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.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 cs.GR - 计算机图形学 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.MA - 多代理系统 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.AG - 代数几何 math.PR - 概率 math.ST - 统计理论 physics.app-ph - 应用物理 physics.soc-ph - 物理学与社会 q-bio.NC - 神经元与认知 q-fin.ST - 统计金融学 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [astro-ph.IM]Solar Image Restoration with the Cycle-GAN Based on Multi-Fractal Properties of Texture Features
    • [cs.AI]A Distributed Approach to LARS Stream Reasoning (System paper)
    • [cs.AI]A Syntactic Operator for Forgetting that Satisfies Strong Persistence
    • [cs.AI]A difficulty ranking approach to personalization in E-learning
    • [cs.AI]Learning to design from humans: Imitating human designers through deep learning
    • [cs.AI]Precomputing Datalog evaluation plans in large-scale scenarios
    • [cs.AI]Towards Model-based Reinforcement Learning for Industry-near Environments
    • [cs.AI]Towards Optimizing Reiter’s HS-Tree for Sequential Diagnosis
    • [cs.AI]von Neumann-Morgenstern and Savage Theorems for Causal Decision Making
    • [cs.CL]A Baseline Neural Machine Translation System for Indian Languages
    • [cs.CL]A Hybrid Neural Network Model for Commonsense Reasoning
    • [cs.CL]A Mathematical Model for Linguistic Universals
    • [cs.CL]Analyzing Linguistic Complexity and Scientific Impact
    • [cs.CL]Automatically Learning Construction Injury Precursors from Text
    • [cs.CL]CAiRE: An End-to-End Empathetic Chatbot
    • [cs.CL]ERNIE 2.0: A Continual Pre-training Framework for Language Understanding
    • [cs.CL]Hierarchical Multi-Label Dialog Act Recognition on Spanish Data
    • [cs.CL]Hybrid Code Networks using a convolutional neural network as an input layer achieves higher turn accuracy
    • [cs.CL]Is BERT Really Robust? Natural Language Attack on Text Classification and Entailment
    • [cs.CL]Joey NMT: A Minimalist NMT Toolkit for Novices
    • [cs.CL]Legal entity recognition in an agglutinating language and document connection network for EU Legislation and EU/Hungarian Case Law
    • [cs.CL]Leveraging Pre-trained Checkpoints for Sequence Generation Tasks
    • [cs.CL]Nefnir: A high accuracy lemmatizer for Icelandic
    • [cs.CL]Neural Mention Detection
    • [cs.CL]Representation Degeneration Problem in Training Natural Language Generation Models
    • [cs.CL]Supervised and unsupervised neural approaches to text readability
    • [cs.CL]Towards Effective Rebuttal: Listening Comprehension using Corpus-Wide Claim Mining
    • [cs.CL]VIANA: Visual Interactive Annotation of Argumentation
    • [cs.CL]What Should I Ask? Using Conversationally Informative Rewards for Goal-Oriented Visual Dialog
    • [cs.CV]A Benchmark on Tricks for Large-scale Image Retrieval
    • [cs.CV]A Fine-Grain Error Map Prediction and Segmentation Quality Assessment Framework for Whole-Heart Segmentation
    • [cs.CV]AirFace:Lightweight and Efficient Model for Face Recognition
    • [cs.CV]An Empirical Study on Leveraging Scene Graphs for Visual Question Answering
    • [cs.CV]Attribute Aware Pooling for Pedestrian Attribute Recognition
    • [cs.CV]Attribute-Guided Deep Polarimetric Thermal-to-visible Face Recognition
    • [cs.CV]Automatic Registration between Cone-Beam CT and Scanned Surface via Deep-Pose Regression Neural Networks and Clustered Similarities
    • [cs.CV]Automatic Text Line Segmentation Directly in JPEG Compressed Document Images
    • [cs.CV]Benefiting from Multitask Learning to Improve Single Image Super-Resolution
    • [cs.CV]ChaLearn Looking at People: IsoGD and ConGD Large-scale RGB-D Gesture Recognition
    • [cs.CV]Consensus Feature Network for Scene Parsing
    • [cs.CV]Context Model for Pedestrian Intention Prediction using Factored Latent-Dynamic Conditional Random Fields
    • [cs.CV]DAR-Net: Dynamic Aggregation Network for Semantic Scene Segmentation
    • [cs.CV]Dilated Point Convolutions: On the Receptive Field of Point Convolutions
    • [cs.CV]End-to-End Learning Deep CRF models for Multi-Object Tracking
    • [cs.CV]Enforcing geometric constraints of virtual normal for depth prediction
    • [cs.CV]FSS-1000: A 1000-Class Dataset for Few-Shot Segmentation
    • [cs.CV]Fairest of Them All: Establishing a Strong Baseline for Cross-Domain Person ReID
    • [cs.CV]Forced Spatial Attention for Driver Foot Activity Classification
    • [cs.CV]Genetic Deep Learning for Lung Cancer Screening
    • [cs.CV]Goal-Driven Sequential Data Abstraction
    • [cs.CV]Grape detection, segmentation and tracking using deep neural networks and three-dimensional association
    • [cs.CV]Hybrid-Attention based Decoupled Metric Learning for Zero-Shot Image Retrieval
    • [cs.CV]Interlaced Sparse Self-Attention for Semantic Segmentation
    • [cs.CV]Iris Recognition for Personal Identification using LAMSTAR neural network
    • [cs.CV]It’s All About The Scale — Efficient Text Detection Using Adaptive Scaling
    • [cs.CV]KNEEL: Knee Anatomical Landmark Localization Using Hourglass Networks
    • [cs.CV]Learn to Scale: Generating Multipolar Normalized Density Map for Crowd Counting
    • [cs.CV]Learning Body Shape and Pose from Dense Correspondences
    • [cs.CV]Learning Instance-wise Sparsity for Accelerating Deep Models
    • [cs.CV]Learning Wear Patterns on Footwear Outsoles Using Convolutional Neural Networks
    • [cs.CV]MaskGAN: Towards Diverse and Interactive Facial Image Manipulation
    • [cs.CV]Meta Learning for Task-Driven Video Summarization
    • [cs.CV]Multi-Granularity Fusion Network for Proposal and Activity Localization: Submission to ActivityNet Challenge 2019 Task 1 and Task 2
    • [cs.CV]Multi-Task Attention-Based Semi-Supervised Learning for Medical Image Segmentation
    • [cs.CV]On the Realization and Analysis of Circular Harmonic Transforms for Feature Detection
    • [cs.CV]Optical Flow for Intermediate Frame Interpolation of Multispectral Geostationary Satellite Data
    • [cs.CV]Pick-and-Learn: Automatic Quality Evaluation for Noisy-Labeled Image Segmentation
    • [cs.CV]Quadtree Generating Networks: Efficient Hierarchical Scene Parsing with Sparse Convolutions
    • [cs.CV]ROAM: Recurrently Optimizing Tracking Model
    • [cs.CV]Real-time Tracking-by-Detection of Human Motion in RGB-D Camera Networks
    • [cs.CV]Recursive Cascaded Networks for Unsupervised Medical Image Registration
    • [cs.CV]Regularizing Proxies with Multi-Adversarial Training for Unsupervised Domain-Adaptive Semantic Segmentation
    • [cs.CV]Reprojection R-CNN: A Fast and Accurate Object Detector for 360° Images
    • [cs.CV]Rethinking Classification and Localization for Cascade R-CNN
    • [cs.CV]Salient Slices: Improved Neural Network Training and Performance with Image Entropy
    • [cs.CV]Seeing Things in Random-Dot Videos
    • [cs.CV]Segmenting Hyperspectral Images Using Spectral-Spatial Convolutional Neural Networks With Training-Time Data Augmentation
    • [cs.CV]Self-Supervised Learning for Stereo Reconstruction on Aerial Images
    • [cs.CV]Semantic Guided Single Image Reflection Removal
    • [cs.CV]Silhouette Guided Point Cloud Reconstruction beyond Occlusion
    • [cs.CV]Specular- and Diffuse-reflection-based Face Liveness Detection for Mobile Devices
    • [cs.CV]Tell Me What to Track
    • [cs.CV]To Learn or Not to Learn: Analyzing the Role of Learning for Navigation in Virtual Environments
    • [cs.CV]Towards Automatic Screening of Typical and Atypical Behaviors in Children With Autism
    • [cs.CV]Triangulation: Why Optimize?
    • [cs.CV]V-PROM: A Benchmark for Visual Reasoning Using Visual Progressive Matrices
    • [cs.CV]VITAL: A Visual Interpretation on Text with Adversarial Learning for Image Labeling
    • [cs.CV]X-LineNet: Detecting Aircraft in Remote Sensing Images by a pair of Intersecting Line Segments
    • [cs.CY]Artificial Intelligence and the Future of Psychiatry: Insights from a Global Physician Survey
    • [cs.CY]Estimating Parameters in Mathematical Model for Societal Booms through Bayesian Inference Approach
    • [cs.CY]Micro-accounting for optimizing and saving energy in smart buildings
    • [cs.CY]Modelling the Safety and Surveillance of the AI Race
    • [cs.CY]Reducing malicious use of synthetic media research: Considerations and potential release practices for machine learning
    • [cs.CY]The Challenges of Investigating Cryptocurrencies and Blockchain Related Crime
    • [cs.DB]sql4ml A declarative end-to-end workflow for machine learning
    • [cs.DC]Decentralized utility- and locality-aware replication for heterogeneous DHT-based P2P cloud storage systems
    • [cs.DC]Distributed Approximation Algorithms for Steiner Tree in the $\mathcal{CONGESTED}$ $\mathcal{CLIQUE}$
    • [cs.DC]Faster asynchronous MST and low diameter tree construction with sublinear communication
    • [cs.DC]Geospatial Big Data Handling with High Performance Computing: Current Approaches and Future Directions
    • [cs.DC]On Observability and Monitoring of Distributed Systems: An Industry Interview Study
    • [cs.DC]Research Computing at a Business University
    • [cs.DC]Small Profits and Quick Returns: An Incentive Mechanism Design for IoT-based Crowdsourcing under Continuous Platform Competition
    • [cs.DC]Spartan: Sparse Robust Addressable Networks
    • [cs.DC]Staged deployment of interactive multi-application HPC workflows
    • [cs.DC]Temporal Data Fusion at the Edge
    • [cs.DS]Distributed Dense Subgraph Detection and Low Outdegree Orientation
    • [cs.DS]Low-Rank Matrix Completion: A Contemporary Survey
    • [cs.GR]Self-Imitation Learning of Locomotion Movements through Termination Curriculum
    • [cs.HC]Augmented Reality Applied to LEGO Construction: AR-based Building Instructions with High Accuracy & Precision and Realistic Object-Hand Occlusions
    • [cs.HC]Multivariate Pointwise Information-Driven Data Sampling and Visualization
    • [cs.HC]Personality is Revealed During Weekends: Towards Data Minimisation for Smartphone Based Personality Classification
    • [cs.HC]Towards Understanding and Modeling Empathy for Use in Motivational Design Thinking
    • [cs.IR]Deep Cross-Modal Hashing with Hashing Functions and Unified Hash Codes Jointly Learning
    • [cs.IR]On the Value of Bandit Feedback for Offline Recommender System Evaluation
    • [cs.IR]Style Conditioned Recommendations
    • [cs.IT]A Greedy Algorithm for Matrix Recovery with Subspace Prior Information
    • [cs.IT]Diffusion Hypercontractivity via Generalized Density Manifold
    • [cs.IT]Energy-Efficient Processing and Robust Wireless Cooperative Transmission for Edge Inference
    • [cs.IT]Finite-Precision Implementation of Arithmetic Coding Based Distribution Matchers
    • [cs.IT]Hulls of Linear Codes Revisited with Applications
    • [cs.IT]Linear reconstructions and the analysis of the stable sampling rate
    • [cs.IT]Monomial-Cartesian codes and their duals, with applications to LCD codes, quantum codes, and locally recoverable codes
    • [cs.IT]Necessities and sufficiencies of a class of permutation polynomials over finite fields
    • [cs.IT]On the Probability of Partial Decoding in Sparse Network Coding
    • [cs.LG]A Deep Learning Based Attack for The Chaos-based Image Encryption
    • [cs.LG]A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment
    • [cs.LG]Action Grammars: A Cognitive Model for Learning Temporal Abstractions
    • [cs.LG]AiAds: Automated and Intelligent Advertising System for Sponsored Search
    • [cs.LG]An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing
    • [cs.LG]Are Odds Really Odd? Bypassing Statistical Detection of Adversarial Examples
    • [cs.LG]Bandit Convex Optimization in Non-stationary Environments
    • [cs.LG]Bandits with Feedback Graphs and Switching Costs
    • [cs.LG]Blocking Bandits
    • [cs.LG]Charting the Right Manifold: Manifold Mixup for Few-shot Learning
    • [cs.LG]CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting
    • [cs.LG]Computing the Value of Data: Towards Applied Data Minimalism
    • [cs.LG]DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation
    • [cs.LG]Deep Reinforcement Learning for Personalized Search Story Recommendation
    • [cs.LG]DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks
    • [cs.LG]Discovering Association with Copula Entropy
    • [cs.LG]FDive: Learning Relevance Models using Pattern-based Similarity Measures
    • [cs.LG]Generative Adversarial Network for Handwritten Text
    • [cs.LG]Hidden Covariate Shift: A Minimal Assumption For Domain Adaptation
    • [cs.LG]Hindsight Trust Region Policy Optimization
    • [cs.LG]Learnable Parameter Similarity
    • [cs.LG]Learning Invariant Representations for Sentiment Analysis: The Missing Material is Datasets
    • [cs.LG]Learning Task Specifications from Demonstrations via the Principle of Maximum Causal Entropy
    • [cs.LG]Learning and Interpreting Potentials for Classical Hamiltonian Systems
    • [cs.LG]Many could be better than all: A novel instance-oriented algorithm for Multi-modal Multi-label problem
    • [cs.LG]Mindful Active Learning
    • [cs.LG]Modeling Winner-Take-All Competition in Sparse Binary Projections
    • [cs.LG]Multi-modal Predictive Models of Diabetes Progression
    • [cs.LG]Multi-task Self-Supervised Learning for Human Activity Detection
    • [cs.LG]On Hard Exploration for Reinforcement Learning: a Case Study in Pommerman
    • [cs.LG]Probabilistic Models of Relational Implication
    • [cs.LG]Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization
    • [cs.LG]REP: Predicting the Time-Course of Drug Sensitivity
    • [cs.LG]RNNbow: Visualizing Learning via Backpropagation Gradients in Recurrent Neural Networks
    • [cs.LG]Scalable Dictionary Classifiers for Time Series Classification
    • [cs.LG]Tackling Multiple Ordinal Regression Problems: Sparse and Deep Multi-Task Learning Approaches
    • [cs.LG]Uncertainty in Model-Agnostic Meta-Learning using Variational Inference
    • [cs.LG]Understanding Adversarial Robustness: The Trade-off between Minimum and Average Margin
    • [cs.LO]Strengthening Gossip Protocols using Protocol-Dependent Knowledge
    • [cs.MA]G-flocking: Flocking Model Optimization based on Genetic Framework
    • [cs.NE]Autoencoding with a Learning Classifier System: Initial Results
    • [cs.NE]On the Limitations of the Univariate Marginal Distribution Algorithm to Deception and Where Bivariate EDAs might help
    • [cs.NE]SOM-Guided Evolutionary Search for Solving MinMax Multiple-TSP
    • [cs.NI]Deep Learning for CSI Feedback Based on Superimposed Coding
    • [cs.NI]Q-MIND: Defeating Stealthy DoS Attacks in SDN with a Machine-learning based Defense Framework
    • [cs.RO]Environment Probing Interaction Policies
    • [cs.RO]Jerk Control of Floating Base Systems with Contact-Stable Parametrised Force Feedback
    • [cs.RO]Real-Time 3D Profiling with RGB-D Mapping in Pipelines Using Stereo Camera Vision and Structured IR Laser Ring
    • [cs.RO]Solving the Robot-World Hand-Eye(s) Calibration Problem with Iterative Methods
    • [cs.SD]StarGAN-VC2: Rethinking Conditional Methods for StarGAN-Based Voice Conversion
    • [cs.SE]Characterizing and Understanding Software Developer Networks in Security Development
    • [cs.SE]Scalable Source Code Similarity Detection in Large Code Repositories
    • [cs.SI]DynWalks: Global Topology and Recent Changes Awareness Dynamic Network Embedding
    • [cs.SI]Fusing location and text features for sentiment classification
    • [cs.SI]Nonuniform Timeslicing of Dynamic Graphs Based on Visual Complexity
    • [cs.SI]Unlocking Analytical Value from Social Media and User Generated Content
    • [eess.IV]A Two Stage GAN for High Resolution Retinal Image Generation and Segmentation
    • [eess.IV]Automated Lesion Detection by Regressing Intensity-Based Distance with a Neural Network
    • [eess.IV]Blind Deblurring Using GANs
    • [eess.IV]Deep learning-based prediction of kinetic parameters from myocardial perfusion MRI
    • [eess.IV]FocusNet: Imbalanced Large and Small Organ Segmentation with an End-to-End Deep Neural Network for Head and Neck CT Images
    • [eess.IV]Momentum-Net: Fast and convergent iterative neural network for inverse problems
    • [eess.IV]Remote Heart Rate Measurement from Highly Compressed Facial Videos: an End-to-end Deep Learning Solution with Video Enhancement
    • [eess.IV]Two-Stream CNN with Loose Pair Training for Multi-modal AMD Categorization
    • [eess.SP]Two Efficient Beamformers for Secure Precise Jamming and Communication with Phase Alignment
    • [eess.SP]Weighted Spectral Efficiency Optimization for Hybrid Beamforming in Multiuser Massive MIMO-OFDM Systems
    • [math.AG]On local real algebraic geometry and applications to kinematics
    • [math.PR]Reinforcement with Fading Memories
    • [math.ST]A Higher-Order Swiss Army Infinitesimal Jackknife
    • [math.ST]A Theoretical Case Study of Structured Variational Inference for Community Detection
    • [math.ST]Approximating the Span of Principal Components via Iterative Least-Squares
    • [math.ST]Estimating the Random Effect in Big Data Mixed Models
    • [math.ST]Principal components of spiked covariance matrices in the supercritical regime
    • [math.ST]Subsampling Sparse Graphons Under Minimal Assumptions
    • [physics.app-ph]Lotka-Volterra competition mechanism embedded in a decision-making method
    • [physics.soc-ph]Beyond the Coverage of Information Spreading: Analytical and Empirical Evidence of Re-exposure in Large-scale Online Social Networks
    • [physics.soc-ph]Fitting In and Breaking Up: A Nonlinear Version of Coevolving Voter Models
    • [q-bio.NC]Effective and efficient ROI-wise visual encoding using an end-to-end CNN regression model and selective optimization
    • [q-bio.NC]Modulation of early visual processing alleviates capacity limits \in solving multiple tasks
    • [q-bio.NC]Spatiotemporal Information Processing with a Reservoir Decision-making Network
    • [q-fin.ST]Investigating the effect of competitiveness power in estimating the average weighted price in electricity market
    • [stat.AP]A Bayesian nonparametric approach to the approximation of the global stable manifold
    • [stat.AP]A Particle Filter for Stochastic Advection by Lie Transport (SALT): A case study for the damped and forced incompressible 2D Euler equation
    • [stat.AP]Modellvalidierung mit Hilfe von Quantil-Quantil-Plots unter Solvency II (Model validation on the basis of quantile-quantile-plots under Solvency II)
    • [stat.CO]Adaptive spline fitting with particle swarm optimization
    • [stat.CO]The Wang-Landau Algorithm as Stochastic Optimization and its Acceleration
    • [stat.ME]A Matrix—free Likelihood Method for Exploratory Factor Analysis of High-dimensional Gaussian Data
    • [stat.ME]Max-and-Smooth: a two-step approach for approximate Bayesian inference in latent Gaussian models
    • [stat.ME]Mitigating unobserved spatial confounding bias with mixed models
    • [stat.ME]Modelling spine locations on dendrite trees using inhomogeneous Cox point processes
    • [stat.ME]Multiply Robust Learning of the Average Treatment Effect with an Invalid Instrumental Variable
    • [stat.ME]Spatial Process Decomposition for Quantitative Imaging Biomarkers Using Multiple Images of Varying Shapes
    • [stat.ML]A Strategy for Adaptive Sampling of Multi-fidelity Gaussian Process to Reduce Predictive Uncertainty
    • [stat.ML]A neural network with feature sparsity
    • [stat.ML]Bayesian Robustness: A Nonasymptotic Viewpoint
    • [stat.ML]Bias of Homotopic Gradient Descent for the Hinge Loss
    • [stat.ML]Memory- and Communication-Aware Model Compression for Distributed Deep Learning Inference on IoT
    • [stat.ML]Multi-Rank Sparse and Functional PCA: Manifold Optimization and Iterative Deflation Techniques
    • [stat.ML]Variational f-divergence Minimization
    • [stat.ML]Wasserstein Fair Classification

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

    • [astro-ph.IM]Solar Image Restoration with the Cycle-GAN Based on Multi-Fractal Properties of Texture Features
    Peng Jia, Yi Huang, Bojun Cai, Dongmei Cai
    http://arxiv.org/abs/1907.12192v1

    • [cs.AI]A Distributed Approach to LARS Stream Reasoning (System paper)
    Thomas Eiter, Paul Ogris, Konstantin Schekotihin
    http://arxiv.org/abs/1907.12344v1

    • [cs.AI]A Syntactic Operator for Forgetting that Satisfies Strong Persistence
    Matti Berthold, Ricardo Gonçalves, Matthias Knorr, João Leite
    http://arxiv.org/abs/1907.12501v1

    • [cs.AI]A difficulty ranking approach to personalization in E-learning
    Avi Segal, Kobi Gal, Guy Shani, Bracha Shapira
    http://arxiv.org/abs/1907.12047v1

    • [cs.AI]Learning to design from humans: Imitating human designers through deep learning
    Ayush Raina, Christopher McComb, Jonathan Cagan
    http://arxiv.org/abs/1907.11813v1

    • [cs.AI]Precomputing Datalog evaluation plans in large-scale scenarios
    Alessio Fiorentino, Nicola Leone, Marco Manna, Simona Perri, Jessica Zangari
    http://arxiv.org/abs/1907.12495v1

    • [cs.AI]Towards Model-based Reinforcement Learning for Industry-near Environments
    Per-Arne Andersen, Morten Goodwin, Ole-Christoffer Granmo
    http://arxiv.org/abs/1907.11971v1

    • [cs.AI]Towards Optimizing Reiter’s HS-Tree for Sequential Diagnosis
    Patrick Rodler
    http://arxiv.org/abs/1907.12130v1

    • [cs.AI]von Neumann-Morgenstern and Savage Theorems for Causal Decision Making
    Mauricio Gonzalez-Soto, Luis E. Sucar, Hugo J. Escalante
    http://arxiv.org/abs/1907.11752v1

    • [cs.CL]A Baseline Neural Machine Translation System for Indian Languages
    Jerin Philip, Vinay P. Namboodiri, C. V. Jawahar
    http://arxiv.org/abs/1907.12437v1

    • [cs.CL]A Hybrid Neural Network Model for Commonsense Reasoning
    Pengcheng He, Xiaodong Liu, Weizhu Chen, Jianfeng Gao
    http://arxiv.org/abs/1907.11983v1

    • [cs.CL]A Mathematical Model for Linguistic Universals
    Weinan E, Yajun Zhou
    http://arxiv.org/abs/1907.12293v1

    • [cs.CL]Analyzing Linguistic Complexity and Scientific Impact
    Chao Lu, Yi Bu, Xianlei Dong, Jie Wang, Ying Ding, Vincent Larivière, Cassidy R. Sugimoto, Logan Paul, Chengzhi Zhang
    http://arxiv.org/abs/1907.11843v1

    • [cs.CL]Automatically Learning Construction Injury Precursors from Text
    Henrietta Baker, Matthew R. Hallowell, Antoine J. -P. Tixier
    http://arxiv.org/abs/1907.11769v1

    • [cs.CL]CAiRE: An End-to-End Empathetic Chatbot
    Zhaojiang Lin, Peng Xu, Genta Indra Winata, Zihan Liu, Pascale Fung
    http://arxiv.org/abs/1907.12108v1

    • [cs.CL]ERNIE 2.0: A Continual Pre-training Framework for Language Understanding
    Yu Sun, Shuohuan Wang, Yukun Li, Shikun Feng, Hao Tian, Hua Wu, Haifeng Wang
    http://arxiv.org/abs/1907.12412v1

    • [cs.CL]Hierarchical Multi-Label Dialog Act Recognition on Spanish Data
    Eugénio Ribeiro, Ricardo Ribeiro, David Martins de Matos
    http://arxiv.org/abs/1907.12316v1

    • [cs.CL]Hybrid Code Networks using a convolutional neural network as an input layer achieves higher turn accuracy
    Petr Marek
    http://arxiv.org/abs/1907.12162v1

    • [cs.CL]Is BERT Really Robust? Natural Language Attack on Text Classification and Entailment
    Di Jin, Zhijing Jin, Joey Tianyi Zhou, Peter Szolovits
    http://arxiv.org/abs/1907.11932v1

    • [cs.CL]Joey NMT: A Minimalist NMT Toolkit for Novices
    Julia Kreutzer, Joost Bastings, Stefan Riezler
    http://arxiv.org/abs/1907.12484v1

    • [cs.CL]Legal entity recognition in an agglutinating language and document connection network for EU Legislation and EU/Hungarian Case Law
    György Görög, Péter Weisz
    http://arxiv.org/abs/1907.12280v1

    • [cs.CL]Leveraging Pre-trained Checkpoints for Sequence Generation Tasks
    Sascha Rothe, Shashi Narayan, Aliaksei Severyn
    http://arxiv.org/abs/1907.12461v1

    • [cs.CL]Nefnir: A high accuracy lemmatizer for Icelandic
    Svanhvít Lilja Ingólfsdóttir, Hrafn Loftsson, Jón Friðrik Daðason, Kristín Bjarnadóttir
    http://arxiv.org/abs/1907.11907v1

    • [cs.CL]Neural Mention Detection
    Juntao Yu, Bernd Bohnet, Massimo Poesio
    http://arxiv.org/abs/1907.12524v1

    • [cs.CL]Representation Degeneration Problem in Training Natural Language Generation Models
    Jun Gao, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu
    http://arxiv.org/abs/1907.12009v1

    • [cs.CL]Supervised and unsupervised neural approaches to text readability
    Matej Martinc, Senja Pollak, Marko Robnik Šikonja
    http://arxiv.org/abs/1907.11779v1

    • [cs.CL]Towards Effective Rebuttal: Listening Comprehension using Corpus-Wide Claim Mining
    Tamar Lavee, Matan Orbach, Lili Kotlerman, Yoav Kantor, Shai Gretz, Lena Dankin, Shachar Mirkin, Michal Jacovi, Yonatan Bilu, Ranit Aharonov, Noam Slonim
    http://arxiv.org/abs/1907.11889v1

    • [cs.CL]VIANA: Visual Interactive Annotation of Argumentation
    Fabian Sperrle, Rita Sevastjanova, Rebecca Kehlbeck, Mennatallah El-Assady
    http://arxiv.org/abs/1907.12413v1

    • [cs.CL]What Should I Ask? Using Conversationally Informative Rewards for Goal-Oriented Visual Dialog
    Pushkar Shukla, Carlos Elmadjian, Richika Sharan, Vivek Kulkarni, Matthew Turk, William Yang Wang
    http://arxiv.org/abs/1907.12021v1

    • [cs.CV]A Benchmark on Tricks for Large-scale Image Retrieval
    ByungSoo Ko, Minchul Shin, Geonmo Gu, HeeJae Jun, Tae Kwan Lee, Youngjoon Kim
    http://arxiv.org/abs/1907.11854v1

    • [cs.CV]A Fine-Grain Error Map Prediction and Segmentation Quality Assessment Framework for Whole-Heart Segmentation
    Rongzhao Zhang, Albert C. S. Chung
    http://arxiv.org/abs/1907.12244v1

    • [cs.CV]AirFace:Lightweight and Efficient Model for Face Recognition
    Xianyang Li
    http://arxiv.org/abs/1907.12256v1

    • [cs.CV]An Empirical Study on Leveraging Scene Graphs for Visual Question Answering
    Cheng Zhang, Wei-Lun Chao, Dong Xuan
    http://arxiv.org/abs/1907.12133v1

    • [cs.CV]Attribute Aware Pooling for Pedestrian Attribute Recognition
    Kai Han, Yunhe Wang, Han Shu, Chuanjian Liu, Chunjing Xu, Chang Xu
    http://arxiv.org/abs/1907.11837v1

    • [cs.CV]Attribute-Guided Deep Polarimetric Thermal-to-visible Face Recognition
    Seyed Mehdi Iranmanesh, Nasser M. Nasrabadi
    http://arxiv.org/abs/1907.11980v1

    • [cs.CV]Automatic Registration between Cone-Beam CT and Scanned Surface via Deep-Pose Regression Neural Networks and Clustered Similarities
    Minyoung Chung, Jingyu Lee, Wisoo Song, Youngchan Song, Il-Hyung Yang, Jeongjin Lee, Yeong-Gil Shin
    http://arxiv.org/abs/1907.12250v1

    • [cs.CV]Automatic Text Line Segmentation Directly in JPEG Compressed Document Images
    Bulla Rajesh, Mohammed Javed, P Nagabhushan
    http://arxiv.org/abs/1907.12219v1

    • [cs.CV]Benefiting from Multitask Learning to Improve Single Image Super-Resolution
    Mohammad Saeed Rad, Behzad Bozorgtabar, Claudiu Musat, Urs-Viktor Marti, Max Basler, Hazim Kemal Ekenel, Jean-Philippe Thiran
    http://arxiv.org/abs/1907.12488v1

    • [cs.CV]ChaLearn Looking at People: IsoGD and ConGD Large-scale RGB-D Gesture Recognition
    Jun Wan, Chi Lin, Longyin Wen, Yunan Li, Qiguang Miao, Sergio Escalera, Gholamreza Anbarjafari, Isabelle Guyon, Guodong Guo, Stan Z. Li
    http://arxiv.org/abs/1907.12193v1

    • [cs.CV]Consensus Feature Network for Scene Parsing
    Tianyi Wu, Sheng Tang, Rui Zhang, Guodong Guo, Yongdong Zhang
    http://arxiv.org/abs/1907.12411v1

    • [cs.CV]Context Model for Pedestrian Intention Prediction using Factored Latent-Dynamic Conditional Random Fields
    Satyajit Neogi, Michael Hoy, Kang Dang, Hang Yu, Justin Dauwels
    http://arxiv.org/abs/1907.11881v1

    • [cs.CV]DAR-Net: Dynamic Aggregation Network for Semantic Scene Segmentation
    Zongyue Zhao, Min Liu, Karthik Ramani
    http://arxiv.org/abs/1907.12022v1

    • [cs.CV]Dilated Point Convolutions: On the Receptive Field of Point Convolutions
    Francis Engelmann, Theodora Kontogianni, Bastian Leibe
    http://arxiv.org/abs/1907.12046v1

    • [cs.CV]End-to-End Learning Deep CRF models for Multi-Object Tracking
    Jun Xiang, Ma Chao, Guohan Xu, Jianhua Hou
    http://arxiv.org/abs/1907.12176v1

    • [cs.CV]Enforcing geometric constraints of virtual normal for depth prediction
    Yin Wei, Yifan Liu, Chunhua Shen, Youliang Yan
    http://arxiv.org/abs/1907.12209v1

    • [cs.CV]FSS-1000: A 1000-Class Dataset for Few-Shot Segmentation
    Tianhan Wei, Xiang Li, Yau Pun Chen, Yu-Wing Tai, Chi-Keung Tang
    http://arxiv.org/abs/1907.12347v1

    • [cs.CV]Fairest of Them All: Establishing a Strong Baseline for Cross-Domain Person ReID
    Devinder Kumar, Parthipan Siva, Paul Marchwica, Alexander Wong
    http://arxiv.org/abs/1907.12016v1

    • [cs.CV]Forced Spatial Attention for Driver Foot Activity Classification
    Akshay Rangesh, Mohan M. Trivedi
    http://arxiv.org/abs/1907.11824v1

    • [cs.CV]Genetic Deep Learning for Lung Cancer Screening
    Hunter Park, Connor Monahan
    http://arxiv.org/abs/1907.11849v1

    • [cs.CV]Goal-Driven Sequential Data Abstraction
    Umar Riaz Muhammad, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song
    http://arxiv.org/abs/1907.12336v1

    • [cs.CV]Grape detection, segmentation and tracking using deep neural networks and three-dimensional association
    Thiago T. Santos, Leonardo L. de Souza, Andreza A. dos Santos, Sandra Avila
    http://arxiv.org/abs/1907.11819v1

    • [cs.CV]Hybrid-Attention based Decoupled Metric Learning for Zero-Shot Image Retrieval
    Binghui Chen, Weihong Deng
    http://arxiv.org/abs/1907.11832v1

    • [cs.CV]Interlaced Sparse Self-Attention for Semantic Segmentation
    Lang Huang, Yuhui Yuan, Jianyuan Guo, Chao Zhang, Xilin Chen, Jingdong Wang
    http://arxiv.org/abs/1907.12273v1

    • [cs.CV]Iris Recognition for Personal Identification using LAMSTAR neural network
    Shideh Homayon, Mahdi Salarian
    http://arxiv.org/abs/1907.12145v1

    • [cs.CV]It’s All About The Scale — Efficient Text Detection Using Adaptive Scaling
    Elad Richardson, Yaniv Azar, Or Avioz, Niv Geron, Tomer Ronen, Zach Avraham, Stav Shapiro
    http://arxiv.org/abs/1907.12122v1

    • [cs.CV]KNEEL: Knee Anatomical Landmark Localization Using Hourglass Networks
    Aleksei Tiulpin, Iaroslav Melekhov, Simo Saarakkala
    http://arxiv.org/abs/1907.12237v1

    • [cs.CV]Learn to Scale: Generating Multipolar Normalized Density Map for Crowd Counting
    Chenfeng Xu, Kai Qiu, Jianlong Fu, Song Bai, Yongchao Xu, Xiang Bai
    http://arxiv.org/abs/1907.12428v1

    • [cs.CV]Learning Body Shape and Pose from Dense Correspondences
    Yusuke Yoshiyasu, Lucas Gamez
    http://arxiv.org/abs/1907.11955v1

    • [cs.CV]Learning Instance-wise Sparsity for Accelerating Deep Models
    Chuanjian Liu, Yunhe Wang, Kai Han, Chunjing Xu, Chang Xu
    http://arxiv.org/abs/1907.11840v1

    • [cs.CV]Learning Wear Patterns on Footwear Outsoles Using Convolutional Neural Networks
    Xavier Francis, Hamid Sharifzadeh, Angus Newton, Nilufar Baghaei, Soheil Varastehpour
    http://arxiv.org/abs/1907.12005v1

    • [cs.CV]MaskGAN: Towards Diverse and Interactive Facial Image Manipulation
    Cheng-Han Lee, Ziwei Liu, Lingyun Wu, Ping Luo
    http://arxiv.org/abs/1907.11922v1

    • [cs.CV]Meta Learning for Task-Driven Video Summarization
    Xuelong Li, Hongli Li, Yongsheng Dong
    http://arxiv.org/abs/1907.12342v1

    • [cs.CV]Multi-Granularity Fusion Network for Proposal and Activity Localization: Submission to ActivityNet Challenge 2019 Task 1 and Task 2
    Haisheng Su, Xu Zhao, Shuming Liu
    http://arxiv.org/abs/1907.12223v1

    • [cs.CV]Multi-Task Attention-Based Semi-Supervised Learning for Medical Image Segmentation
    Shuai Chen, Gerda Bortsova, Antonio Garcia-Uceda Juarez, Gijs van Tulder, Marleen de Bruijne
    http://arxiv.org/abs/1907.12303v1

    • [cs.CV]On the Realization and Analysis of Circular Harmonic Transforms for Feature Detection
    Hugh L Kennedy
    http://arxiv.org/abs/1907.12165v1

    • [cs.CV]Optical Flow for Intermediate Frame Interpolation of Multispectral Geostationary Satellite Data
    Thomas Vandal, Ramakrishna Nemani
    http://arxiv.org/abs/1907.12013v1

    • [cs.CV]Pick-and-Learn: Automatic Quality Evaluation for Noisy-Labeled Image Segmentation
    Haidong Zhu, Jialin Shi, Ji Wu
    http://arxiv.org/abs/1907.11835v1

    • [cs.CV]Quadtree Generating Networks: Efficient Hierarchical Scene Parsing with Sparse Convolutions
    Kashyap Chitta, Jose M. Alvarez, Martial Hebert
    http://arxiv.org/abs/1907.11821v1

    • [cs.CV]ROAM: Recurrently Optimizing Tracking Model
    Tianyu Yang, Pengfei Xu, Runbo Hu, Hua Chai, Antoni B. Chan
    http://arxiv.org/abs/1907.12006v1

    • [cs.CV]Real-time Tracking-by-Detection of Human Motion in RGB-D Camera Networks
    Alessandro Malaguti, Marco Carraro, Mattia Guidolin, Luca Tagliapietra, Emanuele Menegatti, Stefano Ghidoni
    http://arxiv.org/abs/1907.12112v1

    • [cs.CV]Recursive Cascaded Networks for Unsupervised Medical Image Registration
    Shengyu Zhao, Yue Dong, Eric I-Chao Chang, Yan Xu
    http://arxiv.org/abs/1907.12353v1

    • [cs.CV]Regularizing Proxies with Multi-Adversarial Training for Unsupervised Domain-Adaptive Semantic Segmentation
    Tong Shen, Dong Gong, Wei Zhang, Chunhua Shen, Tao Mei
    http://arxiv.org/abs/1907.12282v1

    • [cs.CV]Reprojection R-CNN: A Fast and Accurate Object Detector for 360° Images
    Pengyu Zhao, Ansheng You, Yuanxing Zhang, Jiaying Liu, Kaigui Bian, Yunhai Tong
    http://arxiv.org/abs/1907.11830v1

    • [cs.CV]Rethinking Classification and Localization for Cascade R-CNN
    Ang Li, Xue Yang, Chongyang Zhang
    http://arxiv.org/abs/1907.11914v1

    • [cs.CV]Salient Slices: Improved Neural Network Training and Performance with Image Entropy
    Steven J. Frank, Andrea M. Frank
    http://arxiv.org/abs/1907.12436v1

    • [cs.CV]Seeing Things in Random-Dot Videos
    Thomas Dagès, Michael Lindenbaum, Alfred M. Bruckstein
    http://arxiv.org/abs/1907.12195v1

    • [cs.CV]Segmenting Hyperspectral Images Using Spectral-Spatial Convolutional Neural Networks With Training-Time Data Augmentation
    Jakub Nalepa, Lukasz Tulczyjew, Michal Myller, Michal Kawulok
    http://arxiv.org/abs/1907.11935v1

    • [cs.CV]Self-Supervised Learning for Stereo Reconstruction on Aerial Images
    Patrick Knöbelreiter, Christoph Vogel, Thomas Pock
    http://arxiv.org/abs/1907.12446v1

    • [cs.CV]Semantic Guided Single Image Reflection Removal
    Yunfei Liu, Yu Li, Shaodi You, Feng Lu
    http://arxiv.org/abs/1907.11912v1

    • [cs.CV]Silhouette Guided Point Cloud Reconstruction beyond Occlusion
    Chuhang Zou, Derek Hoiem
    http://arxiv.org/abs/1907.12253v1

    • [cs.CV]Specular- and Diffuse-reflection-based Face Liveness Detection for Mobile Devices
    Akinori F. Ebihara, Kazuyuki Sakurai, Hitoshi Imaoka
    http://arxiv.org/abs/1907.12400v1

    • [cs.CV]Tell Me What to Track
    Qi Feng, Vitaly Ablavsky, Qinxun Bai, Guorong Li, Stan Sclaroff
    http://arxiv.org/abs/1907.11751v1

    • [cs.CV]To Learn or Not to Learn: Analyzing the Role of Learning for Navigation in Virtual Environments
    Noriyuki Kojima, Jia Deng
    http://arxiv.org/abs/1907.11770v1

    • [cs.CV]Towards Automatic Screening of Typical and Atypical Behaviors in Children With Autism
    Andrew Cook, Bappaditya Mandal, Donna Berry, Matthew Johnson
    http://arxiv.org/abs/1907.12537v1

    • [cs.CV]Triangulation: Why Optimize?
    Seong Hun Lee, Javier Civera
    http://arxiv.org/abs/1907.11917v1

    • [cs.CV]V-PROM: A Benchmark for Visual Reasoning Using Visual Progressive Matrices
    Damien Teney, Peng Wang, Jiewei Cao, Lingqiao Liu, Chunhua Shen, Anton van den Hengel
    http://arxiv.org/abs/1907.12271v1

    • [cs.CV]VITAL: A Visual Interpretation on Text with Adversarial Learning for Image Labeling
    Tao Hu, Chengjiang Long, Leheng Zhang, Chunxia Xiao
    http://arxiv.org/abs/1907.11811v1

    • [cs.CV]X-LineNet: Detecting Aircraft in Remote Sensing Images by a pair of Intersecting Line Segments
    Haoran Wei, Wang Bing, Zhang Yue
    http://arxiv.org/abs/1907.12474v1

    • [cs.CY]Artificial Intelligence and the Future of Psychiatry: Insights from a Global Physician Survey
    P. Murali Doraiswamy, Charlotte Blease, Kaylee Bodner
    http://arxiv.org/abs/1907.12386v1

    • [cs.CY]Estimating Parameters in Mathematical Model for Societal Booms through Bayesian Inference Approach
    Yasushi Ota, Naoki Mizutani
    http://arxiv.org/abs/1907.12090v1

    • [cs.CY]Micro-accounting for optimizing and saving energy in smart buildings
    Daniele Sora, Massimo Meceella, Francesco Leotta, Giuseppe Bracone, Daniele Buonanno, Mario Caruso, Adriano Cerocchi, Mariano Leva
    http://arxiv.org/abs/1907.12457v1

    • [cs.CY]Modelling the Safety and Surveillance of the AI Race
    The Anh Han, Luis Moniz Pereira, Francisco C. Santos, Tom Lenaerts
    http://arxiv.org/abs/1907.12393v1

    • [cs.CY]Reducing malicious use of synthetic media research: Considerations and potential release practices for machine learning
    Aviv Ovadya, Jess Whittlestone
    http://arxiv.org/abs/1907.11274v2

    • [cs.CY]The Challenges of Investigating Cryptocurrencies and Blockchain Related Crime
    Simon Dyson, William J Buchanan, Liam Bell
    http://arxiv.org/abs/1907.12221v1

    • [cs.DB]sql4ml A declarative end-to-end workflow for machine learning
    Nantia Makrynioti, Ruy Ley-Wild, Vasilis Vassalos
    http://arxiv.org/abs/1907.12415v1

    • [cs.DC]Decentralized utility- and locality-aware replication for heterogeneous DHT-based P2P cloud storage systems
    Yahya Hassanzadeh-Nazarabadi, Alptekin Küpçü, Öznur Özkasap
    http://arxiv.org/abs/1907.11997v1

    • [cs.DC]Distributed Approximation Algorithms for Steiner Tree in the $\mathcal{CONGESTED}$ $\mathcal{CLIQUE}$
    Parikshit Saikia, Sushanta Karmaker
    http://arxiv.org/abs/1907.12011v1

    • [cs.DC]Faster asynchronous MST and low diameter tree construction with sublinear communication
    Ali Mashreghi, Valerie King
    http://arxiv.org/abs/1907.12152v1

    • [cs.DC]Geospatial Big Data Handling with High Performance Computing: Current Approaches and Future Directions
    Zhenlong Li
    http://arxiv.org/abs/1907.12182v1

    • [cs.DC]On Observability and Monitoring of Distributed Systems: An Industry Interview Study
    Sina Niedermaier, Falko Koetter, Andreas Freymann, Stefan Wagner
    http://arxiv.org/abs/1907.12240v1

    • [cs.DC]Research Computing at a Business University
    Jason Wells, J. Eric Coulter
    http://arxiv.org/abs/1907.11961v1

    • [cs.DC]Small Profits and Quick Returns: An Incentive Mechanism Design for IoT-based Crowdsourcing under Continuous Platform Competition
    Duin Baek, Jing Chen, Bong Jun Choi
    http://arxiv.org/abs/1907.12500v1

    • [cs.DC]Spartan: Sparse Robust Addressable Networks
    John Augustine, Sumathi Sivasubramaniam
    http://arxiv.org/abs/1907.12028v1

    • [cs.DC]Staged deployment of interactive multi-application HPC workflows
    Wouter Klijn, Sandra Diaz-Pier, Abigail Morrison, Alexander Peyser
    http://arxiv.org/abs/1907.12275v1

    • [cs.DC]Temporal Data Fusion at the Edge
    Linfu Yang, Bin Liu
    http://arxiv.org/abs/1907.12042v1

    • [cs.DS]Distributed Dense Subgraph Detection and Low Outdegree Orientation
    Hsin-Hao Su, Hoa T. Vu
    http://arxiv.org/abs/1907.12443v1

    • [cs.DS]Low-Rank Matrix Completion: A Contemporary Survey
    Luong Trung Nguyen, Junhan Kim, Byonghyo Shim
    http://arxiv.org/abs/1907.11705v1

    • [cs.GR]Self-Imitation Learning of Locomotion Movements through Termination Curriculum
    Amin Babadi, Kourosh Naderi, Perttu Hämäläinen
    http://arxiv.org/abs/1907.11842v1

    • [cs.HC]Augmented Reality Applied to LEGO Construction: AR-based Building Instructions with High Accuracy & Precision and Realistic Object-Hand Occlusions
    Wei Yan
    http://arxiv.org/abs/1907.12549v1

    • [cs.HC]Multivariate Pointwise Information-Driven Data Sampling and Visualization
    Soumya Dutta, Ayan Biswas, James Ahrens
    http://arxiv.org/abs/1907.11762v1

    • [cs.HC]Personality is Revealed During Weekends: Towards Data Minimisation for Smartphone Based Personality Classification
    Mohammed Khwaja, Aleksandar Matic
    http://arxiv.org/abs/1907.11498v2

    • [cs.HC]Towards Understanding and Modeling Empathy for Use in Motivational Design Thinking
    Gloria Washington, Rouzbeh Shirvani
    http://arxiv.org/abs/1907.12001v1

    • [cs.IR]Deep Cross-Modal Hashing with Hashing Functions and Unified Hash Codes Jointly Learning
    Rong-Cheng Tu, Xian-Ling Mao, Bing Ma, Yong Hu, Tan Yan, Wei Wei, Heyan Huang
    http://arxiv.org/abs/1907.12490v1

    • [cs.IR]On the Value of Bandit Feedback for Offline Recommender System Evaluation
    Olivier Jeunen, David Rohde, Flavian Vasile
    http://arxiv.org/abs/1907.12384v1

    • [cs.IR]Style Conditioned Recommendations
    Murium Iqbal, Kamelia Aryafar, Timothy Anderton
    http://arxiv.org/abs/1907.12388v1

    • [cs.IT]A Greedy Algorithm for Matrix Recovery with Subspace Prior Information
    Hamideh. S Fazael Ardakani, Sajad Daei, Farzan Haddadi
    http://arxiv.org/abs/1907.11868v1

    • [cs.IT]Diffusion Hypercontractivity via Generalized Density Manifold
    Wuchen Li
    http://arxiv.org/abs/1907.12546v1

    • [cs.IT]Energy-Efficient Processing and Robust Wireless Cooperative Transmission for Edge Inference
    Kai Yang, Yuanming Shi, Wei Yu, Zhi Ding
    http://arxiv.org/abs/1907.12475v1

    • [cs.IT]Finite-Precision Implementation of Arithmetic Coding Based Distribution Matchers
    Marcin Pikus, Wen Xu, Gerhard Kramer
    http://arxiv.org/abs/1907.12066v1

    • [cs.IT]Hulls of Linear Codes Revisited with Applications
    Satanan Thipworawimon, Somphong Jitman
    http://arxiv.org/abs/1907.12026v1

    • [cs.IT]Linear reconstructions and the analysis of the stable sampling rate
    Laura Thesing, Anders Christian Hansen
    http://arxiv.org/abs/1907.12286v1

    • [cs.IT]Monomial-Cartesian codes and their duals, with applications to LCD codes, quantum codes, and locally recoverable codes
    Hiram H. López, Gretchen Matthews, Ivan Soprunov
    http://arxiv.org/abs/1907.11812v1

    • [cs.IT]Necessities and sufficiencies of a class of permutation polynomials over finite fields
    Xiaogang Liu
    http://arxiv.org/abs/1907.12086v1

    • [cs.IT]On the Probability of Partial Decoding in Sparse Network Coding
    Hadi Sehat, Peyman Pahlevani
    http://arxiv.org/abs/1907.12051v1

    • [cs.LG]A Deep Learning Based Attack for The Chaos-based Image Encryption
    Chen He, Kan Ming, Yongwei Wang, Z. Jane Wang
    http://arxiv.org/abs/1907.12245v1

    • [cs.LG]A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment
    Felix Leibfried, Sergio Pascual-Diaz, Jordi Grau-Moya
    http://arxiv.org/abs/1907.12392v1

    • [cs.LG]Action Grammars: A Cognitive Model for Learning Temporal Abstractions
    Robert Tjarko Lange, Aldo Faisal
    http://arxiv.org/abs/1907.12477v1

    • [cs.LG]AiAds: Automated and Intelligent Advertising System for Sponsored Search
    Xiao Yang, Daren Sun, Ruiwei Zhu, Tao Deng, Zhi Guo, Jiao Ding, Shouke Qin, Zongyao Ding, Yanfeng Zhu
    http://arxiv.org/abs/1907.12118v1

    • [cs.LG]An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing
    Baihong Jin, Yingshui Tan, Alexander Nettekoven, Yuxin Chen, Ufuk Topcu, Yisong Yue, Alberto Sangiovanni Vincentelli
    http://arxiv.org/abs/1907.11778v1

    • [cs.LG]Are Odds Really Odd? Bypassing Statistical Detection of Adversarial Examples
    Hossein Hosseini, Sreeram Kannan, Radha Poovendran
    http://arxiv.org/abs/1907.12138v1

    • [cs.LG]Bandit Convex Optimization in Non-stationary Environments
    Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou
    http://arxiv.org/abs/1907.12340v1

    • [cs.LG]Bandits with Feedback Graphs and Switching Costs
    Raman Arora, Teodor V. Marinov, Mehryar Mohri
    http://arxiv.org/abs/1907.12189v1

    • [cs.LG]Blocking Bandits
    Soumya Basu, Rajat Sen, Sujay Sanghavi, Sanjay Shakkottai
    http://arxiv.org/abs/1907.11975v1

    • [cs.LG]Charting the Right Manifold: Manifold Mixup for Few-shot Learning
    Puneet Mangla, Mayank Singh, Abhishek Sinha, Nupur Kumari, Vineeth N Balasubramanian, Balaji Krishnamurthy
    http://arxiv.org/abs/1907.12087v1

    • [cs.LG]CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting
    Chaoyun Zhang, Marco Fiore, Iain Murray, Paul Patras
    http://arxiv.org/abs/1907.12410v1

    • [cs.LG]Computing the Value of Data: Towards Applied Data Minimalism
    Michaela Regneri, Julia S. Georgi, Jurij Kost, Niklas Pietsch, Sabine Stamm
    http://arxiv.org/abs/1907.12404v1

    • [cs.LG]DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation
    Shashank Rajput, Hongyi Wang, Zachary Charles, Dimitris Papailiopoulos
    http://arxiv.org/abs/1907.12205v1

    • [cs.LG]Deep Reinforcement Learning for Personalized Search Story Recommendation
    Jason, Zhang, Junming Yin, Dongwon Lee, Linhong Zhu
    http://arxiv.org/abs/1907.11754v1

    • [cs.LG]DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks
    Simon Wiedemann, Heiner Kirchoffer, Stefan Matlage, Paul Haase, Arturo Marban, Talmaj Marinc, David Neumann, Tung Nguyen, Ahmed Osman, Detlev Marpe, Heiko Schwarz, Thomas Wiegand, Wojciech Samek
    http://arxiv.org/abs/1907.11900v1

    • [cs.LG]Discovering Association with Copula Entropy
    Ma Jian
    http://arxiv.org/abs/1907.12268v1

    • [cs.LG]FDive: Learning Relevance Models using Pattern-based Similarity Measures
    Frederik L. Dennig, Tom Polk, Zudi Lin, Tobias Schreck, Hanspeter Pfister, Michael Behrisch
    http://arxiv.org/abs/1907.12489v1

    • [cs.LG]Generative Adversarial Network for Handwritten Text
    Bo Ji, Tianyi Chen
    http://arxiv.org/abs/1907.11845v1

    • [cs.LG]Hidden Covariate Shift: A Minimal Assumption For Domain Adaptation
    Victor Bouvier, Philippe Very, Céline Hudelot, Clément Chastagnol
    http://arxiv.org/abs/1907.12299v1

    • [cs.LG]Hindsight Trust Region Policy Optimization
    Hanbo Zhang, Site Bai, Xuguang Lan, Nanning Zheng
    http://arxiv.org/abs/1907.12439v1

    • [cs.LG]Learnable Parameter Similarity
    Guangcong Wang, Jianhuang Lai, Wenqi Liang, Guangrun Wang
    http://arxiv.org/abs/1907.11943v1

    • [cs.LG]Learning Invariant Representations for Sentiment Analysis: The Missing Material is Datasets
    Victor Bouvier, Philippe Very, Céline Hudelot, Clément Chastagnol
    http://arxiv.org/abs/1907.12305v1

    • [cs.LG]Learning Task Specifications from Demonstrations via the Principle of Maximum Causal Entropy
    Marcell Vazquez-Chanlatte, Sanjit A. Seshia
    http://arxiv.org/abs/1907.11792v1

    • [cs.LG]Learning and Interpreting Potentials for Classical Hamiltonian Systems
    Harish S. Bhat
    http://arxiv.org/abs/1907.11806v1

    • [cs.LG]Many could be better than all: A novel instance-oriented algorithm for Multi-modal Multi-label problem
    Yi Zhang, Cheng Zeng, Hao Cheng, Chongjun Wang, Lei Zhang
    http://arxiv.org/abs/1907.11857v1

    • [cs.LG]Mindful Active Learning
    Zhila Esna Ashari, Hassan Ghasemzadeh
    http://arxiv.org/abs/1907.12003v1

    • [cs.LG]Modeling Winner-Take-All Competition in Sparse Binary Projections
    Wenye Li
    http://arxiv.org/abs/1907.11959v1

    • [cs.LG]Multi-modal Predictive Models of Diabetes Progression
    Ramin Ramazi, Christine Perndorfer, Emily Soriano, Jean-Philippe Laurenceau, Rahmatollah Beheshti
    http://arxiv.org/abs/1907.12175v1

    • [cs.LG]Multi-task Self-Supervised Learning for Human Activity Detection
    Aaqib Saeed, Tanir Ozcelebi, Johan Lukkien
    http://arxiv.org/abs/1907.11879v1

    • [cs.LG]On Hard Exploration for Reinforcement Learning: a Case Study in Pommerman
    Chao Gao, Bilal Kartal, Pablo Hernandez-Leal, Matthew E. Taylor
    http://arxiv.org/abs/1907.11788v1

    • [cs.LG]Probabilistic Models of Relational Implication
    Xavier Holt
    http://arxiv.org/abs/1907.12048v1

    • [cs.LG]Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization
    Wanli Shi, Bin Gu, Xiang Li, Xiang Geng, Heng Huang
    http://arxiv.org/abs/1907.12416v1

    • [cs.LG]REP: Predicting the Time-Course of Drug Sensitivity
    Cheng Qian, Amin Emad, Nicholas D. Sidiropoulos
    http://arxiv.org/abs/1907.11911v1

    • [cs.LG]RNNbow: Visualizing Learning via Backpropagation Gradients in Recurrent Neural Networks
    Dylan Cashman, Genevieve Patterson, Abigail Mosca, Nathan Watts, Shannon Robinson, Remco Chang
    http://arxiv.org/abs/1907.12545v1

    • [cs.LG]Scalable Dictionary Classifiers for Time Series Classification
    Matthew Middlehurst, William Vickers, Anthony Bagnall
    http://arxiv.org/abs/1907.11815v1

    • [cs.LG]Tackling Multiple Ordinal Regression Problems: Sparse and Deep Multi-Task Learning Approaches
    Lu Wang, Dongxiao Zhu
    http://arxiv.org/abs/1907.12508v1

    • [cs.LG]Uncertainty in Model-Agnostic Meta-Learning using Variational Inference
    Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro
    http://arxiv.org/abs/1907.11864v1

    • [cs.LG]Understanding Adversarial Robustness: The Trade-off between Minimum and Average Margin
    Kaiwen Wu, Yaoliang Yu
    http://arxiv.org/abs/1907.11780v1

    • [cs.LO]Strengthening Gossip Protocols using Protocol-Dependent Knowledge
    Hans van Ditmarsch, Malvin Gattinger, Louwe B. Kuijer, Pere Pardo
    http://arxiv.org/abs/1907.12321v1

    • [cs.MA]G-flocking: Flocking Model Optimization based on Genetic Framework
    Li Ma, Weidong Bao, Xiaomin Zhu, Meng Wu, Yuan Wang, Yunxiang Ling, Wen Zhou
    http://arxiv.org/abs/1907.11852v1

    • [cs.NE]Autoencoding with a Learning Classifier System: Initial Results
    Larry Bull
    http://arxiv.org/abs/1907.11554v2

    • [cs.NE]On the Limitations of the Univariate Marginal Distribution Algorithm to Deception and Where Bivariate EDAs might help
    Per Kristian Lehre, Phan Trung Hai Nguyen
    http://arxiv.org/abs/1907.12438v1

    • [cs.NE]SOM-Guided Evolutionary Search for Solving MinMax Multiple-TSP
    Vlad-Ioan Lupoaie, Ivona-Alexandra Chili, Mihaela Elena Breaban, Madalina Raschip
    http://arxiv.org/abs/1907.11910v1

    • [cs.NI]Deep Learning for CSI Feedback Based on Superimposed Coding
    Chaojin Qing, Bin Cai, Qingyao Yang, Jiafan Wang, Chuan Huang
    http://arxiv.org/abs/1907.11836v1

    • [cs.NI]Q-MIND: Defeating Stealthy DoS Attacks in SDN with a Machine-learning based Defense Framework
    Trung V. Phan, T M Rayhan Gias, Syed Tasnimul Islam, Truong Thu Huong, Nguyen Huu Thanh, Thomas Bauschert
    http://arxiv.org/abs/1907.11887v1

    • [cs.RO]Environment Probing Interaction Policies
    Wenxuan Zhou, Lerrel Pinto, Abhinav Gupta
    http://arxiv.org/abs/1907.11740v1

    • [cs.RO]Jerk Control of Floating Base Systems with Contact-Stable Parametrised Force Feedback
    Ahmad Gazar, Gabriele Nava, Francisco Javier Andrade Chavez, Daniele Pucci
    http://arxiv.org/abs/1907.11906v1

    • [cs.RO]Real-Time 3D Profiling with RGB-D Mapping in Pipelines Using Stereo Camera Vision and Structured IR Laser Ring
    Amal Gunatilake, Lasitha Piyathilaka, Sarath Kodagoda, Stephen Barclay, Dammika Vitanage
    http://arxiv.org/abs/1907.12172v1

    • [cs.RO]Solving the Robot-World Hand-Eye(s) Calibration Problem with Iterative Methods
    Amy Tabb, Khalil M. Ahmad Yousef
    http://arxiv.org/abs/1907.12425v1

    • [cs.SD]StarGAN-VC2: Rethinking Conditional Methods for StarGAN-Based Voice Conversion
    Takuhiro Kaneko, Hirokazu Kameoka, Kou Tanaka, Nobukatsu Hojo
    http://arxiv.org/abs/1907.12279v1

    • [cs.SE]Characterizing and Understanding Software Developer Networks in Security Development
    Song Wang, Nachi Nagappan
    http://arxiv.org/abs/1907.12141v1

    • [cs.SE]Scalable Source Code Similarity Detection in Large Code Repositories
    F Alomari, M Harbi
    http://arxiv.org/abs/1907.11817v1

    • [cs.SI]DynWalks: Global Topology and Recent Changes Awareness Dynamic Network Embedding
    Chengbin Hou, Han Zhang, Ke Tang, Shan He
    http://arxiv.org/abs/1907.11968v1

    • [cs.SI]Fusing location and text features for sentiment classification
    Wei Lun Lim, Chiung Ching Ho, Choo-Yee Ting
    http://arxiv.org/abs/1907.12008v1

    • [cs.SI]Nonuniform Timeslicing of Dynamic Graphs Based on Visual Complexity
    Yong Wang, Daniel Archambault, Hammad Haleem, Torsten Moeller, Yanhong Wu, Huamin Qu
    http://arxiv.org/abs/1907.12015v1

    • [cs.SI]Unlocking Analytical Value from Social Media and User Generated Content
    James Meneghello, Nik Thompson, Kevin Lee, Kok Wai Wong, Bilal Abu-Salih
    http://arxiv.org/abs/1907.11934v1

    • [eess.IV]A Two Stage GAN for High Resolution Retinal Image Generation and Segmentation
    Paolo Andreini, Simone Bonechi, Monica Bianchini, Alessandro Mecocci, Franco Scarselli, Andrea Sodi
    http://arxiv.org/abs/1907.12296v1

    • [eess.IV]Automated Lesion Detection by Regressing Intensity-Based Distance with a Neural Network
    Kimberlin M. H. van Wijnen, Florian Dubost, Pinar Yilmaz, M. Arfan Ikram, Wiro J. Niessen, Hieab Adams, Meike W. Vernooij, Marleen de Bruijne
    http://arxiv.org/abs/1907.12452v1

    • [eess.IV]Blind Deblurring Using GANs
    Manoj Kumar Lenka, Anubha Pandey, Anurag Mittal
    http://arxiv.org/abs/1907.11880v1

    • [eess.IV]Deep learning-based prediction of kinetic parameters from myocardial perfusion MRI
    Cian M. Scannell, Piet van den Bosch, Amedeo Chiribiri, Jack Lee, Marcel Breeuwer, Mitko Veta
    http://arxiv.org/abs/1907.11899v1

    • [eess.IV]FocusNet: Imbalanced Large and Small Organ Segmentation with an End-to-End Deep Neural Network for Head and Neck CT Images
    Yunhe Gao, Rui Huang, Ming Chen, Zhe Wang, Jincheng Deng, Yuanyuan Chen, Yiwei Yang, Jie Zhang, Chanjuan Tao, Hongsheng Li
    http://arxiv.org/abs/1907.12056v1

    • [eess.IV]Momentum-Net: Fast and convergent iterative neural network for inverse problems
    Il Yong Chun, Zhengyu Huang, Hongki Lim, Jeffrey A. Fessler
    http://arxiv.org/abs/1907.11818v1

    • [eess.IV]Remote Heart Rate Measurement from Highly Compressed Facial Videos: an End-to-end Deep Learning Solution with Video Enhancement
    Zitong Yu, Wei Peng, Xiaobai Li, Xiaopeng Hong, Guoying Zhao
    http://arxiv.org/abs/1907.11921v1

    • [eess.IV]Two-Stream CNN with Loose Pair Training for Multi-modal AMD Categorization
    Weisen Wang, Zhiyan Xu, Weihong Yu, Jianchun Zhao, Jingyuan Yang, Feng He, Zhikun Yang, Di Chen, Dayong Ding, Youxin Chen, Xirong Li
    http://arxiv.org/abs/1907.12023v1

    • [eess.SP]Two Efficient Beamformers for Secure Precise Jamming and Communication with Phase Alignment
    Feng Shu, Lingling Zhu, Wenlong Cai, Tong Shen, Jinyong Lin, Shuo Zhang, Jiangzhou Wang
    http://arxiv.org/abs/1907.12070v1

    • [eess.SP]Weighted Spectral Efficiency Optimization for Hybrid Beamforming in Multiuser Massive MIMO-OFDM Systems
    Jingbo Du, Wei Xu, Chunming Zhao, Luc Vandendorpe
    http://arxiv.org/abs/1907.12255v1

    • [math.AG]On local real algebraic geometry and applications to kinematics
    Marc Diesse
    http://arxiv.org/abs/1907.12134v1

    • [math.PR]Reinforcement with Fading Memories
    Kuang Xu, Se-Young Yun
    http://arxiv.org/abs/1907.12227v1

    • [math.ST]A Higher-Order Swiss Army Infinitesimal Jackknife
    Ryan Giordano, Michael I. Jordan, Tamara Broderick
    http://arxiv.org/abs/1907.12116v1

    • [math.ST]A Theoretical Case Study of Structured Variational Inference for Community Detection
    Mingzhang Yin, Y. X. Rachel Wang, Purnamrita Sarkar
    http://arxiv.org/abs/1907.12203v1

    • [math.ST]Approximating the Span of Principal Components via Iterative Least-Squares
    Yariv Aizenbud, Barak Sober
    http://arxiv.org/abs/1907.12159v1

    • [math.ST]Estimating the Random Effect in Big Data Mixed Models
    Michael Law, Ya’acov Ritov
    http://arxiv.org/abs/1907.11958v1

    • [math.ST]Principal components of spiked covariance matrices in the supercritical regime
    Zhigang Bao, Xiucai Ding, Jingming Wang, Ke Wang
    http://arxiv.org/abs/1907.12251v1

    • [math.ST]Subsampling Sparse Graphons Under Minimal Assumptions
    Robert Lunde, Purnamrita Sarkar
    http://arxiv.org/abs/1907.12528v1

    • [physics.app-ph]Lotka-Volterra competition mechanism embedded in a decision-making method
    Tomoaki Niiyama, Genki Furuhata, Atsushi Uchida, Makoto Naruse, Satoshi Sunada
    http://arxiv.org/abs/1907.12399v1

    • [physics.soc-ph]Beyond the Coverage of Information Spreading: Analytical and Empirical Evidence of Re-exposure in Large-scale Online Social Networks
    Xin Lu, Shuo Qin, Petter Holme, Fanhui Meng, Yanqing Hu, Fredrik Liljeros, Gad Allon
    http://arxiv.org/abs/1907.12389v1

    • [physics.soc-ph]Fitting In and Breaking Up: A Nonlinear Version of Coevolving Voter Models
    Yacoub H. Kureh, Mason A. Porter
    http://arxiv.org/abs/1907.11608v1

    • [q-bio.NC]Effective and efficient ROI-wise visual encoding using an end-to-end CNN regression model and selective optimization
    Kai Qiao, Chi Zhang, Jian Chen, Linyuan Wang, Li Tong, Bin Yan
    http://arxiv.org/abs/1907.11885v1

    • [q-bio.NC]Modulation of early visual processing alleviates capacity limits \in solving multiple tasks
    Sushrut Thorat, Giacomo Aldegheri, Marcel A. J. van Gerven, Marius V. Peelen
    http://arxiv.org/abs/1907.12309v1

    • [q-bio.NC]Spatiotemporal Information Processing with a Reservoir Decision-making Network
    Yuanyuan Mi, Xiaohan Lin, Xiaolong Zou, Zilong Ji, Tiejun Huang, Si Wu
    http://arxiv.org/abs/1907.12071v1

    • [q-fin.ST]Investigating the effect of competitiveness power in estimating the average weighted price in electricity market
    Naser Rostamni, Tarik A. Rashid
    http://arxiv.org/abs/1907.11984v1

    • [stat.AP]A Bayesian nonparametric approach to the approximation of the global stable manifold
    Spyridon J. Hatjispyros, Konstantinos Kaloudis
    http://arxiv.org/abs/1907.12510v1

    • [stat.AP]A Particle Filter for Stochastic Advection by Lie Transport (SALT): A case study for the damped and forced incompressible 2D Euler equation
    Colin Cotter, Dan Crisan, Darryl D. Holm, Wei Pan, Igor Shevchenko
    http://arxiv.org/abs/1907.11884v1

    • [stat.AP]Modellvalidierung mit Hilfe von Quantil-Quantil-Plots unter Solvency II (Model validation on the basis of quantile-quantile-plots under Solvency II)
    Dietmar Pfeifer
    http://arxiv.org/abs/1907.11925v1

    • [stat.CO]Adaptive spline fitting with particle swarm optimization
    Soumya D. Mohanty, Ethan Fahnestock
    http://arxiv.org/abs/1907.12160v1

    • [stat.CO]The Wang-Landau Algorithm as Stochastic Optimization and its Acceleration
    Chenguang Dai, Jun S. Liu
    http://arxiv.org/abs/1907.11985v1

    • [stat.ME]A Matrix—free Likelihood Method for Exploratory Factor Analysis of High-dimensional Gaussian Data
    Fan Dai, Somak Dutta, Ranjan Maitra
    http://arxiv.org/abs/1907.11970v1

    • [stat.ME]Max-and-Smooth: a two-step approach for approximate Bayesian inference in latent Gaussian models
    Birgir Hrafnkelsson, Árni V. Jóhannesson, Stefan Siegert, Haakon Bakka, Raphaël Huser
    http://arxiv.org/abs/1907.11969v1

    • [stat.ME]Mitigating unobserved spatial confounding bias with mixed models
    Patrick Schnell, Georgia Papadogeorgou
    http://arxiv.org/abs/1907.12150v1

    • [stat.ME]Modelling spine locations on dendrite trees using inhomogeneous Cox point processes
    Heidi S. Christensen, Jesper Møller
    http://arxiv.org/abs/1907.12283v1

    • [stat.ME]Multiply Robust Learning of the Average Treatment Effect with an Invalid Instrumental Variable
    BaoLuo Sun, Eric Tchetgen Tchetgen
    http://arxiv.org/abs/1907.11882v1

    • [stat.ME]Spatial Process Decomposition for Quantitative Imaging Biomarkers Using Multiple Images of Varying Shapes
    ShengLi Tzeng, Jun Zhu, Amy Weisman, Tyler Bradshaw, Robert Jeraj
    http://arxiv.org/abs/1907.11767v1

    • [stat.ML]A Strategy for Adaptive Sampling of Multi-fidelity Gaussian Process to Reduce Predictive Uncertainty
    Sayan Ghosh, Jesper Kristensen, Yiming Zhang, Waad Subber, Liping Wang
    http://arxiv.org/abs/1907.11739v1

    • [stat.ML]A neural network with feature sparsity
    Ismael Lemhadri, Feng Ruan, Robert Tibshirani
    http://arxiv.org/abs/1907.12207v1

    • [stat.ML]Bayesian Robustness: A Nonasymptotic Viewpoint
    Kush Bhatia, Yi-An Ma, Anca D. Dragan, Peter L. Bartlett, Michael I. Jordan
    http://arxiv.org/abs/1907.11826v1

    • [stat.ML]Bias of Homotopic Gradient Descent for the Hinge Loss
    Denali Molitor, Deanna Needell, Rachel Ward
    http://arxiv.org/abs/1907.11746v1

    • [stat.ML]Memory- and Communication-Aware Model Compression for Distributed Deep Learning Inference on IoT
    Kartikeya Bhardwaj, Chingyi Lin, Anderson Sartor, Radu Marculescu
    http://arxiv.org/abs/1907.11804v1

    • [stat.ML]Multi-Rank Sparse and Functional PCA: Manifold Optimization and Iterative Deflation Techniques
    Michael Weylandt
    http://arxiv.org/abs/1907.12012v1

    • [stat.ML]Variational f-divergence Minimization
    Mingtian Zhang, Thomas Bird, Raza Habib, Tianlin Xu, David Barber
    http://arxiv.org/abs/1907.11891v1

    • [stat.ML]Wasserstein Fair Classification
    Ray Jiang, Aldo Pacchiano, Tom Stepleton, Heinrich Jiang, Silvia Chiappa
    http://arxiv.org/abs/1907.12059v1