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
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• [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