • [cs.MS]Semi-Automatic Task Graph Construction for $\mathcal{H}$-Matrix Arithmetic
    • [cs.NE]ImmuNeCS: Neural Committee Search by an Artificial Immune System
    • [cs.NE]Particle Swarm and EDAs
    • [cs.NI]Caching Techniques to Improve Latency in Serverless Architectures
    • [cs.NI]Profile-based Resource Allocation for Virtualized Network Functions
    • [cs.NI]The geopolitics behind the routes data travels: a case study of Iran
    • [cs.PF]Understanding Open Source Serverless Platforms: Design Considerations and Performance
    • [cs.PL]PriorityGraph: A Unified Programming Model for Optimizing Ordered Graph Algorithms
    • [cs.RO]A Hierarchical Framework to Generate Robust Biped Locomotion Based on Divergent Component of Motion
    • [cs.RO]A gamified simulator and physical platform for self-driving algorithm training and validation
    • [cs.RO]Adaptive Leader-Follower Formation Control and Obstacle Avoidance via Deep Reinforcement Learning
    • [cs.RO]Design of the First Insect-scale Spinning-wing Robot
    • [cs.RO]Development of MirrorShape: High Fidelity Large-Scale Shape Rendering Framework for Virtual Reality
    • [cs.RO]Fast 2D Map Matching Based on Area Graphs
    • [cs.RO]Flexoskeleton printing for versatile insect-inspired robots
    • [cs.RO]Ground and Non-Ground Separation Filter for UAV Lidar Point Cloud
    • [cs.RO]IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks
    • [cs.RO]Object Finding in Cluttered Scenes Using Interactive Perception
    • [cs.RO]Optimal Control of a Differentially Flat 2D Spring-Loaded Inverted Pendulum Model
    • [cs.RO]Robotic Sculpting with Collision-free Motion Planning in Voxel Space
    • [cs.RO]Strategy Synthesis for Surveillance-Evasion Games with Learning-Enabled Visibility Optimization
    • [cs.SE]patch2vec: Distributed Representation of Code Changes
    • [cs.SI]A First Look at References from the Dark to Surface Web World
    • [cs.SI]An Application of Random Walk on Fake Account Detection Problem: A Hybrid Approach
    • [cs.SI]An Induced Multi-Relational Framework for Answer Selection in Community Question Answer Platforms
    • [cs.SI]Large-Scale Parallel Matching of Social Network Profiles
    • [cs.SI]Mining Unfollow Behavior in Large-Scale Online Social Networks via Spatial-Temporal Interaction
    • [cs.SI]Towards Automated Sexual Violence Report Tracking
    • [econ.EM]Causal Inference Under Approximate Neighborhood Interference
    • [econ.EM]Inference in Models of Discrete Choice with Social Interactions Using Network Data
    • [econ.EM]Semiparametric Estimation of Correlated Random Coefficient Models without Instrumental Variables
    • [eess.IV]Automated Human Claustrum Segmentation using Deep Learning Technologies
    • [eess.IV]Automated fetal brain extraction from clinical Ultrasound volumes using 3D Convolutional Neural Networks
    • [eess.IV]Kvasir-SEG: A Segmented Polyp Dataset
    • [eess.IV]Liver Steatosis Segmentation with Deep Learning Methods
    • [eess.IV]Low-Weight and Learnable Image Denoising
    • [eess.IV]Multi-Temporal Recurrent Neural Networks For Progressive Non-Uniform Single Image Deblurring With Incremental Temporal Training
    • [eess.IV]Multi-modal Deep Guided Filtering for Comprehensible Medical Image Processing
    • [eess.IV]On Space-spectrum Uncertainty Analysis for Coded Aperture Systems
    • [eess.IV]Quality Assessment of DIBR-synthesized views: An Overview
    • [eess.IV]ResUNet++: An Advanced Architecture for Medical Image Segmentation
    • [eess.IV]Skin Lesion Classification Using Deep Neural Network
    • [eess.IV]Transfer Learning of fMRI Dynamics
    • [eess.SP]A Novel Content Caching and Delivery Scheme for Millimeter Wave Device-to-Device Communications
    • [eess.SP]Deep Learning with Persistent Homology for Orbital Angular Momentum (OAM) Decoding
    • [eess.SP]Energy-Efficient MIMO Multiuser Systems: Nash Equilibrium Analysis
    • [eess.SP]FFDNet-Based Channel Estimation for Massive MIMO Visible Light Communication Systems
    • [eess.SP]Radar Emitter Classification with Attribute-specific Recurrent Neural Networks
    • [eess.SP]Scale- and Context-Aware Convolutional Non-intrusive Load Monitoring
    • [eess.SP]Subcarrier Assignment Schemes Based on Q-Learning in Wideband Cognitive Radio Networks
    • [eess.SY]Fixed-horizon Active Hypothesis Testing
    • [eess.SY]General Regression Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, and Feedforward Neural Networks
    • [eess.SY]Prescribed Performance Distance-Based Formation Control of Multi-Agent Systems (Extended Version)
    • [eess.SY]Safe Interactive Model-Based Learning
    • [eess.SY]Steady-State Control and Machine Learning of Large-Scale Deformable Mirror Models
    • [math.OC]Convergence Analysis of a Momentum Algorithm with Adaptive Step Size for Non Convex Optimization
    • [math.OC]Coordinate-wise Armijo’s condition
    • [math.OC]Inexact Primal-Dual Gradient Projection Methods for Nonlinear Optimization on Convex Set
    • [math.OC]Online Learning and Matching for Resource Allocation Problems
    • [math.ST]Detecting structural breaks in eigensystems of functional time series
    • [math.ST]Goodness-of-fit Testing in Linear Regression Models
    • [math.ST]Graph Topological Aspects of Granger Causal Network Learning
    • [math.ST]Graph estimation for Gaussian data zero-inflated by double truncation
    • [math.ST]Maximum Approximate Likelihood Estimation in Accelerated Failure Time Model for Interval-Censored Data
    • [math.ST]Oracle inequalities for image denoising with total variation regularization
    • [quant-ph]Quantifying the unextendibility of entanglement
    • [quant-ph]Universal superposition codes: capacity regions of compound quantum broadcast channel with confidential messages
    • [stat.AP]A spatio-temporal multi-scale model for Geyer saturation point process: application to forest fire occurrences
    • [stat.AP]Granular Motor State Monitoring of Free Living Parkinson’s Disease Patients via Deep Learning
    • [stat.AP]Predicting colorectal polyp recurrence using time-to-event analysis of medical records
    • [stat.AP]Spatiotemporal large-scale networks shaped by air mass movements
    • [stat.AP]The implications of Labour’s plan to scrap Key Stage 2 tests for Progress 8 and secondary school accountability in England
    • [stat.CO]Bayesian Model Selection for Ultrahigh-Dimensional Doubly-Intractable Distributions with an Application to Network Psychometrics
    • [stat.CO]DRHotNet: An R package for detecting differential risk hotspots on a linear network
    • [stat.ME]A Bootstrap-based Inference Framework for Testing Similarity of Paired Networks
    • [stat.ME]A Permutation Test for Assessing the Presence of Individual Differences in Treatment Effects
    • [stat.ME]A hierarchical expected improvement method for Bayesian optimization
    • [stat.ME]A projection approach for multiple monotone regression
    • [stat.ME]Bayesian Ordinal Quantile Regression with a Partially Collapsed Gibbs Sampler
    • [stat.ME]Causal inference with recurrent data via inverse probability treatment weighting method (IPTW)
    • [stat.ME]Change point localization in dependent dynamic nonparametric random dot product graphs
    • [stat.ME]Constrained High Dimensional Statistical Inference
    • [stat.ME]Does Regression Approximate the Influence of the Covariates or Just Measurement Errors? A Model Validity Test
    • [stat.ME]Marginal and Interactive Feature Screening of Ultra-high Dimensional Feature Spaces with Multivariate Response
    • [stat.ME]Online Change-Point Detection in High-Dimensional Covariance Structure with Application to Dynamic Networks
    • [stat.ME]Partial Least Squares for Functional Joint Models
    • [stat.ME]State Space Emulation and Annealed Sequential Monte Carlo for High Dimensional Optimization
    • [stat.ME]Testing for Stochastic Order in Interval-Valued Data
    • [stat.ME]Variance partitioning in multilevel models for count data
    • [stat.ME]Wavelet-Based Moment-Matching Techniques for Inertial Sensor Calibration
    • [stat.ML]A Simple Heuristic for Bayesian Optimization with A Low Budget
    • [stat.ML]Benchmarking time series classification — Functional data vs machine learning approaches
    • [stat.ML]Defending Against Model Stealing Attacks with Adaptive Misinformation
    • [stat.ML]Iterative Construction of Gaussian Process Surrogate Models for Bayesian Inference
    • [stat.ML]Learning with Good Feature Representations in Bandits and in RL with a Generative Model
    • [stat.ML]Stochastic Gradient Annealed Importance Sampling for Efficient Online Marginal Likelihood Estimation

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

    • [cs.AI]Beyond the Grounding Bottleneck: Datalog Techniques for Inference in Probabilistic Logic Programs (Technical Report)
    Efthymia Tsamoura, Victor Gutierrez-Basulto, Angelika Kimmig
    http://arxiv.org/abs/1911.07750v1

    • [cs.AI]Improving Graph Neural Network Representations of Logical Formulae with Subgraph Pooling
    Maxwell Crouse, Ibrahim Abdelaziz, Cristina Cornelio, Veronika Thost, Lingfei Wu, Kenneth Forbus, Achille Fokoue
    http://arxiv.org/abs/1911.06904v1

    • [cs.AI]Inducing Cooperation via Team Regret Minimization based Multi-Agent Deep Reinforcement Learning
    Runsheng Yu, Zhenyu Shi, Xinrun Wang, Rundong Wang, Buhong Liu, Xinwen Hou, Hanjiang Lai, Bo An
    http://arxiv.org/abs/1911.07712v1

    • [cs.AI]Learning Efficient Multi-agent Communication: An Information Bottleneck Approach
    Rundong Wang, Xu He, Runsheng Yu, Wei Qiu, Bo An, Zinovi Rabinovich
    http://arxiv.org/abs/1911.06992v1

    • [cs.AI]Learning Query Inseparable ELH Ontologies
    Cosimo Persia, Ana Ozaki, Andrea Mazzullo
    http://arxiv.org/abs/1911.07229v1

    • [cs.AI]Leveraging Decentralized Artificial Intelligence to Enhance Resilience of Energy Networks
    Ahmed Imteaj, M. Hadi Amini, Javad Mohammadi
    http://arxiv.org/abs/1911.07690v1

    • [cs.AI]Opportunities for artificial intelligence in advancing precision medicine
    Fabian V. Filipp
    http://arxiv.org/abs/1911.07125v1

    • [cs.AI]Pattern-based design applied to cultural heritage knowledge graphs
    Valentina Anita Carriero, Aldo Gangemi, Maria Letizia Mancinelli, Andrea Giovanni Nuzzolese, Valentina Presutti, Chiara Veninata
    http://arxiv.org/abs/1911.07585v1

    • [cs.AI]Sensory Optimization: Neural Networks as a Model for Understanding and Creating Art
    Owain Evans
    http://arxiv.org/abs/1911.07068v1

    • [cs.AI]Taming Reasoning in Temporal Probabilistic Relational Models
    Marcel Gehrke, Ralf Möller, Tanya Braun
    http://arxiv.org/abs/1911.07040v1

    • [cs.AI]Towards Efficient Anytime Computation and Execution of Decoupled Robustness Envelopes for Temporal Plans
    Michael Cashmore, Alessandro Cimatti, Daniele Magazzeni, Andrea Micheli, Parisa Zehtabi
    http://arxiv.org/abs/1911.07318v1

    • [cs.AR]NeuMMU: Architectural Support for Efficient Address Translations in Neural Processing Units
    Bongjoon Hyun, Youngeun Kwon, Yujeong Choi, John Kim, Minsoo Rhu
    http://arxiv.org/abs/1911.06859v1

    • [cs.CL]An Annotated Corpus of Reference Resolution for Interpreting Common Grounding
    Takuma Udagawa, Akiko Aizawa
    http://arxiv.org/abs/1911.07588v1

    • [cs.CL]Assigning Medical Codes at the Encounter Level by Paying Attention to Documents
    Han-Chin Shing, Guoli Wang, Philip Resnik
    http://arxiv.org/abs/1911.06848v1

    • [cs.CL]AttaCut: A Fast and Accurate Neural Thai Word Segmenter
    Pattarawat Chormai, Ponrawee Prasertsom, Attapol Rutherford
    http://arxiv.org/abs/1911.07056v1

    • [cs.CL]CNN-based Dual-Chain Models for Knowledge Graph Learning
    Bo Peng, Renqiang Min, Xia Ning
    http://arxiv.org/abs/1911.06910v1

    • [cs.CL]Contribution au Niveau de l’Approche Indirecte à Base de Transfert dans la Traduction Automatique
    Sadik Bessou
    http://arxiv.org/abs/1911.07030v1

    • [cs.CL]Deep Learning versus Traditional Classifiers on Vietnamese Students’ Feedback Corpus
    Phu X. V. Nguyen, Tham T. T. Hong, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen
    http://arxiv.org/abs/1911.07223v1

    • [cs.CL]Dense and Deep Sarcasm Detection
    Devin Pelser, Hugh Murrell
    http://arxiv.org/abs/1911.07474v1

    • [cs.CL]Drug Repurposing for Cancer: An NLP Approach to Identify Low-Cost Therapies
    Shivashankar Subramanian, Ioana Baldini, Sushma Ravichandran, Dmitriy A. Katz-Rogozhnikov, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Kush R. Varshney, Annmarie Wang, Pradeep Mangalath, Laura B. Kleiman
    http://arxiv.org/abs/1911.07819v1

    • [cs.CL]Error Analysis for Vietnamese Named Entity Recognition on Deep Neural Network Models
    Binh An Nguyen, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen
    http://arxiv.org/abs/1911.07228v1

    • [cs.CL]Evaluating robustness of language models for chief complaint extraction from patient-generated text
    Ilya Valmianski, Caleb Goodwin, Ian M. Finn, Naqi Khan, Daniel S. Zisook
    http://arxiv.org/abs/1911.06915v1

    • [cs.CL]Experiments in Detecting Persuasion Techniques in the News
    Seunghak Yu, Giovanni Da San Martino, Preslav Nakov
    http://arxiv.org/abs/1911.06815v1

    • [cs.CL]Fine-Grained Static Detection of Obfuscation Transforms Using Ensemble-Learning and Semantic Reasoning
    Ramtine Tofighi-Shirazi, Irina Mariuca Asavoae, Philippe Elbaz-Vincent
    http://arxiv.org/abs/1911.07523v1

    • [cs.CL]Graph Transformer for Graph-to-Sequence Learning
    Deng Cai, Wai Lam
    http://arxiv.org/abs/1911.07470v1

    • [cs.CL]Improved Document Modelling with a Neural Discourse Parser
    Fajri Koto, Jey Han Lau, Timothy Baldwin
    http://arxiv.org/abs/1911.06919v1

    • [cs.CL]Learning Autocomplete Systems as a Communication Game
    Mina Lee, Tatsunori B. Hashimoto, Percy Liang
    http://arxiv.org/abs/1911.06964v1

    • [cs.CL]Multi-Zone Unit for Recurrent Neural Networks
    Fandong Meng, Jinchao Zhang, Yang Liu, Jie Zhou
    http://arxiv.org/abs/1911.07184v1

    • [cs.CL]Multi-task Sentence Encoding Model for Semantic Retrieval in Question Answering Systems
    Qiang Huang, Jianhui Bu, Weijian Xie, Shengwen Yang, Weijia Wu, Liping Liu
    http://arxiv.org/abs/1911.07405v1

    • [cs.CL]Overcoming Practical Issues of Deep Active Learning and its Applications on Named Entity Recognition
    Haw-Shiuan Chang, Shankar Vembu, Sunil Mohan, Rheeya Uppaal, Andrew McCallum
    http://arxiv.org/abs/1911.07335v1

    • [cs.CL]Quick and (not so) Dirty: Unsupervised Selection of Justification Sentences for Multi-hop Question Answering
    Vikas Yadav, Steven Bethard, Mihai Surdeanu
    http://arxiv.org/abs/1911.07176v1

    • [cs.CL]Robust Reading Comprehension with Linguistic Constraints via Posterior Regularization
    Mantong Zhou, Minlie Huang, Xiaoyan Zhu
    http://arxiv.org/abs/1911.06948v1

    • [cs.CL]Short Text Language Identification for Under Resourced Languages
    Bernardt Duvenhage
    http://arxiv.org/abs/1911.07555v1

    • [cs.CL]Utterance-to-Utterance Interactive Matching Network for Multi-Turn Response Selection in Retrieval-Based Chatbots
    Jia-Chen Gu, Zhen-Hua Ling, Quan Liu
    http://arxiv.org/abs/1911.06940v1

    • [cs.CR]Hacking Neural Networks: A Short Introduction
    Michael Kissner
    http://arxiv.org/abs/1911.07658v1

    • [cs.CV]2nd Place Solution in Google AI Open Images Object Detection Track 2019
    Ruoyu Guo, Cheng Cui, Yuning Du, Xianglong Meng, Xiaodi Wang, Jingwei Liu, Jianfeng Zhu, Yuan Feng, Shumin Han
    http://arxiv.org/abs/1911.07171v1

    • [cs.CV]AETv2: AutoEncoding Transformations for Self-Supervised Representation Learning by Minimizing Geodesic Distances in Lie Groups
    Feng Lin, Haohang Xu, Houqiang Li, Hongkai Xiong, Guo-Jun Qi
    http://arxiv.org/abs/1911.07004v1

    • [cs.CV]AI-based Pilgrim Detection using Convolutional Neural Networks
    Marwa Ben Jabra, Adel Ammar, Anis Koubaa, Omar Cheikhrouhou, Habib Hamam
    http://arxiv.org/abs/1911.07509v1

    • [cs.CV]AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results
    Andreas Lugmayr, Martin Danelljan, Radu Timofte, Manuel Fritsche, Shuhang Gu, Kuldeep Purohit, Praveen Kandula, Maitreya Suin, A N Rajagopalan, Nam Hyung Joon, Yu Seung Won, Guisik Kim, Dokyeong Kwon, Chih-Chung Hsu, Chia-Hsiang Lin, Yuanfei Huang, Xiaopeng Sun, Wen Lu, Jie Li, Xinbo Gao, Sefi Bell-Kligler
    http://arxiv.org/abs/1911.07783v1

    • [cs.CV]Action Anticipation with RBF KernelizedFeature Mapping RNN
    Yuge Shi, Basura Fernando, Richard Hartley
    http://arxiv.org/abs/1911.07806v1

    • [cs.CV]Affine Self Convolution
    Nichita Diaconu, Daniel E Worrall
    http://arxiv.org/abs/1911.07704v1

    • [cs.CV]Aging Deep Face Features: Finding Missing Children
    Debayan Deb, Divyansh Aggarwal, Anil K. Jain
    http://arxiv.org/abs/1911.07538v1

    • [cs.CV]All-In-One: Facial Expression Transfer, Editing and Recognition Using A Single Network
    Kamran Ali, Charles E. Hughes
    http://arxiv.org/abs/1911.07050v1

    • [cs.CV]Automatic Annotation of Hip Anatomy in Fluoroscopy for Robust and Efficient 2D/3D Registration
    Robert Grupp, Mathias Unberath, Cong Gao, Rachel Hegeman, Ryan Murphy, Clayton Alexander, Yoshito Otake, Benjamin McArthur, Mehran Armand, Russell Taylor
    http://arxiv.org/abs/1911.07042v1

    • [cs.CV]Automatic Image Co-Segmentation: A Survey
    Xiabi Liu, Xin Duan
    http://arxiv.org/abs/1911.07685v1

    • [cs.CV]BSP-Net: Generating Compact Meshes via Binary Space Partitioning
    Zhiqin Chen, Andrea Tagliasacchi, Hao Zhang
    http://arxiv.org/abs/1911.06971v1

    • [cs.CV]Bias-Aware Heapified Policy for Active Learning
    Wen-Yen Chang, Wen-Huan Chiang, Shao-Hao Lu, Tingfan Wu, Min Sun
    http://arxiv.org/abs/1911.07574v1

    • [cs.CV]Capturing Hand Articulations using Recurrent Neural Network for 3D Hand Pose Estimation
    Cheol-hwan Yoo, Seung-wook Kim, Seo-won Ji, Yong-goo Shin, Sung-jea Ko
    http://arxiv.org/abs/1911.07424v1

    • [cs.CV]Constructing Multiple Tasks for Augmentation: Improving Neural Image Classification With K-means Features
    Tao Gui, Lizhi Qing, Qi Zhang, Jiacheng Ye, HangYan, Zichu Fei, Xuanjing Huang
    http://arxiv.org/abs/1911.07518v1

    • [cs.CV]Counterfactual Vision-and-Language Navigation via Adversarial Path Sampling
    Tsu-Jui Fu, Xin Wang, Matthew Peterson, Scott Grafton, Miguel Eckstein, William Yang Wang
    http://arxiv.org/abs/1911.07308v1

    • [cs.CV]Countering Inconsistent Labelling by Google’s Vision API for Rotated Images
    Aman Apte, Aritra Bandyopadhyay, K Akhilesh Shenoy, Jason Peter Andrews, Aditya Rathod, Manish Agnihotri, Aditya Jajodia
    http://arxiv.org/abs/1911.07201v1

    • [cs.CV]Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models
    Tong Che, Xiaofeng Liu, Site Li, Yubin Ge, Ruixiang Zhang, Caiming Xiong, Yoshua Bengio
    http://arxiv.org/abs/1911.07421v1

    • [cs.CV]DeepPFCN: Deep Parallel Feature Consensus Network For Person Re-Identification
    Shubham Kumar Singh, Krishna P Miyapuram, Shanmuganathan Raman
    http://arxiv.org/abs/1911.07776v1

    • [cs.CV]Defensive Few-shot Adversarial Learning
    Wenbin Li, Lei Wang, Xingxing Zhang, Jing Huo, Yang Gao, Jiebo Luo
    http://arxiv.org/abs/1911.06968v1

    • [cs.CV]Dense Color Constancy with Effective Edge Augmentation
    Yilang Zhang, Zheng Wei, Jian Wang, Xin Yuan
    http://arxiv.org/abs/1911.07163v1

    • [cs.CV]Detecting F-formations & Roles in Crowded Social Scenes with Wearables: Combining Proxemics & Dynamics using LSTMs
    Alessio Rosatelli, Ekin Gedik, Hayley Hung
    http://arxiv.org/abs/1911.07279v1

    • [cs.CV]DirectPose: Direct End-to-End Multi-Person Pose Estimation
    Zhi Tian, Hao Chen, Chunhua Shen
    http://arxiv.org/abs/1911.07451v1

    • [cs.CV]Distributed Low Precision Training Without Mixed Precision
    Zehua Cheng, Weiyang Wang, Yan Pan, Thomas Lukasiewicz
    http://arxiv.org/abs/1911.07384v1

    • [cs.CV]Distribution Context Aware Loss for Person Re-identification
    Zhigang Chang, Qin Zhou, Mingyang Yu, Shibao Zheng, Hua Yang, Tai-Pang Wu
    http://arxiv.org/abs/1911.07273v1

    • [cs.CV]Domain Generalization Using a Mixture of Multiple Latent Domains
    Toshihiko Matsuura, Tatsuya Harada
    http://arxiv.org/abs/1911.07661v1

    • [cs.CV]DualVD: An Adaptive Dual Encoding Model for Deep Visual Understanding in Visual Dialogue
    Xiaoze Jiang, Jing Yu, Zengchang Qin, Yingying Zhuang, Xingxing Zhang, Yue Hu, Qi Wu
    http://arxiv.org/abs/1911.07251v1

    • [cs.CV]Dynamic Instance Normalization for Arbitrary Style Transfer
    Yongcheng Jing, Xiao Liu, Yukang Ding, Xinchao Wang, Errui Ding, Mingli Song, Shilei Wen
    http://arxiv.org/abs/1911.06953v1

    • [cs.CV]ELoPE: Fine-Grained Visual Classification with Efficient Localization, Pooling and Embedding
    Harald Hanselmann, Hermann Ney
    http://arxiv.org/abs/1911.07344v1

    • [cs.CV]Effectively Unbiased FID and Inception Score and where to find them
    Min Jin Chong, David Forsyth
    http://arxiv.org/abs/1911.07023v1

    • [cs.CV]Extra Proximal-Gradient Inspired Non-local Network
    Qingchao Zhang, Yunmei Chen
    http://arxiv.org/abs/1911.07144v1

    • [cs.CV]FFA-Net: Feature Fusion Attention Network for Single Image Dehazing
    Xu Qin, Zhilin Wang, Yuanchao Bai, Xiaodong Xie, Huizhu Jia
    http://arxiv.org/abs/1911.07559v1

    • [cs.CV]Fast 3D Pose Refinement with RGB Images
    Abhinav Jain, Frank Dellaert
    http://arxiv.org/abs/1911.07347v1

    • [cs.CV]Fast Color Constancy with Patch-wise Bright Pixels
    Yiyao Shi, Jian Wang, Xiangyang Xue
    http://arxiv.org/abs/1911.07177v1

    • [cs.CV]Faster AutoAugment: Learning Augmentation Strategies using Backpropagation
    Ryuichiro Hataya, Jan Zdenek, Kazuki Yoshizoe, Hideki Nakayama
    http://arxiv.org/abs/1911.06987v1

    • [cs.CV]Fine-Grained Neural Architecture Search
    Heewon Kim, Seokil Hong, Bohyung Han, Heesoo Myeong, Kyoung Mu Lee
    http://arxiv.org/abs/1911.07478v1

    • [cs.CV]GLMNet: Graph Learning-Matching Networks for Feature Matching
    Bo Jiang, Pengfei Sun, Jin Tang, Bin Luo
    http://arxiv.org/abs/1911.07681v1

    • [cs.CV]Grounding Human-to-Vehicle Advice for Self-driving Vehicles
    Jinkyu Kim, Teruhisa Misu, Yi-Ting Chen, Ashish Tawari, John Canny
    http://arxiv.org/abs/1911.06978v1

    • [cs.CV]Instance Shadow Detection
    Tianyu Wang, Xiaowei Hu, Qiong Wang, Pheng-Ann Heng, Chi-Wing Fu
    http://arxiv.org/abs/1911.07034v1

    • [cs.CV]Ladder Loss for Coherent Visual-Semantic Embedding
    Mo Zhou, Zhenxing Niu, Le Wang, Zhanning Gao, Qilin Zhang, Gang Hua
    http://arxiv.org/abs/1911.07528v1

    • [cs.CV]Large Scale Open-Set Deep Logo Detection
    Muhammet Bastan, Hao-Yu Wu, Tian Cao, Bhargava Kota, Mehmet Tek
    http://arxiv.org/abs/1911.07440v1

    • [cs.CV]Learning Similarity Attention
    Meng Zheng, Srikrishna Karanam, Terrence Chen, Richard J. Radke, Ziyan Wu
    http://arxiv.org/abs/1911.07381v1

    • [cs.CV]Learning to Predict More Accurate Text Instances for Scene Text Detection
    XiaoQian Li, Jie Liu, ShuWu Zhang, GuiXuan Zhang
    http://arxiv.org/abs/1911.07423v1

    • [cs.CV]Learning to Synthesize Fashion Textures
    Wu Shi, Tak-Wai Hui, Ziwei Liu, Dahua Lin, Chen Change Loy
    http://arxiv.org/abs/1911.07472v1

    • [cs.CV]Learning with Hierarchical Complement Objective
    Hao-Yun Chen, Li-Huang Tsai, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan
    http://arxiv.org/abs/1911.07257v1

    • [cs.CV]Leveraging Multi-view Image Sets for Unsupervised Intrinsic Image Decomposition and Highlight Separation
    Renjiao Yi, Ping Tan, Stephen Lin
    http://arxiv.org/abs/1911.07262v1

    • [cs.CV]Long Range 3D with Quadocular Thermal (LWIR) Camera
    Andrey Filippov, Oleg Dzhimiev
    http://arxiv.org/abs/1911.06975v1

    • [cs.CV]Maintaining Discrimination and Fairness in Class Incremental Learning
    Bowen Zhao, Xi Xiao, Guojun Gan, Bin Zhang, Shutao Xia
    http://arxiv.org/abs/1911.07053v1

    • [cs.CV]MaskedFusion: Mask-based 6D Object Pose Detection
    Nuno Pereira, Luís A. Alexandre
    http://arxiv.org/abs/1911.07771v1

    • [cs.CV]Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual Recognition
    Satoshi Tsutsui, Yanwei Fu, David Crandall
    http://arxiv.org/abs/1911.07164v1

    • [cs.CV]Modeling Gestalt Visual Reasoning on the Raven’s Progressive Matrices Intelligence Test Using Generative Image Inpainting Techniques
    Tianyu Hua, Maithilee Kunda
    http://arxiv.org/abs/1911.07736v1

    • [cs.CV]Multi-Task Learning of Height and Semantics from Aerial Images
    Marcela Carvalho, Bertrand Le Saux, Pauline Trouvé-Peloux, Frédéric Champagnat, Andrés Almansa
    http://arxiv.org/abs/1911.07543v1

    • [cs.CV]Multiple Style-Transfer in Real-Time
    Michael Maring, Kaustav Chakraborty
    http://arxiv.org/abs/1911.06464v2

    • [cs.CV]On the well-posedness of uncalibrated photometric stereo under general lighting
    Mohammed Brahimi, Yvain Quéau, Bjoern Haefner, Daniel Cremers
    http://arxiv.org/abs/1911.07268v1

    • [cs.CV]Optimized CNN for PolSAR Image Classification via Differentiable Neural Architecture Search
    Hongwei Dong, Siyu Zhang, Bin Zou, Lamei Zhang
    http://arxiv.org/abs/1911.06993v1

    • [cs.CV]Oriented Boxes for Accurate Instance Segmentation
    Patrick Follmann, Rebecca König
    http://arxiv.org/abs/1911.07732v1

    • [cs.CV]Potential Field: Interpretable and Unified Representation for Trajectory Prediction
    Shan Su, Cheng Peng, Jianbo Shi, Chiho Choi
    http://arxiv.org/abs/1911.07414v1

    • [cs.CV]Preparing Lessons: Improve Knowledge Distillation with Better Supervision
    Tiancheng Wen, Shenqi Lai, Xueming Qian
    http://arxiv.org/abs/1911.07471v1

    • [cs.CV]Putting visual object recognition in context
    Mengmi Zhang, Claire Tseng, Gabriel Kreiman
    http://arxiv.org/abs/1911.07349v1

    • [cs.CV]Real-Time Semantic Segmentation via Multiply Spatial Fusion Network
    Haiyang Si, Zhiqiang Zhang, Feifan Lv, Gang Yu, Feng Lu
    http://arxiv.org/abs/1911.07217v1

    • [cs.CV]Revisiting Shadow Detection: A New Benchmark Dataset for Complex World
    Xiaowei Hu, Tianyu Wang, Chi-Wing Fu, Yitong Jiang, Qiong Wang, Pheng-Ann Heng
    http://arxiv.org/abs/1911.06998v1

    • [cs.CV]S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search
    Zhihang Yuan, Bingzhe Wu, Zheng Liang, Shiwan Zhao, Weichen Bi, Guangyu Sun
    http://arxiv.org/abs/1911.07033v1

    • [cs.CV]SA-Text: Simple but Accurate Detector for Text of Arbitrary Shapes
    Qitong Wang, Yi Zheng, Margrit Betke
    http://arxiv.org/abs/1911.07046v1

    • [cs.CV]SMART: Skeletal Motion Action Recognition aTtack
    He Wang, Feixiang He, Zexi Peng, Yongliang Yang, Tianjia Shao, Kun Zhou, David Hogg
    http://arxiv.org/abs/1911.07107v1

    • [cs.CV]SOGNet: Scene Overlap Graph Network for Panoptic Segmentation
    Yibo Yang, Hongyang Li, Xia Li, Qijie Zhao, Jianlong Wu, Zhouchen Lin
    http://arxiv.org/abs/1911.07527v1

    • [cs.CV]Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention
    Vivien Sainte Fare Garnot, Loic Landrieu, Sebastien Giordano, Nesrine Chehata
    http://arxiv.org/abs/1911.07757v1

    • [cs.CV]Self-supervised GAN: Analysis and Improvement with Multi-class Minimax Game
    Ngoc-Trung Tran, Viet-Hung Tran, Ngoc-Bao Nguyen, Linxiao Yang, Ngai-Man Cheung
    http://arxiv.org/abs/1911.06997v1

    • [cs.CV]SiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Tracking
    Dongyan Guo, Jun Wang, Ying Cui, Zhenhua Wang, Shengyong Chen
    http://arxiv.org/abs/1911.07241v1

    • [cs.CV]Signal Clustering with Class-independent Segmentation
    Stefano Gasperini, Magdalini Paschali, Carsten Hopke, David Wittmann, Nassir Navab
    http://arxiv.org/abs/1911.07590v1

    • [cs.CV]Signed Input Regularization
    Saeid Asgari Taghanaki, Kumar Abhishek, Ghassan Hamarneh
    http://arxiv.org/abs/1911.07086v1

    • [cs.CV]TSRNet: Scalable 3D Surface Reconstruction Network for Point Clouds using Tangent Convolution
    Zhenxing Mi, Yiming Luo, Wenbing Tao
    http://arxiv.org/abs/1911.07401v1

    • [cs.CV]The Devil is in the Details: Delving into Unbiased Data Processing for Human Pose Estimation
    Junjie Huang, Zheng Zhu, Feng Guo, Guan Huang
    http://arxiv.org/abs/1911.07524v1

    • [cs.CV]The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersections
    Julian Bock, Robert Krajewski, Tobias Moers, Steffen Runde, Lennart Vater, Lutz Eckstein
    http://arxiv.org/abs/1911.07602v1

    • [cs.CV]Towards Robust RGB-D Human Mesh Recovery
    Ren Li, Changjiang Cai, Georgios Georgakis, Srikrishna Karanam, Terrence Chen, Ziyan Wu
    http://arxiv.org/abs/1911.07383v1

    • [cs.CV]Towards Visually Explaining Variational Autoencoders
    Wenqian Liu, Runze Li, Meng Zheng, Srikrishna Karanam, Ziyan Wu, Bir Bhanu, Richard J. Radke, Octavia Camps
    http://arxiv.org/abs/1911.07389v1

    • [cs.CV]Towards the Automation of Deep Image Prior
    Qianwei Zhou, Chen Zhou, Haigen Hu, Yuhang Chen, Shengyong Chen, Xiaoxin Li
    http://arxiv.org/abs/1911.07185v1

    • [cs.CV]Transductive Zero-Shot Hashing for Multi-Label Image Retrieval
    Qin Zou, Zheng Zhang, Ling Cao, Long Chen, Song Wang
    http://arxiv.org/abs/1911.07192v1

    • [cs.CV]Unsupervised Deep Metric Learning via Auxiliary Rotation Loss
    Xuefei Cao, Bor-Chun Chen, Ser-Nam Lim
    http://arxiv.org/abs/1911.07072v1

    • [cs.CV]Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning
    Fuxun Yu, Di Wang, Yinpeng Chen, Nikolaos Karianakis, Pei Yu, Dimitrios Lymberopoulos, Xiang Chen
    http://arxiv.org/abs/1911.07158v1

    • [cs.CV]Unsupervised Reinforcement Learning of Transferable Meta-Skills for Embodied Navigation
    Juncheng Li, Xin Wang, Siliang Tang, Haizhou Shi, Fei Wu, Yueting Zhuang, William Yang Wang
    http://arxiv.org/abs/1911.07450v1

    • [cs.CV]Unsupervised Representation Learning by Discovering Reliable Image Relations
    Timo Milbich, Omair Ghori, Ferran Diego, Björn Ommer
    http://arxiv.org/abs/1911.07808v1

    • [cs.CV]Unsupervised Representation Learning for Gaze Estimation
    Yu Yu, Jean-Marc Odobez
    http://arxiv.org/abs/1911.06939v1

    • [cs.CV]Unsupervised Visual Representation Learning with Increasing Object Shape Bias
    Zhibo Wang, Shen Yan, Xiaoyu Zhang, Mubarak Shah, Niels Lobo
    http://arxiv.org/abs/1911.07272v1

    • [cs.CV]Weakly Supervised Object Localization with Inter-Intra Regulated CAMs
    Guofeng Cui, Ziyi Kou, Shaojie Wang, Wentian Zhao, Chenliang Xu
    http://arxiv.org/abs/1911.07160v1

    • [cs.CY]Adaptive Learning Guidance System (ALGS)
    Ghada El-Hadad, Doaa Shawky, Ashraf Badawi
    http://arxiv.org/abs/1911.06812v1

    • [cs.DB]IDEALEM: Statistical Similarity Based Data Reduction
    Dongeun Lee, Alex Sim, Jaesik Choi, Kesheng Wu
    http://arxiv.org/abs/1911.06980v1

    • [cs.DB]Using Mapping Languages for Building Legal Knowledge Graphs from XML Files
    Ademar Crotti Junior, Fabrizio Orlandi, Declan O’Sullivan, Christian Dirschl, Quentin Reul
    http://arxiv.org/abs/1911.07673v1

    • [cs.DC]A Code injection Method for Rapid Docker Image Building
    Yujing Wang, Qinyang Bao
    http://arxiv.org/abs/1911.07444v1

    • [cs.DC]Distributed Machine Learning through Heterogeneous Edge Systems
    Hanpeng Hu, Dan Wang, Chuan Wu
    http://arxiv.org/abs/1911.06949v1

    • [cs.DC]Pangolin: An Efficient and Flexible Graph Mining System on CPU and GPU
    Xuhao Chen, Roshan Dathathri, Gurbinder Gill, Keshav Pingali
    http://arxiv.org/abs/1911.06969v1

    • [cs.DC]Towards Design Methodology of Efficient Fast Algorithms for Accelerating Generative Adversarial Networks on FPGAs
    Jung-Woo Chang, Saehyun Ahn, Keon-Woo Kang, Suk-Ju Kang
    http://arxiv.org/abs/1911.06918v1

    • [cs.DM]Optimal adaptive group testing
    Max Hahn-Klimroth, Philipp Loick
    http://arxiv.org/abs/1911.06647v2

    • [cs.DS]Random Restrictions of High-Dimensional Distributions and Uniformity Testing with Subcube Conditioning
    Clément L. Canonne, Xi Chen, Gautam Kamath, Amit Levi, Erik Waingarten
    http://arxiv.org/abs/1911.07357v1

    • [cs.DS]Sparse Hopsets in Congested Clique
    Yasamin Nazari
    http://arxiv.org/abs/1911.07154v1

    • [cs.DS]Testing Properties of Multiple Distributions with Few Samples
    Maryam Aliakbarpour, Sandeep Silwal
    http://arxiv.org/abs/1911.07324v1

    • [cs.GT]Learning Probably Approximately Correct Maximin Strategies in Simulation-Based Games with Infinite Strategy Spaces
    Alberto Marchesi, Francesco Trovò, Nicola Gatti
    http://arxiv.org/abs/1911.07755v1

    • [cs.HC]A Sketch-Based System for Human-Guided Constrained Object Manipulation
    Sina Masnadi, Joseph J. LaViola Jr., Jana Pavlasek, Xiaofan Zhu, Karthik Desingh, Odest Chadwicke Jenkins
    http://arxiv.org/abs/1911.07340v1

    • [cs.HC]Developing a Scenario-Based Video Game Generation Framework: Preliminary Results
    Elif Surer, Mustafa Erkayaoğlu, Zeynep Nur Öztürk, Furkan Yücel, Emin Alp Bıyık, Burak Altan, Büşra Şenderin, Zeliha Oğuz, Servet Gürer, H. Şebnem Düzgün
    http://arxiv.org/abs/1911.07380v1

    • [cs.IR]A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research
    Maurizio Ferrari Dacrema, Simone Boglio, Paolo Cremonesi, Dietmar Jannach
    http://arxiv.org/abs/1911.07698v1

    • [cs.IR]Common Artist Music Assistance
    Manish Agnihotri, Adiyta Rathod, Aditya Jajodia, Chethan Sharma
    http://arxiv.org/abs/1911.07200v1

    • [cs.IR]Pairwise Interactive Graph Attention Network for Context-Aware Recommendation
    Yahui Liu, Furao Shen, Jian Zhao
    http://arxiv.org/abs/1911.07429v1

    • [cs.IR]Quels corpus d’entraînement pour l’expansion de requêtes par plongement de mots : application à la recherche de microblogs culturels
    Philippe Mulhem, Lorraine Goeuriot, Massih-Reza Amini, Nayanika Dogra
    http://arxiv.org/abs/1911.07317v1

    • [cs.IR]Rumor Detection on Social Media: Datasets, Methods and Opportunities
    Quanzhi Li, Qiong Zhang, Luo Si, Yingchi Liu
    http://arxiv.org/abs/1911.07199v1

    • [cs.IT]Channel Estimation in Massive MIMO under Hardware Non-Linearities: Bayesian Methods versus Deep Learning
    Özlem Tugfe Demir, Emil Björnson
    http://arxiv.org/abs/1911.07316v1

    • [cs.IT]Degrees of Freedom of Holographic MIMO Channels
    Andrea Pizzo, Thomas L. Marzetta, Luca Sanguinetti
    http://arxiv.org/abs/1911.07516v1

    • [cs.IT]Demand-Private Coded Caching and the Exact Trade-off for N=K=2
    Sneha Kamath, Jithin Ravi, Bikash Kumar Dey
    http://arxiv.org/abs/1911.06995v1

    • [cs.IT]Deterministic partial binary circulant compressed sensing matrices
    Arman Arian, Ozgur Yilmaz
    http://arxiv.org/abs/1911.07497v1

    • [cs.IT]Finding the Exact Distribution of (Peak) Age of Information for Queues of PH/PH/1/1 and M/PH/1/2 Type
    Nail Akar, Ozancan Dogan, Eray Unsal Atay
    http://arxiv.org/abs/1911.07274v1

    • [cs.IT]Identify Equivalent Frames
    Xuemei Chen, Yang Chu, Min Zheng
    http://arxiv.org/abs/1911.07356v1

    • [cs.IT]Learning The MMSE Channel Predictor
    Nurettin Turan, Wolfgang Utschick
    http://arxiv.org/abs/1911.07256v1

    • [cs.IT]Locally recoverable $J$-affine variety codes
    Carlos Galindo, Fernando Hernando, Carlos Munuera
    http://arxiv.org/abs/1911.07485v1

    • [cs.IT]Multiple-Source Ellipsoidal Localization Using Acoustic Energy Measurements
    Fanqin Meng, Xiaojing Shen, Zhiguo Wang, Haiqi Liu, Junfeng Wang, Yunmin Zhu, Pramod K. Varshney
    http://arxiv.org/abs/1911.07180v1

    • [cs.IT]On one-stage recovery for $ΣΔ$-quantized compressed sensing
    Arman Arian, Ozgur Yilmaz
    http://arxiv.org/abs/1911.07525v1

    • [cs.IT]On q-ary Bent and Plateaued Functions
    Vladimir N. Potapov
    http://arxiv.org/abs/1911.06973v1

    • [cs.IT]On the Age of Information in Multi-Source Queueing Models
    Mohammad Moltafet, Markus Leinonen, Marian Codreanu
    http://arxiv.org/abs/1911.07029v1

    • [cs.IT]On the Hamming distances of repeated-root cyclic codes of length $5p^s$
    Xia Li, Qin Yue
    http://arxiv.org/abs/1911.07542v1

    • [cs.IT]Optimal deployments of UAVs with directional antennas for a power-efficient coverage
    Jun Guo, Philipp Walk, Hamid Jafarkhani
    http://arxiv.org/abs/1911.07463v1

    • [cs.IT]Predicting Device-to-Device Channels from Cellular Channel Measurements: A Learning Approach
    Mehyar Najla, Zdenek Becvar, Pavel Mach, David Gesbert
    http://arxiv.org/abs/1911.07191v1

    • [cs.IT]Projection decoding of some binary optimal linear codes of lengths 36 and 40
    Lucky Galvez, Jon-Lark Kim
    http://arxiv.org/abs/1911.07212v1

    • [cs.IT]Quantized Compressed Sensing by Rectified Linear Units
    Hans Christian Jung, Johannes Maly, Lars Palzer, Alexander Stollenwerk
    http://arxiv.org/abs/1911.07816v1

    • [cs.IT]RIP constants for deterministic compressed sensing matrices-beyond Gershgorin
    Arman Arian, Ozgur Yilmaz
    http://arxiv.org/abs/1911.07428v1

    • [cs.IT]Secure Communication for Spatially Sparse Millimeter-Wave Massive MIMO Channels via Hybrid Precoding
    Jindan Xu, Wei Xu, Derrick Wing Kwan Ng, A. Lee Swindlehurst
    http://arxiv.org/abs/1911.07017v1

    • [cs.IT]Sparse Bayesian Multi-Task Learning of Time-Varying Massive MIMO Channels with Dynamic Filtering
    Arash Shahmansoori
    http://arxiv.org/abs/1911.07570v1

    • [cs.IT]Study of Non-Uniform Channel Polarization and Design of Polar Codes with Arbitrary Rates
    Robert M. Oliveira, Rodrigo C. de Lamare
    http://arxiv.org/abs/1911.07137v1

    • [cs.IT]The Parameters of Minimal Linear Codes
    Wei Lu, Xia Wu, Xiwang Cao
    http://arxiv.org/abs/1911.07648v1

    • [cs.IT]Throughput Maximization with an Average Age of Information Constraint in Fading Channels
    Rajshekhar Vishweshwar Bhat, Rahul Vaze, Mehul Motani
    http://arxiv.org/abs/1911.07499v1

    • [cs.IT]Two-weight codes over the integers modulo a prime power
    Minjia Shi, Tor Helleseth, Patrick Sole
    http://arxiv.org/abs/1911.07657v1

    • [cs.LG]$DC^2$: A Divide-and-conquer Algorithm for Large-scale Kernel Learning with Application to Clustering
    Ke Alexander Wang, Xinran Bian, Pan Liu, Donghui Yan
    http://arxiv.org/abs/1911.06944v1

    • [cs.LG]A Graph Autoencoder Approach to Causal Structure Learning
    Ignavier Ng, Shengyu Zhu, Zhitang Chen, Zhuangyan Fang
    http://arxiv.org/abs/1911.07420v1

    • [cs.LG]A Multi-Task Gradient Descent Method for Multi-Label Learning
    Lu Bai, Yew-Soon Ong, Tiantian He, Abhishek Gupta
    http://arxiv.org/abs/1911.07693v1

    • [cs.LG]A New Ensemble Adversarial Attack Powered by Long-term Gradient Memories
    Zhaohui Che, Ali Borji, Guangtao Zhai, Suiyi Ling, Jing Li, Patrick Le Callet
    http://arxiv.org/abs/1911.07682v1

    • [cs.LG]An “outside the box” solution for imbalanced data classification
    Hubert Jegierski, Stanisław Saganowski
    http://arxiv.org/abs/1911.06965v1

    • [cs.LG]An Empirical and Comparative Analysis of Data Valuation with Scalable Algorithms
    Ruoxi Jia, Xuehui Sun, Jiacen Xu, Ce Zhang, Bo Li, Dawn Song
    http://arxiv.org/abs/1911.07128v1

    • [cs.LG]An explanation method for Siamese neural networks
    Lev V. Utkin, Maxim S. Kovalev, Ernest M. Kasimov
    http://arxiv.org/abs/1911.07702v1

    • [cs.LG]Any-Precision Deep Neural Networks
    Haichao Yu, Haoxiang Li, Honghui Shi, Thomas S. Huang, Gang Hua
    http://arxiv.org/abs/1911.07346v1

    • [cs.LG]Bayesian Recurrent Framework for Missing Data Imputation and Prediction with Clinical Time Series
    Yang Guo, Zhengyuan Liu, Pavitra Krishnswamy, Savitha Ramasamy
    http://arxiv.org/abs/1911.07572v1

    • [cs.LG]Benanza: Automatic uBenchmark Generation to Compute “Lower-bound” Latency and Inform Optimizations of Deep Learning Models on GPUs
    Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-mei Hwu
    http://arxiv.org/abs/1911.06922v1

    • [cs.LG]Binary Sine Cosine Algorithms for Feature Selection from Medical Data
    Shokooh Taghian, Mohammad H. Nadimi-Shahraki
    http://arxiv.org/abs/1911.07805v1

    • [cs.LG]Black-Box Adversarial Attack with Transferable Model-based Embedding
    Zhichao Huang, Tong Zhang
    http://arxiv.org/abs/1911.07140v1

    • [cs.LG]Causality-based Feature Selection: Methods and Evaluations
    Kui Yu, Xianjie Guo, Lin Liu, Jiuyong Li, Hao Wang, Zhaolong Ling, Xindong Wu
    http://arxiv.org/abs/1911.07147v1

    • [cs.LG]Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis
    Yifan Zhang, Ying Wei, Peilin Zhao, Shuaicheng Niu, Qingyao Wu, Mingkui Tan, Junzhou Huang
    http://arxiv.org/abs/1911.07293v1

    • [cs.LG]Convex Formulation of Overparameterized Deep Neural Networks
    Cong Fang, Yihong Gu, Weizhong Zhang, Tong Zhang
    http://arxiv.org/abs/1911.07626v1

    • [cs.LG]Coverage Testing of Deep Learning Models using Dataset Characterization
    Senthil Mani, Anush Sankaran, Srikanth Tamilselvam, Akshay Sethi
    http://arxiv.org/abs/1911.07309v1

    • [cs.LG]Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learning
    Kevin Sebastian Luck, Heni Ben Amor, Roberto Calandra
    http://arxiv.org/abs/1911.06832v1

    • [cs.LG]Deep geometric matrix completion: Are we doing it right?
    Amit Boyarski, Sanketh Vedula, Alex Bronstein
    http://arxiv.org/abs/1911.07255v1

    • [cs.LG]Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning
    Cameron Voloshin, Hoang M. Le, Nan Jiang, Yisong Yue
    http://arxiv.org/abs/1911.06854v1

    • [cs.LG]Encouraging an Appropriate Representation Simplifies Training of Neural Networks
    Krisztian Buza
    http://arxiv.org/abs/1911.07245v1

    • [cs.LG]Explanatory Masks for Neural Network Interpretability
    Lawrence Phillips, Garrett Goh, Nathan Hodas
    http://arxiv.org/abs/1911.06876v1

    • [cs.LG]Fast Machine Learning with Byzantine Workers and Servers
    El Mahdi El Mhamdi, Rachid Guerraoui, Arsany Guirguis
    http://arxiv.org/abs/1911.07537v1

    • [cs.LG]Feedback Control for Online Training of Neural Networks
    Zilong Zhao, Sophie Cerf, Bogdan Robu, Nicolas Marchand
    http://arxiv.org/abs/1911.07710v1

    • [cs.LG]Gamma-Nets: Generalizing Value Estimation over Timescale
    Craig Sherstan, Shibhansh Dohare, James MacGlashan, Johannes Günther, Patrick M. Pilarski
    http://arxiv.org/abs/1911.07794v1

    • [cs.LG]Glyph: Fast and Accurately Training Deep Neural Networks on Encrypted Data
    Qian Lou, Bo Feng, Geoffrey C. Fox, Lei Jiang
    http://arxiv.org/abs/1911.07101v1

    • [cs.LG]GraLSP: Graph Neural Networks with Local Structural Patterns
    Yilun Jin, Guojie Song, Chuan Shi
    http://arxiv.org/abs/1911.07675v1

    • [cs.LG]Graph Neural Ordinary Differential Equations
    Michael Poli, Stefano Massaroli, Junyoung Park, Atsushi Yamashita, Hajime Asama, Jinkyoo Park
    http://arxiv.org/abs/1911.07532v1

    • [cs.LG]Graph-Revised Convolutional Network
    Donghan Yu, Ruohong Zhang, Zhengbao Jiang, Yuexin Wu, Yiming Yang
    http://arxiv.org/abs/1911.07123v1

    • [cs.LG]Grassmannian Packings in Neural Networks: Learning with Maximal Subspace Packings for Diversity and Anti-Sparsity
    Dian Ang Yap, Nicholas Roberts, Vinay Uday Prabhu
    http://arxiv.org/abs/1911.07418v1

    • [cs.LG]Hebbian Synaptic Modifications in Spiking Neurons that Learn
    Peter L. Bartlett, Jonathan Baxter
    http://arxiv.org/abs/1911.07247v1

    • [cs.LG]Improved Exploration through Latent Trajectory Optimization in Deep Deterministic Policy Gradient
    Kevin Sebastian Luck, Mel Vecerik, Simon Stepputtis, Heni Ben Amor, Jonathan Scholz
    http://arxiv.org/abs/1911.06833v1

    • [cs.LG]Inductive Relation Prediction on Knowledge Graphs
    Komal K. Teru, William L. Hamilton
    http://arxiv.org/abs/1911.06962v1

    • [cs.LG]Influence-aware Memory for Deep Reinforcement Learning
    Miguel Suau de Castro, Elena Congeduti, Rolf Starre, Aleksander Czechowski, Frans Olihoek
    http://arxiv.org/abs/1911.07643v1

    • [cs.LG]Information-Theoretic Perspective of Federated Learning
    Linara Adilova, Julia Rosenzweig, Michael Kamp
    http://arxiv.org/abs/1911.07652v1

    • [cs.LG]Inverse Reinforcement Learning with Missing Data
    Tien Mai, Quoc Phong Nguyen, Kian Hsiang Low, Patrick Jaillet
    http://arxiv.org/abs/1911.06930v1

    • [cs.LG]Justification-Based Reliability in Machine Learning
    Nurali Virani, Naresh Iyer, Zhaoyuan Yang
    http://arxiv.org/abs/1911.07391v1

    • [cs.LG]Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks
    Difan Zou, Ziniu Hu, Yewen Wang, Song Jiang, Yizhou Sun, Quanquan Gu
    http://arxiv.org/abs/1911.07323v1

    • [cs.LG]Learning Behavioral Representations from Wearable Sensors
    Nazgol Tavabi, Homa Hosseinmardi, Jennifer L. Villatte, Andrés Abeliuk, Shrikanth Narayanan, Emilio Ferrara, Kristina Lerman
    http://arxiv.org/abs/1911.06959v1

    • [cs.LG]Loss Aware Post-training Quantization
    Yury Nahshan, Brian Chmiel, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Alex M. Bronstein, Avi Mendelson
    http://arxiv.org/abs/1911.07190v1

    • [cs.LG]Missingness as Stability: Understanding the Structure of Missingness in Longitudinal EHR data and its Impact on Reinforcement Learning in Healthcare
    Scott L. Fleming, Kuhan Jeyapragasan, Tony Duan, Daisy Ding, Saurabh Gombar, Nigam Shah, Emma Brunskill
    http://arxiv.org/abs/1911.07084v1

    • [cs.LG]NAIS: Neural Architecture and Implementation Search and its Applications in Autonomous Driving
    Cong Hao, Yao Chen, Xinheng Liu, Atif Sarwari, Daryl Sew, Ashutosh Dhar, Bryan Wu, Dongdong Fu, Jinjun Xiong, Wen-mei Hwu, Junli Gu, Deming Chen
    http://arxiv.org/abs/1911.07446v1

    • [cs.LG]Neural Recurrent Structure Search for Knowledge Graph Embedding
    Yongqi Zhang, Quanming Yao, Lei Chen
    http://arxiv.org/abs/1911.07132v1

    • [cs.LG]Off-Policy Policy Gradient Algorithms by Constraining the State Distribution Shift
    Riashat Islam, Komal K. Teru, Deepak Sharma
    http://arxiv.org/abs/1911.06970v1

    • [cs.LG]On Value Discrepancy of Imitation Learning
    Tian Xu, Ziniu Li, Yang Yu
    http://arxiv.org/abs/1911.07027v1

    • [cs.LG]Online Adaptive Asymmetric Active Learning with Limited Budgets
    Yifan Zhang, Peilin Zhao, Shuaicheng Niu, Qingyao Wu, Jiezhang Cao, Junzhou Huang, Mingkui Tan
    http://arxiv.org/abs/1911.07498v1

    • [cs.LG]Program synthesis performance constrained by non-linear spatial relations in Synthetic Visual Reasoning Test
    Lu Yihe, Scott C. Lowe, Penelope A. Lewis, Mark C. W. van Rossum
    http://arxiv.org/abs/1911.07721v1

    • [cs.LG]Prototypical Networks for Multi-Label Learning
    Zhuo Yang, Yufei Han, Guoxian Yu, Xiangliang Zhang
    http://arxiv.org/abs/1911.07203v1

    • [cs.LG]Provable Filter Pruning for Efficient Neural Networks
    Lucas Liebenwein, Cenk Baykal, Harry Lang, Dan Feldman, Daniela Rus
    http://arxiv.org/abs/1911.07412v1

    • [cs.LG]Query Complexity of Bayesian Private Learning
    Kuang Xu
    http://arxiv.org/abs/1911.06903v1

    • [cs.LG]RSM-GAN: A Convolutional Recurrent GAN for Anomaly Detection in Contaminated Seasonal Multivariate Time Series
    Farzaneh Khoshnevisan, Zhewen Fan
    http://arxiv.org/abs/1911.07104v1

    • [cs.LG]Rebalancing Learning on Evolving Data Streams
    Alessio Bernardo, Emanuele Della Valle, Albert Bifet
    http://arxiv.org/abs/1911.07361v1

    • [cs.LG]Reinforcement Learning from Imperfect Demonstrations under Soft Expert Guidance
    Mingxuan Jing, Xiaojian Ma, Wenbing Huang, Fuchun Sun, Chao Yang, Bin Fang, Huaping Liu
    http://arxiv.org/abs/1911.07109v1

    • [cs.LG]Robust Anomaly Detection and Backdoor Attack Detection Via Differential Privacy
    Min Du, Ruoxi Jia, Dawn Song
    http://arxiv.org/abs/1911.07116v1

    • [cs.LG]RotationOut as a Regularization Method for Neural Network
    Kai Hu, Barnabas Poczos
    http://arxiv.org/abs/1911.07427v1

    • [cs.LG]Safe squeezing for antisparse coding
    Clément Elvira, Cédric Herzet
    http://arxiv.org/abs/1911.07508v1

    • [cs.LG]Selective sampling for accelerating training of deep neural networks
    Berry Weinstein, Shai Fine, Yacov Hel-Or
    http://arxiv.org/abs/1911.06996v1

    • [cs.LG]Smoothed Inference for Adversarially-Trained Models
    Yaniv Nemcovsky, Evgenii Zheltonozhskii, Chaim Baskin, Brian Chmiel, Alex M. Bronstein, Avi Mendelson
    http://arxiv.org/abs/1911.07198v1

    • [cs.LG]Sparse $\ell_1$ and $\ell_2$ Center Classifiers
    Giuseppe C. Calafiore, Giulia Fracastoro
    http://arxiv.org/abs/1911.07320v1

    • [cs.LG]Suspicion-Free Adversarial Attacks on Clustering Algorithms
    Anshuman Chhabra, Abhishek Roy, Prasant Mohapatra
    http://arxiv.org/abs/1911.07015v1

    • [cs.LG]SySCD: A System-Aware Parallel Coordinate Descent Algorithm
    Nikolas Ioannou, Celestine Mendler-Dünner, Thomas Parnell
    http://arxiv.org/abs/1911.07722v1

    • [cs.LG]The Effectiveness of Variational Autoencoders for Active Learning
    Farhad Pourkamali-Anaraki, Michael B. Wakin
    http://arxiv.org/abs/1911.07716v1

    • [cs.LG]The Proper Care and Feeding of CAMELS: How Limited Training Data Affects Streamflow Prediction
    Martin Gauch, Juliane Mai, Jimmy Lin
    http://arxiv.org/abs/1911.07249v1

    • [cs.LG]The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks
    Yuheng Zhang, Ruoxi Jia, Hengzhi Pei, Wenxiao Wang, Bo Li, Dawn Song
    http://arxiv.org/abs/1911.07135v1

    • [cs.LG]Towards Making Deep Transfer Learning Never Hurt
    Ruosi Wan, Haoyi Xiong, Xingjian Li, Zhanxing Zhu, Jun Huan
    http://arxiv.org/abs/1911.07489v1

    • [cs.LG]Towards Quantification of Bias in Machine Learning for Healthcare: A Case Study of Renal Failure Prediction
    Josie Williams, Narges Razavian
    http://arxiv.org/abs/1911.07679v1

    • [cs.LG]Understanding and Improving Layer Normalization
    Jingjing Xu, Xu Sun, Zhiyuan Zhang, Guangxiang Zhao, Junyang Lin
    http://arxiv.org/abs/1911.07013v1

    • [cs.LG]VLUC: An Empirical Benchmark for Video-Like Urban Computing on Citywide Crowd and Traffic Prediction
    Renhe Jiang, Zekun Cai, Zhaonan Wang, Chuang Yang, Zipei Fan, Xuan Song, Kota Tsubouchi, Ryosuke Shibasaki
    http://arxiv.org/abs/1911.06982v1

    • [cs.LG]Vulnerability Analysis for Data Driven Pricing Schemes
    Jingshi Cui, Haoxiang Wang, Chenye Wu, Yang Yu
    http://arxiv.org/abs/1911.07453v1

    • [cs.LG]Walking the Tightrope: An Investigation of the Convolutional Autoencoder Bottleneck
    Ilja Manakov, Markus Rohm, Volker Tresp
    http://arxiv.org/abs/1911.07460v1

    • [cs.LG]What Will Your Child Look Like? DNA-Net: Age and Gender Aware Kin Face Synthesizer
    Pengyu Gao, Siyu Xia, Joseph Robinson, Junkang Zhang, Chao Xia, Ming Shao, Yun Fu
    http://arxiv.org/abs/1911.07014v1

    • [cs.LG]Working Memory Graphs
    Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew Hausknecht
    http://arxiv.org/abs/1911.07141v1

    • [cs.MM]Parametric Graph-based Separable Transforms for Video Coding
    Hilmi E. Egilmez, Oguzhan Teke, Amir Said, Vadim Seregin, Marta Karczewicz
    http://arxiv.org/abs/1911.06981v1

    • [cs.MM]Understanding the Teaching Styles by an Attention based Multi-task Cross-media Dimensional modelling
    Suping Zhou, Jia Jia, Yufeng Yin, Xiang Li, Yang Yao, Ying Zhang, Zeyang Ye, Kehua Lei, Yan Huang, Jialie Shen
    http://arxiv.org/abs/1911.07253v1

    • [cs.MS]Semi-Automatic Task Graph Construction for $\mathcal{H}$-Matrix Arithmetic
    Steffen Börm, Sven Christophersen, Ronald Kriemann
    http://arxiv.org/abs/1911.07531v1

    • [cs.NE]ImmuNeCS: Neural Committee Search by an Artificial Immune System
    Luc Frachon, Wei Pang, George M. Coghill
    http://arxiv.org/abs/1911.07729v1

    • [cs.NE]Particle Swarm and EDAs
    Alison Jenkins, Vinika Gupta, Alexis Myrick, Mary Lenoir
    http://arxiv.org/abs/1911.07112v1

    • [cs.NI]Caching Techniques to Improve Latency in Serverless Architectures
    Bishakh Chandra Ghosh, Sourav Kanti Addya, Nishant Baranwal Somy, Shubha Brata Nath, Sandip Chakraborty, Soumya K Ghosh
    http://arxiv.org/abs/1911.07351v1

    • [cs.NI]Profile-based Resource Allocation for Virtualized Network Functions
    Steven Van Rossem, Wouter Tavernier, Didier Colle, Mario Pickavet, Piet Demeester
    http://arxiv.org/abs/1911.07738v1

    • [cs.NI]The geopolitics behind the routes data travels: a case study of Iran
    Loqman Salamatian, Frederick Douzet, Kevin Limonier, Kavé Salamatian
    http://arxiv.org/abs/1911.07723v1

    • [cs.PF]Understanding Open Source Serverless Platforms: Design Considerations and Performance
    Junfeng Li, Sameer G. Kulkarni, K. K. Ramakrishnan, Dan Li
    http://arxiv.org/abs/1911.07449v1

    • [cs.PL]PriorityGraph: A Unified Programming Model for Optimizing Ordered Graph Algorithms
    Yunming Zhang, Ajay Brahmakshatriya, Xinyi Chen, Laxman Dhulipala, Shoaib Kamil, Saman Amarasinghe, Julian Shun
    http://arxiv.org/abs/1911.07260v1

    • [cs.RO]A Hierarchical Framework to Generate Robust Biped Locomotion Based on Divergent Component of Motion
    Mohammadreza Kasaei, Nuno Lau, Artur Pereira
    http://arxiv.org/abs/1911.07505v1

    • [cs.RO]A gamified simulator and physical platform for self-driving algorithm training and validation
    Joshua E. Siegel, Georgios Pappas, Konstantinos Politopoulos, Yongbin Sun
    http://arxiv.org/abs/1911.07759v1

    • [cs.RO]Adaptive Leader-Follower Formation Control and Obstacle Avoidance via Deep Reinforcement Learning
    Yanlin Zhou, Fan Lu, George Pu, Xiyao Ma, Runhan Sun, Hsi-Yuan Chen, Xiaolin Li, Dapeng Wu
    http://arxiv.org/abs/1911.06882v1

    • [cs.RO]Design of the First Insect-scale Spinning-wing Robot
    Palak Bhushan, Claire Tomlin
    http://arxiv.org/abs/1911.06947v1

    • [cs.RO]Development of MirrorShape: High Fidelity Large-Scale Shape Rendering Framework for Virtual Reality
    Aleksey Fedoseev, Nikita Chernyadev, Dzmitry Tsetserukou
    http://arxiv.org/abs/1911.07408v1

    • [cs.RO]Fast 2D Map Matching Based on Area Graphs
    Jiawei Hou, Haofei Kuang, Sören Schwertfeger
    http://arxiv.org/abs/1911.07432v1

    • [cs.RO]Flexoskeleton printing for versatile insect-inspired robots
    Mingsong Jiang, Ziyi Zhou, Nicholas G. Gravish
    http://arxiv.org/abs/1911.06897v1

    • [cs.RO]Ground and Non-Ground Separation Filter for UAV Lidar Point Cloud
    Geesara Prathap, Roman Fedorenko, Alexandr Klimchik
    http://arxiv.org/abs/1911.06994v1

    • [cs.RO]IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks
    Youngwoon Lee, Edward S. Hu, Zhengyu Yang, Alex Yin, Joseph J. Lim
    http://arxiv.org/abs/1911.07246v1

    • [cs.RO]Object Finding in Cluttered Scenes Using Interactive Perception
    Tonci Novkovic, Remi Pautrat, Fadri Furrer, Michel Breyer, Roland Siegwart, Juan Nieto
    http://arxiv.org/abs/1911.07482v1

    • [cs.RO]Optimal Control of a Differentially Flat 2D Spring-Loaded Inverted Pendulum Model
    Hua Chen, Patrick M. Wensing, Wei Zhang
    http://arxiv.org/abs/1911.07168v1

    • [cs.RO]Robotic Sculpting with Collision-free Motion Planning in Voxel Space
    Abhinav Jain, Seth Hutchinson, Frank Dellaert
    http://arxiv.org/abs/1911.07348v1

    • [cs.RO]Strategy Synthesis for Surveillance-Evasion Games with Learning-Enabled Visibility Optimization
    Suda Bharadwaj, Louis Ly, Bo Wu, Richard Tsai, Ufuk Topcu
    http://arxiv.org/abs/1911.07394v1

    • [cs.SE]patch2vec: Distributed Representation of Code Changes
    Rocìo Cabrera Lozoya, Arnaud Baumann, Antonino Sabetta, Michele Bezzi
    http://arxiv.org/abs/1911.07605v1

    • [cs.SI]A First Look at References from the Dark to Surface Web World
    Mahdieh Zabihimayvan, Derek Doran
    http://arxiv.org/abs/1911.07814v1

    • [cs.SI]An Application of Random Walk on Fake Account Detection Problem: A Hybrid Approach
    Ngoc C. Lê, Manh-Tuan Dao, Hoang-Linh Nguyen, Tuyet-Nhi Nguyen, Hue Vu
    http://arxiv.org/abs/1911.07609v1

    • [cs.SI]An Induced Multi-Relational Framework for Answer Selection in Community Question Answer Platforms
    Kanika Narang, Chaoqi Yang, Adit Krishnan, Junting Wang, Hari Sundaram, Carolyn Sutter
    http://arxiv.org/abs/1911.06957v1

    • [cs.SI]Large-Scale Parallel Matching of Social Network Profiles
    Alexander Panchenko, Dmitry Babaev, Sergei Obiedkov
    http://arxiv.org/abs/1911.06861v1

    • [cs.SI]Mining Unfollow Behavior in Large-Scale Online Social Networks via Spatial-Temporal Interaction
    Haozhe Wu, Zhiyuan Hu, Jia Jia, Yaohua Bu, Xiangnan He, Tat-Seng Chua
    http://arxiv.org/abs/1911.07156v1

    • [cs.SI]Towards Automated Sexual Violence Report Tracking
    Naeemul Hassan, Amrit Poudel, Jason Hale, Claire Hubacek, Khandakar Tasnim Huq, Shubhra Kanti Karmaker Santu, Syed Ishtiaque Ahmed
    http://arxiv.org/abs/1911.06961v1

    • [econ.EM]Causal Inference Under Approximate Neighborhood Interference
    Michael P. Leung
    http://arxiv.org/abs/1911.07085v1

    • [econ.EM]Inference in Models of Discrete Choice with Social Interactions Using Network Data
    Michael P. Leung
    http://arxiv.org/abs/1911.07106v1

    • [econ.EM]Semiparametric Estimation of Correlated Random Coefficient Models without Instrumental Variables
    Samuele Centorrino, Aman Ullah, Jing Xue
    http://arxiv.org/abs/1911.06857v1

    • [eess.IV]Automated Human Claustrum Segmentation using Deep Learning Technologies
    Ahmed Awad Albishri, Syed Jawad Hussain Shah, Anthony Schmiedler, Seung Suk Kang, Yugyung Lee
    http://arxiv.org/abs/1911.07515v1

    • [eess.IV]Automated fetal brain extraction from clinical Ultrasound volumes using 3D Convolutional Neural Networks
    Felipe Moser, Ruobing Huang, Aris T. Papageorghiou, Bartlomiej W. Papiez, Ana I. L. Namburete
    http://arxiv.org/abs/1911.07566v1

    • [eess.IV]Kvasir-SEG: A Segmented Polyp Dataset
    Debesh Jha, Pia H. Smedsrud, Michael A. Riegler, Pål Halvorsen, Thomas de Lange, Dag Johansen, Håvard D. Johansen
    http://arxiv.org/abs/1911.07069v1

    • [eess.IV]Liver Steatosis Segmentation with Deep Learning Methods
    Xiaoyuan Guo, Fusheng Wang, George Teodorou, Alton B. Farris, Jun Kong
    http://arxiv.org/abs/1911.07088v1

    • [eess.IV]Low-Weight and Learnable Image Denoising
    Gregory Vaksman, Michael Elad, Peyman Milanfar
    http://arxiv.org/abs/1911.07167v1

    • [eess.IV]Multi-Temporal Recurrent Neural Networks For Progressive Non-Uniform Single Image Deblurring With Incremental Temporal Training
    Dongwon Park, Dong Un Kang, Jisoo Kim, Se Young Chun
    http://arxiv.org/abs/1911.07410v1

    • [eess.IV]Multi-modal Deep Guided Filtering for Comprehensible Medical Image Processing
    Bernhard Stimpel, Christopher Syben, Franziska Schirrmacher, Philipp Hoelter, Arnd Dörfler, Andreas Maier
    http://arxiv.org/abs/1911.07731v1

    • [eess.IV]On Space-spectrum Uncertainty Analysis for Coded Aperture Systems
    Vishwanath Saragadam, Aswin Sankaranarayanan
    http://arxiv.org/abs/1911.06956v1

    • [eess.IV]Quality Assessment of DIBR-synthesized views: An Overview
    Shishun Tian, Lu Zhang, Wenbin Zou, Xia Li, Ting Su, Luce Morin, Olivier Deforges
    http://arxiv.org/abs/1911.07036v1

    • [eess.IV]ResUNet++: An Advanced Architecture for Medical Image Segmentation
    Debesh Jha, Pia H. Smedsrud, Michael A. Riegler, Dag Johansen, Thomas de Lange, Pal Halvorsen, Havard D. Johansen
    http://arxiv.org/abs/1911.07067v1

    • [eess.IV]Skin Lesion Classification Using Deep Neural Network
    Alla Eddine Guissous
    http://arxiv.org/abs/1911.07817v1

    • [eess.IV]Transfer Learning of fMRI Dynamics
    Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Zening Fu, Sergey Plis
    http://arxiv.org/abs/1911.06813v1

    • [eess.SP]A Novel Content Caching and Delivery Scheme for Millimeter Wave Device-to-Device Communications
    Theshani Nuradha, Tharaka Samarasinghe, Kasun T. Hemachandra
    http://arxiv.org/abs/1911.06517v1

    • [eess.SP]Deep Learning with Persistent Homology for Orbital Angular Momentum (OAM) Decoding
    Soheil Rostami, Walid Saad, Choong Seon Hong
    http://arxiv.org/abs/1911.06858v1

    • [eess.SP]Energy-Efficient MIMO Multiuser Systems: Nash Equilibrium Analysis
    Hang Zou, Chao Zhang, Samson Lasaulce, Lucas Saludjian, Patrick Panciatici
    http://arxiv.org/abs/1911.07687v1

    • [eess.SP]FFDNet-Based Channel Estimation for Massive MIMO Visible Light Communication Systems
    Zhipeng Gao, Yuhao Wang, Xiaodong Liu, Fuhui Zhou, Kai-Kit Wong
    http://arxiv.org/abs/1911.07404v1

    • [eess.SP]Radar Emitter Classification with Attribute-specific Recurrent Neural Networks
    Paolo Notaro, Magdalini Paschali, Carsten Hopke, David Wittmann, Nassir Navab
    http://arxiv.org/abs/1911.07683v1

    • [eess.SP]Scale- and Context-Aware Convolutional Non-intrusive Load Monitoring
    Kunjin Chen, Yu Zhang, Qin Wang, Jun Hu, Hang Fan, Jinliang He
    http://arxiv.org/abs/1911.07183v1

    • [eess.SP]Subcarrier Assignment Schemes Based on Q-Learning in Wideband Cognitive Radio Networks
    Yuan Zhou, Fuhui Zhou, Yongpeng Wu, Rose Qingyang Hu, Yuhao Wang
    http://arxiv.org/abs/1911.07149v1

    • [eess.SY]Fixed-horizon Active Hypothesis Testing
    Dhruva Kartik, Ashutosh Nayyar, Urbashi Mitra
    http://arxiv.org/abs/1911.06912v1

    • [eess.SY]General Regression Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, and Feedforward Neural Networks
    Alison Jenkins, Vinika Gupta, Mary Lenoir
    http://arxiv.org/abs/1911.07115v1

    • [eess.SY]Prescribed Performance Distance-Based Formation Control of Multi-Agent Systems (Extended Version)
    Farhad Mehdifar, Charalampos P. Bechlioulis, Farzad Hashemzadeh, Mahdi Baradarannia
    http://arxiv.org/abs/1911.07266v1

    • [eess.SY]Safe Interactive Model-Based Learning
    Marco Gallieri, Seyed Sina Mirrazavi Salehian, Nihat Engin Toklu, Alessio Quaglino, Jonathan Masci, Jan Koutník, Faustino Gomez
    http://arxiv.org/abs/1911.06556v2

    • [eess.SY]Steady-State Control and Machine Learning of Large-Scale Deformable Mirror Models
    Aleksandar Haber
    http://arxiv.org/abs/1911.07456v1

    • [math.OC]Convergence Analysis of a Momentum Algorithm with Adaptive Step Size for Non Convex Optimization
    Anas Barakat, Pascal Bianchi
    http://arxiv.org/abs/1911.07596v1

    • [math.OC]Coordinate-wise Armijo’s condition
    Tuyen Trung Truong
    http://arxiv.org/abs/1911.07820v1

    • [math.OC]Inexact Primal-Dual Gradient Projection Methods for Nonlinear Optimization on Convex Set
    Fan Zhang, Hao Wang, Jiashan Wang, Kai Yang
    http://arxiv.org/abs/1911.07758v1

    • [math.OC]Online Learning and Matching for Resource Allocation Problems
    Andrea Boskovic, Qinyi Chen, Dominik Kufel, Zijie Zhou
    http://arxiv.org/abs/1911.07409v1

    • [math.ST]Detecting structural breaks in eigensystems of functional time series
    Holger Dette, Tim Kutta
    http://arxiv.org/abs/1911.07580v1

    • [math.ST]Goodness-of-fit Testing in Linear Regression Models
    Rok Blagus, Jakob Peterlin, Janez Stare
    http://arxiv.org/abs/1911.07522v1

    • [math.ST]Graph Topological Aspects of Granger Causal Network Learning
    R. J. Kinnear, R. R. Mazumdar
    http://arxiv.org/abs/1911.07121v1

    • [math.ST]Graph estimation for Gaussian data zero-inflated by double truncation
    Gégout-Petit Anne, Gueudin-Muller Aurélie, Karmann Clémence
    http://arxiv.org/abs/1911.07694v1

    • [math.ST]Maximum Approximate Likelihood Estimation in Accelerated Failure Time Model for Interval-Censored Data
    Zhong Guan
    http://arxiv.org/abs/1911.07087v1

    • [math.ST]Oracle inequalities for image denoising with total variation regularization
    Francesco Ortelli, Sara van de Geer
    http://arxiv.org/abs/1911.07231v1

    • [quant-ph]Quantifying the unextendibility of entanglement
    Kun Wang, Xin Wang, Mark M. Wilde
    http://arxiv.org/abs/1911.07433v1

    • [quant-ph]Universal superposition codes: capacity regions of compound quantum broadcast channel with confidential messages
    Holger Boche, Gisbert Janßen, Sajad Saeedinaeeni
    http://arxiv.org/abs/1911.07753v1

    • [stat.AP]A spatio-temporal multi-scale model for Geyer saturation point process: application to forest fire occurrences
    Morteza Raeisi, Florent Bonneu, Edith Gabriel
    http://arxiv.org/abs/1911.06999v1

    • [stat.AP]Granular Motor State Monitoring of Free Living Parkinson’s Disease Patients via Deep Learning
    Kamer A. Yuksel, Jann Goschenhofer, Hridya V. Varma, Urban Fietzek, Franz M. J. Pfister
    http://arxiv.org/abs/1911.06913v1

    • [stat.AP]Predicting colorectal polyp recurrence using time-to-event analysis of medical records
    Lia X. Harrington, Jason W. Wei, Arief A. Suriawinata, Todd A. Mackenzie, Saeed Hassanpour
    http://arxiv.org/abs/1911.07368v1

    • [stat.AP]Spatiotemporal large-scale networks shaped by air mass movements
    Maria Choufany, Davide Martinetti, Rachid Senoussi, Cindy E. Morris, Samuel Soubeyrand
    http://arxiv.org/abs/1911.07007v1

    • [stat.AP]The implications of Labour’s plan to scrap Key Stage 2 tests for Progress 8 and secondary school accountability in England
    George Leckie, Lucy Prior, Harvey Goldstein
    http://arxiv.org/abs/1911.06884v1

    • [stat.CO]Bayesian Model Selection for Ultrahigh-Dimensional Doubly-Intractable Distributions with an Application to Network Psychometrics
    Jaewoo Park, Ick Hoon Jin
    http://arxiv.org/abs/1911.07142v1

    • [stat.CO]DRHotNet: An R package for detecting differential risk hotspots on a linear network
    Álvaro Briz-Redón, Francisco Martínez-Ruiz, Francisco Montes
    http://arxiv.org/abs/1911.07827v1

    • [stat.ME]A Bootstrap-based Inference Framework for Testing Similarity of Paired Networks
    Somnath Bhadra, Kaustav Chakraborty, Srijan Sengupta, Soumendra Lahiri
    http://arxiv.org/abs/1911.06869v1

    • [stat.ME]A Permutation Test for Assessing the Presence of Individual Differences in Treatment Effects
    Chi Chang, Thomas Jaki, Muhammad Saad Sadiq, Alena A. Kuhlemeier, Daniel Feaster, Nathan Cole, Andrea Lamont, Daniel Oberski, Yasin Desai, M. Lee Van Horn
    http://arxiv.org/abs/1911.07248v1

    • [stat.ME]A hierarchical expected improvement method for Bayesian optimization
    Zhehui Chen, Simon Mak, C. F. Jeff Wu
    http://arxiv.org/abs/1911.07285v1

    • [stat.ME]A projection approach for multiple monotone regression
    Lizhen Lin, Brian St. Thomas, Walter W. Piegorsch, James Scott, Carlos Carvalho
    http://arxiv.org/abs/1911.07553v1

    • [stat.ME]Bayesian Ordinal Quantile Regression with a Partially Collapsed Gibbs Sampler
    Isabella N Grabski, Roberta De Vito, Barbara E Engelhardt
    http://arxiv.org/abs/1911.07099v1

    • [stat.ME]Causal inference with recurrent data via inverse probability treatment weighting method (IPTW)
    Haodi Liang, Cecilia Cotton
    http://arxiv.org/abs/1911.06868v1

    • [stat.ME]Change point localization in dependent dynamic nonparametric random dot product graphs
    Oscar Hernan Madrid Padilla, Yi Yu, Carey E. Priebe
    http://arxiv.org/abs/1911.07494v1

    • [stat.ME]Constrained High Dimensional Statistical Inference
    Ming Yu, Varun Gupta, Mladen Kolar
    http://arxiv.org/abs/1911.07319v1

    • [stat.ME]Does Regression Approximate the Influence of the Covariates or Just Measurement Errors? A Model Validity Test
    Alexander Kukush, Igor Mandel
    http://arxiv.org/abs/1911.07556v1

    • [stat.ME]Marginal and Interactive Feature Screening of Ultra-high Dimensional Feature Spaces with Multivariate Response
    Randall Reese
    http://arxiv.org/abs/1911.06955v1

    • [stat.ME]Online Change-Point Detection in High-Dimensional Covariance Structure with Application to Dynamic Networks
    Lingjun Li, Jun Li
    http://arxiv.org/abs/1911.07762v1

    • [stat.ME]Partial Least Squares for Functional Joint Models
    Yue Wang, Joseph Ibrahim, Hongtu Zhu
    http://arxiv.org/abs/1911.07111v1

    • [stat.ME]State Space Emulation and Annealed Sequential Monte Carlo for High Dimensional Optimization
    Chencheng Cai, Rong Chen
    http://arxiv.org/abs/1911.07172v1

    • [stat.ME]Testing for Stochastic Order in Interval-Valued Data
    Hyejeong Choi, Johan Lim, Johan Lim, Seongoh Park
    http://arxiv.org/abs/1911.07196v1

    • [stat.ME]Variance partitioning in multilevel models for count data
    George Leckie, William Browne, Harvey Goldstein, Juan Merlo, Peter Austin
    http://arxiv.org/abs/1911.06888v1

    • [stat.ME]Wavelet-Based Moment-Matching Techniques for Inertial Sensor Calibration
    Stéphane Guerrier, Juan Jurado, Mehran Khaghani, Gaetan Bakalli, Mucyo Karemera, Roberto Molinari, Samuel Orso, John Raquet, Christine M. Schubert Kabban, Jan Skaloud, Haotian Xu, Yuming Zhang
    http://arxiv.org/abs/1911.07049v1

    • [stat.ML]A Simple Heuristic for Bayesian Optimization with A Low Budget
    Masahiro Nomura, Kenshi Abe
    http://arxiv.org/abs/1911.07790v1

    • [stat.ML]Benchmarking time series classification — Functional data vs machine learning approaches
    Florian Pfisterer, Laura Beggel, Xudong Sun, Fabian Scheipl, Bernd Bischl
    http://arxiv.org/abs/1911.07511v1

    • [stat.ML]Defending Against Model Stealing Attacks with Adaptive Misinformation
    Sanjay Kariyappa, Moinuddin K Qureshi
    http://arxiv.org/abs/1911.07100v1

    • [stat.ML]Iterative Construction of Gaussian Process Surrogate Models for Bayesian Inference
    Leen Alawieh, Jonathan Goodman, John B. Bell
    http://arxiv.org/abs/1911.07227v1

    • [stat.ML]Learning with Good Feature Representations in Bandits and in RL with a Generative Model
    Tor Lattimore, Csaba Szepesvari
    http://arxiv.org/abs/1911.07676v1

    • [stat.ML]Stochastic Gradient Annealed Importance Sampling for Efficient Online Marginal Likelihood Estimation
    Scott A. Cameron, Hans C. Eggers, Steve Kroon
    http://arxiv.org/abs/1911.07337v1