cs.AI - 人工智能
cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.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.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.PL - 编程语言 cs.RO - 机器人学 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 math-ph - 数学物理 math.CO - 组合数学 math.OC - 优化与控制 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 quant-ph - 量子物理 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cs.AI]CLaRO: a Data-driven CNL for Specifying Competency Questions
• [cs.CL]Almawave-SLU: A new dataset for SLU in Italian
• [cs.CL]Differentiable Disentanglement Filter: an Application Agnostic Core Concept Discovery Probe
• [cs.CL]Fake News Detection as Natural Language Inference
• [cs.CL]Gated Recurrent Neural Network Approach for Multilabel Emotion Detection in Microblogs
• [cs.CL]Learning End-to-End Goal-Oriented Dialog with Maximal User Task Success and Minimal Human Agent Use
• [cs.CL]Learning Representation Mapping for Relation Detection in Knowledge Base Question Answering
• [cs.CL]Probing Neural Network Comprehension of Natural Language Arguments
• [cs.CL]STRASS: A Light and Effective Method for Extractive Summarization Based on Sentence Embeddings
• [cs.CL]SUMBT: Slot-Utterance Matching for Universal and Scalable Belief Tracking
• [cs.CL]You Write Like You Eat: Stylistic variation as a predictor of social stratification
• [cs.CR]Decentralized & Collaborative AI on Blockchain
• [cs.CR]Dynamic Malware Analysis with Feature Engineering and Feature Learning
• [cs.CR]Helen: Maliciously Secure Coopetitive Learning for Linear Models
• [cs.CR]Real-time Evasion Attacks with Physical Constraints on Deep Learning-based Anomaly Detectors in Industrial Control Systems
• [cs.CV]A Link Between the Multiplicative and Additive Functional Asplund’s Metrics
• [cs.CV]AVDNet: A Small-Sized Vehicle Detection Network for Aerial Visual Data
• [cs.CV]Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming
• [cs.CV]Deep Metric Learning with Alternating Projections onto Feasible Sets
• [cs.CV]FOSNet: An End-to-End Trainable Deep Neural Network for Scene Recognition
• [cs.CV]Half a Percent of Labels is Enough: Efficient Animal Detection in UAV Imagery using Deep CNNs and Active Learning
• [cs.CV]Multi-Adapter RGBT Tracking
• [cs.CV]News Cover Assessment via Multi-task Learning
• [cs.CV]OGNet: Salient Object Detection with Output-guided Attention Module
• [cs.CV]Real-time Vision-based Depth Reconstruction with NVidia Jetson
• [cs.CV]Relation Network for Multi-label Aerial Image Classification
• [cs.CV]Robustness properties of Facebook’s ResNeXt WSL models
• [cs.CV]Scene Motion Decomposition for Learnable Visual Odometry
• [cs.CV]Style Transfer Applied to Face Liveness Detection with User-Centered Models
• [cs.CV]Towards Data-Driven Automatic Video Editing
• [cs.CV]Towards Markerless Grasp Capture
• [cs.CV]Underexposed Image Correction via Hybrid Priors Navigated Deep Propagation
• [cs.CY]Canada Protocol: an ethical checklist for the use of Artificial Intelligence in Suicide Prevention and Mental Health
• [cs.CY]Inferring Tracker-Advertiser Relationships in the Online Advertising Ecosystem using Header Bidding
• [cs.CY]Truck Traffic Monitoring with Satellite Images
• [cs.DC]$\texttt{DeepSqueeze}$: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression
• [cs.DC]Partitioning Graphs for the Cloud using Reinforcement Learning
• [cs.DS]Seedless Graph Matching via Tail of Degree Distribution for Correlated Erdos-Renyi Graphs
• [cs.GR]RayTracer.jl: A Differentiable Renderer that supports Parameter Optimization for Scene Reconstruction
• [cs.HC]Conversational Help for Task Completion and Feature Discovery in Personal Assistants
• [cs.HC]End-To-End Prediction of Emotion From Heartbeat Data Collected by a Consumer Fitness Tracker
• [cs.HC]Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics
• [cs.HC]MedCATTrainer: A Biomedical Free Text Annotation Interface with Active Learning and Research Use Case Specific Customisation
• [cs.IR]Leveraging Linguistic Characteristics for Bipolar Disorder Recognition with Gender Differences
• [cs.IR]On the Importance of News Content Representation in Hybrid Neural Session-based Recommender Systems
• [cs.IR]The Role of Local Intrinsic Dimensionality in Benchmarking Nearest Neighbor Search
• [cs.IR]Unbiased Learning to Rank: Counterfactual and Online Approaches
• [cs.IT]A Note on Linear Complementary Pairs of Group Codes
• [cs.IT]Inference-Based Resource Allocation for Multi-Cell Backscatter Sensor Networks
• [cs.IT]Leveraging online learning for CSS in frugal IoT network
• [cs.IT]Multi-Antenna Covert Communications with Random Access Protocol
• [cs.IT]Optimal Energy Allocation and Task Offloading Policy for Wireless Powered Mobile Edge Computing Systems
• [cs.IT]Privacy-Aware Location Sharing with Deep Reinforcement Learning
• [cs.IT]Scalar Quantizer Design for Two-Way Channels
• [cs.IT]Scheduling to Minimize Age of Synchronization in Wireless Broadcast Networks with Random Updates
• [cs.IT]Sparse Subspace Clustering via Two-Step Reweighted L1-Minimization: Algorithm and Provable Neighbor Recovery Rates
• [cs.LG]$t$-$k$-means: A $k$-means Variant with Robustness and Stability
• [cs.LG]A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI
• [cs.LG]Adversarial Security Attacks and Perturbations on Machine Learning and Deep Learning Methods
• [cs.LG]An Embedding Framework for Consistent Polyhedral Surrogates
• [cs.LG]An Inductive Synthesis Framework for Verifiable Reinforcement Learning
• [cs.LG]AquaSight: Automatic Water Impurity Detection Utilizing Convolutional Neural Networks
• [cs.LG]Block based Singular Value Decomposition approach to matrix factorization for recommender systems
• [cs.LG]DeepTrax: Embedding Graphs of Financial Transactions
• [cs.LG]FAHT: An Adaptive Fairness-aware Decision Tree Classifier
• [cs.LG]Fairness-enhancing interventions in stream classification
• [cs.LG]Feature Selection via Mutual Information: New Theoretical Insights
• [cs.LG]Improving Heart Rate Variability Measurements from Consumer Smartwatches with Machine Learning
• [cs.LG]Improving Outbreak Detection with Stacking of Statistical Surveillance Methods
• [cs.LG]Learnability for the Information Bottleneck
• [cs.LG]Learning Multimodal Fixed-Point Weights using Gradient Descent
• [cs.LG]Low-Shot Classification: A Comparison of Classical and Deep Transfer Machine Learning Approaches
• [cs.LG]Mitigating Uncertainty in Document Classification
• [cs.LG]Online Local Boosting: improving performance in online decision trees
• [cs.LG]PPO Dash: Improving Generalization in Deep Reinforcement Learning
• [cs.LG]Remaining Useful Lifetime Prediction via Deep Domain Adaptation
• [cs.LG]Self-Attentive Hawkes Processes
• [cs.LG]Subspace Inference for Bayesian Deep Learning
• [cs.LG]Towards Understanding Generalization in Gradient-Based Meta-Learning
• [cs.NE]Iterative temporal differencing with random synaptic feedback weights support error backpropagation for deep learning
• [cs.NE]Machine Learning based Simulation Optimisation for Trailer Management
• [cs.NI]Achieving Ultra-Reliable Communication via CRAN-Enabled Diversity Schemes
• [cs.NI]Caching as an Image Characterization Problem using Deep Convolutional Neural Networks
• [cs.NI]Energy-Efficient Power Control of Train-ground mmWave Communication for High Speed Trains
• [cs.PL]Zygote: A Differentiable Programming System to Bridge Machine Learning and Scientific Computing
• [cs.RO]A General Framework of Learning Multi-Vehicle Interaction Patterns from Videos
• [cs.RO]Cooperative UAVs Gas Monitoring using Distributed Consensus
• [cs.RO]Edge Detection for Event Cameras using Intra-pixel-area Events
• [cs.RO]Evaluation of a 1-DOF Hand Exoskeleton for Neuromuscular Rehabilitation
• [cs.RO]Fly Safe: Aerial Swarm Robotics using Force Field Particle Swarm Optimisation
• [cs.RO]Learning Variable Impedance Control for Contact Sensitive Tasks
• [cs.RO]Leveraging Experience in Lazy Search
• [cs.RO]Stereo Event Lifetime and Disparity Estimation for Dynamic Vision Sensors
• [cs.RO]Stochastic Optimization for Trajectory Planning with Heteroscedastic Gaussian Processes
• [cs.RO]Tactile Model O: Fabrication and testing of a 3d-printed, three-fingered tactile robot hand
• [cs.RO]Towards Blockchain-based Multi-Agent Robotic Systems: Analysis, Classification and Applications
• [cs.RO]Understanding Teacher Gaze Patterns for Robot Learning
• [cs.SE]The General Data Protection Regulation: Requirements, Architectures, and Constraints
• [cs.SI]Computational Human Dynamics
• [cs.SI]DeepNC: Deep Generative Network Completion
• [cs.SI]Fairness and Diversity in the Recommendation and Ranking of Participatory Media Content
• [cs.SI]Homophily as a process generating social networks: insights from Social Distance Attachment model
• [cs.SI]Modeling Human Annotation Errors to Design Bias-Aware Systems for Social Stream Processing
• [cs.SI]Relevancy Classification of Multimodal Social Media Streams for Emergency Services
• [cs.SI]Towards Reliable Online Clickbait Video Detection: A Content-Agnostic Approach
• [econ.EM]Consistency and matching without replacement
• [eess.AS]AP19-OLR Challenge: Three Tasks and Their Baselines
• [eess.IV]CLCI-Net: Cross-Level fusion and Context Inference Networks for Lesion Segmentation of Chronic Stroke
• [eess.IV]Deep Learning for Pneumothorax Detection and Localization in Chest Radiographs
• [eess.SP]A Neural Network Detector for Spectrum Sensing under Uncertainties
• [eess.SP]Comparison of Neural Network Architectures for Spectrum Sensing
• [eess.SP]Deciphering Dynamical Nonlinearities in Short Time Series Using Recurrent Neural Networks
• [eess.SP]Deep learning scheme for microwave photonic analog broadband signal recovery
• [eess.SP]Near-Field Joint Localization and Synchronization
• [math-ph]Distribution of the ratio of two consecutive level spacings in orthogonal to unitary crossover ensembles
• [math.CO]Tangles in the social sciences
• [math.OC]Dynamic optimization with side information
• [math.OC]Feature-driven Improvement of Renewable Energy Forecasting and Trading
• [math.PR]On the cut-off phenomenon for the maximum of a sampling of Ornstein-Uhlenbeck processes
• [math.PR]On the geometry of polytopes generated by heavy-tailed random vectors
• [math.ST]What is… a Markov basis?
• [physics.app-ph]Noise Analysis of Photonic Modulator Neurons
• [physics.soc-ph]Constructions and properties of a class of random scale-free networks
• [quant-ph]Photonic architecture for reinforcement learning
• [stat.AP]Self Organizing Supply Chains for Micro-Prediction: Present and Future uses of the ROAR Protocol
• [stat.AP]Spherical data handling and analysis with R package rcosmo
• [stat.ME]A Multivariate Extreme Value Theory Approach to Anomaly Clustering and Visualization
• [stat.ME]Assessing Treatment Effect Variation in Observational Studies: Results from a Data Challenge
• [stat.ME]Factor copula models for mixed data
• [stat.ME]Optimal Sampling for Generalized Linear Models under Measurement Constraints
• [stat.ME]Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics
• [stat.ML]Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing
• [stat.ML]Clustering Activity-Travel Behavior Time Series using Topological Data Analysis
• [stat.ML]Output-weighted optimal sampling for Bayesian regression and rare event statistics using few samples
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• [cs.AI]CLaRO: a Data-driven CNL for Specifying Competency Questions
C. Maria Keet, Zola Mahlaza, Mary-Jane Antia
http://arxiv.org/abs/1907.07378v1
• [cs.CL]Almawave-SLU: A new dataset for SLU in Italian
Valentina Bellomaria, Giuseppe Castellucci, Andrea Favalli, Raniero Romagnoli
http://arxiv.org/abs/1907.07526v1
• [cs.CL]Differentiable Disentanglement Filter: an Application Agnostic Core Concept Discovery Probe
Guntis Barzdins, Eduards Sidorovics
http://arxiv.org/abs/1907.07507v1
• [cs.CL]Fake News Detection as Natural Language Inference
Kai-Chou Yang, Timothy Niven, Hung-Yu Kao
http://arxiv.org/abs/1907.07347v1
• [cs.CL]Gated Recurrent Neural Network Approach for Multilabel Emotion Detection in Microblogs
Prabod Rathnayaka, Supun Abeysinghe, Chamod Samarajeewa, Isura Manchanayake, Malaka J. Walpola, Rashmika Nawaratne, Tharindu Bandaragoda, Damminda Alahakoon
http://arxiv.org/abs/1907.07653v1
• [cs.CL]Learning End-to-End Goal-Oriented Dialog with Maximal User Task Success and Minimal Human Agent Use
Janarthanan Rajendran, Jatin Ganhotra, Lazaros Polymenakos
http://arxiv.org/abs/1907.07638v1
• [cs.CL]Learning Representation Mapping for Relation Detection in Knowledge Base Question Answering
Peng Wu, Shujian Huang, Rongxiang Weng, Zaixiang Zheng, Jianbing Zhang, Xiaohui Yan, Jiajun Chen
http://arxiv.org/abs/1907.07328v1
• [cs.CL]Probing Neural Network Comprehension of Natural Language Arguments
Timothy Niven, Hung-Yu Kao
http://arxiv.org/abs/1907.07355v1
• [cs.CL]STRASS: A Light and Effective Method for Extractive Summarization Based on Sentence Embeddings
Léo Bouscarrat, Antoine Bonnefoy, Thomas Peel, Cécile Pereira
http://arxiv.org/abs/1907.07323v1
• [cs.CL]SUMBT: Slot-Utterance Matching for Universal and Scalable Belief Tracking
Hwaran Lee, Jinsik Lee, Tae-Yoon Kim
http://arxiv.org/abs/1907.07421v1
• [cs.CL]You Write Like You Eat: Stylistic variation as a predictor of social stratification
Angelo Basile, Albert Gatt, Malvina Nissim
http://arxiv.org/abs/1907.07265v1
• [cs.CR]Decentralized & Collaborative AI on Blockchain
Justin D. Harris, Bo Waggoner
http://arxiv.org/abs/1907.07247v1
• [cs.CR]Dynamic Malware Analysis with Feature Engineering and Feature Learning
Zhaoqi Zhang, Panpan Qi, Wei Wang
http://arxiv.org/abs/1907.07352v1
• [cs.CR]Helen: Maliciously Secure Coopetitive Learning for Linear Models
Wenting Zheng, Raluca Ada Popa, Joseph E. Gonzalez, Ion Stoica
http://arxiv.org/abs/1907.07212v1
• [cs.CR]Real-time Evasion Attacks with Physical Constraints on Deep Learning-based Anomaly Detectors in Industrial Control Systems
Alessandro Erba, Riccardo Taormina, Stefano Galelli, Marcello Pogliani, Michele Carminati, Stefano Zanero, Nils Ole Tippenhauer
http://arxiv.org/abs/1907.07487v1
• [cs.CV]A Link Between the Multiplicative and Additive Functional Asplund’s Metrics
Guillaume Noyel
http://arxiv.org/abs/1907.07509v1
• [cs.CV]AVDNet: A Small-Sized Vehicle Detection Network for Aerial Visual Data
Murari Mandal, Manal Shah, Prashant Meena, Sanhita Devi, Santosh Kumar Vipparthi
http://arxiv.org/abs/1907.07477v1
• [cs.CV]Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming
Claudio Michaelis, Benjamin Mitzkus, Robert Geirhos, Evgenia Rusak, Oliver Bringmann, Alexander S. Ecker, Matthias Bethge, Wieland Brendel
http://arxiv.org/abs/1907.07484v1
• [cs.CV]Deep Metric Learning with Alternating Projections onto Feasible Sets
Oğul Can, Yeti Ziya Gürbüz, A. Aydın Alatan
http://arxiv.org/abs/1907.07585v1
• [cs.CV]FOSNet: An End-to-End Trainable Deep Neural Network for Scene Recognition
Hongje Seong, Junhyuk Hyun, Euntai Kim
http://arxiv.org/abs/1907.07570v1
• [cs.CV]Half a Percent of Labels is Enough: Efficient Animal Detection in UAV Imagery using Deep CNNs and Active Learning
Benjamin Kellenberger, Diego Marcos, Sylvain Lobry, Devis Tuia
http://arxiv.org/abs/1907.07319v1
• [cs.CV]Multi-Adapter RGBT Tracking
Chenglong Li, Andong Lu, Aihua Zheng, Zhengzheng Tu, Jin Tang
http://arxiv.org/abs/1907.07485v1
• [cs.CV]News Cover Assessment via Multi-task Learning
Zixun Sun, Shuang Zhao, Chengwei Zhu, Xiao Chen
http://arxiv.org/abs/1907.07581v1
• [cs.CV]OGNet: Salient Object Detection with Output-guided Attention Module
Shiping Zhu, Lanyun Zhu
http://arxiv.org/abs/1907.07449v1
• [cs.CV]Real-time Vision-based Depth Reconstruction with NVidia Jetson
Andrey Bokovoy, Kirill Muravyev, Konstantin Yakovlev
http://arxiv.org/abs/1907.07210v1
• [cs.CV]Relation Network for Multi-label Aerial Image Classification
Yuansheng Hua, Lichao Mou, Xiao Xiang Zhu
http://arxiv.org/abs/1907.07274v1
• [cs.CV]Robustness properties of Facebook’s ResNeXt WSL models
A. Emin Orhan
http://arxiv.org/abs/1907.07640v1
• [cs.CV]Scene Motion Decomposition for Learnable Visual Odometry
Igor Slinko, Anna Vorontsova, Filipp Konokhov, Olga Barinova, Anton Konushin
http://arxiv.org/abs/1907.07227v1
• [cs.CV]Style Transfer Applied to Face Liveness Detection with User-Centered Models
Israel A. Laurensi R., Luciana T. Menon, Manoel Camillo O. Penna N., Alessandro L. Koerich, Alceu S. Britto Jr
http://arxiv.org/abs/1907.07270v1
• [cs.CV]Towards Data-Driven Automatic Video Editing
Sergey Podlesnyy
http://arxiv.org/abs/1907.07345v1
• [cs.CV]Towards Markerless Grasp Capture
Samarth Brahmbhatt, Charles C. Kemp, James Hays
http://arxiv.org/abs/1907.07388v1
• [cs.CV]Underexposed Image Correction via Hybrid Priors Navigated Deep Propagation
Risheng Liu, Long Ma, Yuxi Zhang, Xin Fan, Zhongxuan Luo
http://arxiv.org/abs/1907.07408v1
• [cs.CY]Canada Protocol: an ethical checklist for the use of Artificial Intelligence in Suicide Prevention and Mental Health
Carl-Maria Mörch, Abhishek Gupta, Brian L. Mishara
http://arxiv.org/abs/1907.07493v1
• [cs.CY]Inferring Tracker-Advertiser Relationships in the Online Advertising Ecosystem using Header Bidding
John Cook, Rishab Nithyanand, Zubair Shafiq
http://arxiv.org/abs/1907.07275v1
• [cs.CY]Truck Traffic Monitoring with Satellite Images
Lynn H. Kaack, George H. Chen, M. Granger Morgan
http://arxiv.org/abs/1907.07660v1
• [cs.DC]$\texttt{DeepSqueeze}$: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression
Hanlin Tang, Xiangru Lian, Shuang Qiu, Lei Yuan, Ce Zhang, Tong Zhang, Ji Liu
http://arxiv.org/abs/1907.07346v1
• [cs.DC]Partitioning Graphs for the Cloud using Reinforcement Learning
Mohammad Hasanzadeh Mofrad, Rami Melhem, Mohammad Hammoud
http://arxiv.org/abs/1907.06768v2
• [cs.DS]Seedless Graph Matching via Tail of Degree Distribution for Correlated Erdos-Renyi Graphs
Mahdi Bozorg, Saber Salehkaleybar, Matin Hashemi
http://arxiv.org/abs/1907.06334v2
• [cs.GR]RayTracer.jl: A Differentiable Renderer that supports Parameter Optimization for Scene Reconstruction
Avik Pal
http://arxiv.org/abs/1907.07198v1
• [cs.HC]Conversational Help for Task Completion and Feature Discovery in Personal Assistants
Madan Gopal Jhawar, Vipindeep Vangala, Nishchay Sharma, Ankur Hayatnagarkar, Mansi Saxena, Swati Valecha
http://arxiv.org/abs/1907.07564v1
• [cs.HC]End-To-End Prediction of Emotion From Heartbeat Data Collected by a Consumer Fitness Tracker
Ross Harper, Joshua Southern
http://arxiv.org/abs/1907.07327v1
• [cs.HC]Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics
Yuxin Ma, Tiankai Xie, Jundong Li, Ross Maciejewski
http://arxiv.org/abs/1907.07296v1
• [cs.HC]MedCATTrainer: A Biomedical Free Text Annotation Interface with Active Learning and Research Use Case Specific Customisation
Thomas Searle, Zeljko Kraljevic, Rebecca Bendayan, Daniel Bean, Richard Dobson
http://arxiv.org/abs/1907.07322v1
• [cs.IR]Leveraging Linguistic Characteristics for Bipolar Disorder Recognition with Gender Differences
Yen-Hao Huang, Yi-Hsin Chen, Fernando Henrique Calderon Alvarado, Ssu-Rui Lee, Shu-I Wu, Yuwen Lai, Yi-Shin Chen
http://arxiv.org/abs/1907.07366v1
• [cs.IR]On the Importance of News Content Representation in Hybrid Neural Session-based Recommender Systems
Gabriel de Souza P. Moreira, Dietmar Jannach, Adilson Marques da Cunha
http://arxiv.org/abs/1907.07629v1
• [cs.IR]The Role of Local Intrinsic Dimensionality in Benchmarking Nearest Neighbor Search
Martin Aumüller, Matteo Ceccarello
http://arxiv.org/abs/1907.07387v1
• [cs.IR]Unbiased Learning to Rank: Counterfactual and Online Approaches
Harrie Oosterhuis, Rolf Jagerman, Maarten de Rijke
http://arxiv.org/abs/1907.07260v1
• [cs.IT]A Note on Linear Complementary Pairs of Group Codes
Martino Borello, Javier de la Cruz, Wolfgang Willems
http://arxiv.org/abs/1907.07506v1
• [cs.IT]Inference-Based Resource Allocation for Multi-Cell Backscatter Sensor Networks
Panos N. Alevizos, Aggelos Bletsas
http://arxiv.org/abs/1907.07251v1
• [cs.IT]Leveraging online learning for CSS in frugal IoT network
Nancy Nayak, Vishnu Raj, Sheetal Kalyani
http://arxiv.org/abs/1907.07201v1
• [cs.IT]Multi-Antenna Covert Communications with Random Access Protocol
Weile Zhang, Nan Zhao, Shun Zhang, F. Richard Yu
http://arxiv.org/abs/1907.07481v1
• [cs.IT]Optimal Energy Allocation and Task Offloading Policy for Wireless Powered Mobile Edge Computing Systems
Feng Wang, Jie Xu, Shuguang Cui
http://arxiv.org/abs/1907.07565v1
• [cs.IT]Privacy-Aware Location Sharing with Deep Reinforcement Learning
Ecenaz Erdemir, Pier Luigi Dragotti, Deniz Gunduz
http://arxiv.org/abs/1907.07606v1
• [cs.IT]Scalar Quantizer Design for Two-Way Channels
Saeed Rezazadeh, Fady Alajaji, Wai-Yip Chan
http://arxiv.org/abs/1907.07269v1
• [cs.IT]Scheduling to Minimize Age of Synchronization in Wireless Broadcast Networks with Random Updates
Haoyue Tang, Jintao Wang, Zihan Tang, Jian Song
http://arxiv.org/abs/1907.07380v1
• [cs.IT]Sparse Subspace Clustering via Two-Step Reweighted L1-Minimization: Algorithm and Provable Neighbor Recovery Rates
Jwo-Yuh Wu, Liang-Chi Huang, Ming-Hsun Yang, Chun-Hung Liu
http://arxiv.org/abs/1907.07359v1
• [cs.LG]$t$-$k$-means: A $k$-means Variant with Robustness and Stability
Yang Zhang, Qingtao Tang, Yiming Li, Weipeng Huang, Shutao Xia
http://arxiv.org/abs/1907.07442v1
• [cs.LG]A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI
Erico Tjoa, Cuntai Guan
http://arxiv.org/abs/1907.07374v1
• [cs.LG]Adversarial Security Attacks and Perturbations on Machine Learning and Deep Learning Methods
Arif Siddiqi
http://arxiv.org/abs/1907.07291v1
• [cs.LG]An Embedding Framework for Consistent Polyhedral Surrogates
Jessie Finocchiaro, Rafael Frongillo, Bo Waggoner
http://arxiv.org/abs/1907.07330v1
• [cs.LG]An Inductive Synthesis Framework for Verifiable Reinforcement Learning
He Zhu, Zikang Xiong, Stephen Magill, Suresh Jagannathan
http://arxiv.org/abs/1907.07273v1
• [cs.LG]AquaSight: Automatic Water Impurity Detection Utilizing Convolutional Neural Networks
Ankit Gupta, Elliott Ruebush
http://arxiv.org/abs/1907.07573v1
• [cs.LG]Block based Singular Value Decomposition approach to matrix factorization for recommender systems
Prasad Bhavana, Vikas Kumar, Vineet Padmanabhan
http://arxiv.org/abs/1907.07410v1
• [cs.LG]DeepTrax: Embedding Graphs of Financial Transactions
C. Bayan Bruss, Anish Khazane, Jonathan Rider, Richard Serpe, Antonia Gogoglou, Keegan E. Hines
http://arxiv.org/abs/1907.07225v1
• [cs.LG]FAHT: An Adaptive Fairness-aware Decision Tree Classifier
Wenbin Zhang, Eirini Ntoutsi
http://arxiv.org/abs/1907.07237v1
• [cs.LG]Fairness-enhancing interventions in stream classification
Vasileios Iosifidis, Thi Ngoc Han Tran, Eirini Ntoutsi
http://arxiv.org/abs/1907.07223v1
• [cs.LG]Feature Selection via Mutual Information: New Theoretical Insights
Mario Beraha, Alberto Maria Metelli, Matteo Papini, Andrea Tirinzoni, Marcello Restelli
http://arxiv.org/abs/1907.07384v1
• [cs.LG]Improving Heart Rate Variability Measurements from Consumer Smartwatches with Machine Learning
Martin Maritsch, Caterina Bérubé, Mathias Kraus, Vera Lehmann, Thomas Züger, Stefan Feuerriegel, Tobias Kowatsch, Felix Wortmann
http://arxiv.org/abs/1907.07496v1
• [cs.LG]Improving Outbreak Detection with Stacking of Statistical Surveillance Methods
Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
http://arxiv.org/abs/1907.07464v1
• [cs.LG]Learnability for the Information Bottleneck
Tailin Wu, Ian Fischer, Isaac L. Chuang, Max Tegmark
http://arxiv.org/abs/1907.07331v1
• [cs.LG]Learning Multimodal Fixed-Point Weights using Gradient Descent
Lukas Enderich, Fabian Timm, Lars Rosenbaum, Wolfram Burgard
http://arxiv.org/abs/1907.07220v1
• [cs.LG]Low-Shot Classification: A Comparison of Classical and Deep Transfer Machine Learning Approaches
Peter Usherwood, Steven Smit
http://arxiv.org/abs/1907.07543v1
• [cs.LG]Mitigating Uncertainty in Document Classification
Xuchao Zhang, Fanglan Chen, Chang-Tien Lu, Naren Ramakrishnan
http://arxiv.org/abs/1907.07590v1
• [cs.LG]Online Local Boosting: improving performance in online decision trees
Victor G. Turrisi da Costa, Saulo Martiello Mastelini, André C. Ponce de Leon Ferreira de Carvalho, Sylvio Barbon Jr
http://arxiv.org/abs/1907.07207v1
• [cs.LG]PPO Dash: Improving Generalization in Deep Reinforcement Learning
Joe Booth
http://arxiv.org/abs/1907.06704v2
• [cs.LG]Remaining Useful Lifetime Prediction via Deep Domain Adaptation
Paulo R. de O. da Costa, Alp Akcay, Yingqian Zhang, Uzay Kaymak
http://arxiv.org/abs/1907.07480v1
• [cs.LG]Self-Attentive Hawkes Processes
Qiang Zhang, Aldo Lipani, Omer Kirnap, Emine Yilmaz
http://arxiv.org/abs/1907.07561v1
• [cs.LG]Subspace Inference for Bayesian Deep Learning
Pavel Izmailov, Wesley J. Maddox, Polina Kirichenko, Timur Garipov, Dmitry Vetrov, Andrew Gordon Wilson
http://arxiv.org/abs/1907.07504v1
• [cs.LG]Towards Understanding Generalization in Gradient-Based Meta-Learning
Simon Guiroy, Vikas Verma, Christopher Pal
http://arxiv.org/abs/1907.07287v1
• [cs.NE]Iterative temporal differencing with random synaptic feedback weights support error backpropagation for deep learning
Aras R. Dargazany
http://arxiv.org/abs/1907.07255v1
• [cs.NE]Machine Learning based Simulation Optimisation for Trailer Management
Dylan Rijnen, Jason Rhuggenaath, Paulo R. de O. da Costa, Yingqian Zhang
http://arxiv.org/abs/1907.07568v1
• [cs.NI]Achieving Ultra-Reliable Communication via CRAN-Enabled Diversity Schemes
Binod Kharel, Onel L. Alcaraz López, Hirley Alves, Matti Latva-aho
http://arxiv.org/abs/1907.07476v1
• [cs.NI]Caching as an Image Characterization Problem using Deep Convolutional Neural Networks
Yantong Wang, Vasilis Friderikos
http://arxiv.org/abs/1907.07263v1
• [cs.NI]Energy-Efficient Power Control of Train-ground mmWave Communication for High Speed Trains
Lei Wang, Bo Ai, Yong Niu, Xia Chen, Pan Hui
http://arxiv.org/abs/1907.07427v1
• [cs.PL]Zygote: A Differentiable Programming System to Bridge Machine Learning and Scientific Computing
Mike Innes, Alan Edelman, Keno Fischer, Chris Rackauckus, Elliot Saba, Viral B Shah, Will Tebbutt
http://arxiv.org/abs/1907.07587v1
• [cs.RO]A General Framework of Learning Multi-Vehicle Interaction Patterns from Videos
Chengyuan Zhang, Jiacheng Zhu, Wenshuo Wang, Ding Zhao
http://arxiv.org/abs/1907.07315v1
• [cs.RO]Cooperative UAVs Gas Monitoring using Distributed Consensus
Daniele Facinelli, Matteo Larcher, Davide Brunelli, Daniele Fontanelli
http://arxiv.org/abs/1907.07279v1
• [cs.RO]Edge Detection for Event Cameras using Intra-pixel-area Events
Sangil Lee, Haram Kim, H. Jin Kim
http://arxiv.org/abs/1907.07469v1
• [cs.RO]Evaluation of a 1-DOF Hand Exoskeleton for Neuromuscular Rehabilitation
Xinalian Zhou, Ashley Mont, Sergei Adamovich
http://arxiv.org/abs/1907.07311v1
• [cs.RO]Fly Safe: Aerial Swarm Robotics using Force Field Particle Swarm Optimisation
Lauren Parker, James Butterworth, Shan Luo
http://arxiv.org/abs/1907.07647v1
• [cs.RO]Learning Variable Impedance Control for Contact Sensitive Tasks
Miroslav Bogdanovic, Majid Khadiv, Ludovic Righetti
http://arxiv.org/abs/1907.07500v1
• [cs.RO]Leveraging Experience in Lazy Search
Mohak Bhardwaj, Sanjiban Choudhury, Byron Boots, Siddhartha Srinivasa
http://arxiv.org/abs/1907.07238v1
• [cs.RO]Stereo Event Lifetime and Disparity Estimation for Dynamic Vision Sensors
Antea Hadviger, Ivan Marković, Ivan Petrović
http://arxiv.org/abs/1907.07518v1
• [cs.RO]Stochastic Optimization for Trajectory Planning with Heteroscedastic Gaussian Processes
Luka Petrović, Juraj Peršić, Marija Seder, Ivan Marković
http://arxiv.org/abs/1907.07521v1
• [cs.RO]Tactile Model O: Fabrication and testing of a 3d-printed, three-fingered tactile robot hand
Alex Church, Jasper James, Luke Cramphorn, Nathan Lepora
http://arxiv.org/abs/1907.07535v1
• [cs.RO]Towards Blockchain-based Multi-Agent Robotic Systems: Analysis, Classification and Applications
Ilya Afanasyev, Alexander Kolotov, Ruslan Rezin, Konstantin Danilov, Manuel Mazzara, Subham Chakraborty, Alexey Kashevnik, Andrey Chechulin, Aleksandr Kapitonov, Vladimir Jotsov, Andon Topalov, Nikola Shakev, Sevil Ahmed
http://arxiv.org/abs/1907.07433v1
• [cs.RO]Understanding Teacher Gaze Patterns for Robot Learning
Akanksha Saran, Elaine Schaertl Short, Andrea Thomaz, Scott Niekum
http://arxiv.org/abs/1907.07202v1
• [cs.SE]The General Data Protection Regulation: Requirements, Architectures, and Constraints
Kalle Hjerppe, Jukka Ruohonen, Ville Leppänen
http://arxiv.org/abs/1907.07498v1
• [cs.SI]Computational Human Dynamics
Márton Karsai
http://arxiv.org/abs/1907.07475v1
• [cs.SI]DeepNC: Deep Generative Network Completion
Cong Tran, Won-Yong Shin, Andreas Spitz, Michael Gertz
http://arxiv.org/abs/1907.07381v1
• [cs.SI]Fairness and Diversity in the Recommendation and Ranking of Participatory Media Content
Muskaan, Mehak Preet Dhaliwal, Aaditeshwar Seth
http://arxiv.org/abs/1907.07253v1
• [cs.SI]Homophily as a process generating social networks: insights from Social Distance Attachment model
Szymon Talaga, Andrzej Nowak
http://arxiv.org/abs/1907.07055v2
• [cs.SI]Modeling Human Annotation Errors to Design Bias-Aware Systems for Social Stream Processing
Rahul Pandey, Carlos Castillo, Hemant Purohit
http://arxiv.org/abs/1907.07228v1
• [cs.SI]Relevancy Classification of Multimodal Social Media Streams for Emergency Services
Ganesh Nalluru, Rahul Pandey, Hemant Purohit
http://arxiv.org/abs/1907.07240v1
• [cs.SI]Towards Reliable Online Clickbait Video Detection: A Content-Agnostic Approach
Lanyu Shang, Daniel Zhang, Michael Wang, Shuyue Lai, Dong Wang
http://arxiv.org/abs/1907.07604v1
• [econ.EM]Consistency and matching without replacement
Fredrik Sävje
http://arxiv.org/abs/1907.07288v1
• [eess.AS]AP19-OLR Challenge: Three Tasks and Their Baselines
Zhiyuan Tang, Dong Wang, Liming Song
http://arxiv.org/abs/1907.07626v1
• [eess.IV]CLCI-Net: Cross-Level fusion and Context Inference Networks for Lesion Segmentation of Chronic Stroke
Hao Yang, Weijian Huang, Kehan Qi, Cheng Li, Xinfeng Liu, Meiyun Wang, Hairong Zheng, Shanshan Wang
http://arxiv.org/abs/1907.07008v2
• [eess.IV]Deep Learning for Pneumothorax Detection and Localization in Chest Radiographs
André Gooßen, Hrishikesh Deshpande, Tim Harder, Evan Schwab, Ivo Baltruschat, Thusitha Mabotuwana, Nathan Cross, Axel Saalbach
http://arxiv.org/abs/1907.07324v1
• [eess.SP]A Neural Network Detector for Spectrum Sensing under Uncertainties
Ziyu Ye, Qihang Peng, Kelly Levick, Hui Rong, Andrew Gilman, Pamela Cosman, Larry Milstein
http://arxiv.org/abs/1907.07326v1
• [eess.SP]Comparison of Neural Network Architectures for Spectrum Sensing
Ziyu Ye, Andrew Gilman, Qihang Peng, Kelly Levick, Pamela Cosman, Larry Milstein
http://arxiv.org/abs/1907.07321v1
• [eess.SP]Deciphering Dynamical Nonlinearities in Short Time Series Using Recurrent Neural Networks
Radhakrishnan Nagarajan
http://arxiv.org/abs/1907.07181v1
• [eess.SP]Deep learning scheme for microwave photonic analog broadband signal recovery
Shaofu Xu, Rui Wang, Jianping Chen, Lei Yu, Weiwen Zou
http://arxiv.org/abs/1907.07312v1
• [eess.SP]Near-Field Joint Localization and Synchronization
Henk Wymeersch
http://arxiv.org/abs/1907.07411v1
• [math-ph]Distribution of the ratio of two consecutive level spacings in orthogonal to unitary crossover ensembles
Ayana Sarkar, Manuja Kothiyal, Santosh Kumar
http://arxiv.org/abs/1907.07548v1
• [math.CO]Tangles in the social sciences
Reinhard Diestel
http://arxiv.org/abs/1907.07341v1
• [math.OC]Dynamic optimization with side information
Dimitris Bertsimas, Christopher McCord, Bradley Sturt
http://arxiv.org/abs/1907.07307v1
• [math.OC]Feature-driven Improvement of Renewable Energy Forecasting and Trading
Miguel Á. Muñoz, Juan M. Morales, Salvador Pineda
http://arxiv.org/abs/1907.07580v1
• [math.PR]On the cut-off phenomenon for the maximum of a sampling of Ornstein-Uhlenbeck processes
Gerardo Barrera
http://arxiv.org/abs/1907.07618v1
• [math.PR]On the geometry of polytopes generated by heavy-tailed random vectors
Olivier Guédon, Felix Krahmer, Christian Kümmerle, Shahar Mendelson, Holger Rauhut
http://arxiv.org/abs/1907.07258v1
• [math.ST]What is… a Markov basis?
Sonja Petrović
http://arxiv.org/abs/1907.07320v1
• [physics.app-ph]Noise Analysis of Photonic Modulator Neurons
Thomas Ferreira de Lima, Alexander N. Tait, Hooman Saeidi, Mitchell A. Nahmias, Hsuan-Tung Peng, Siamak Abbaslou, Bhavin J. Shastri, Paul R. Prucnal
http://arxiv.org/abs/1907.07325v1
• [physics.soc-ph]Constructions and properties of a class of random scale-free networks
Xiaomin Wang, Fei Ma
http://arxiv.org/abs/1907.07406v1
• [quant-ph]Photonic architecture for reinforcement learning
Fulvio Flamini, Arne Hamann, Sofiène Jerbi, Lea M. Trenkwalder, Hendrik Poulsen Nautrup, Hans J. Briegel
http://arxiv.org/abs/1907.07503v1
• [stat.AP]Self Organizing Supply Chains for Micro-Prediction: Present and Future uses of the ROAR Protocol
Peter Cotton
http://arxiv.org/abs/1907.07514v1
• [stat.AP]Spherical data handling and analysis with R package rcosmo
Daniel Fryer, Andriy Olenko
http://arxiv.org/abs/1907.07439v1
• [stat.ME]A Multivariate Extreme Value Theory Approach to Anomaly Clustering and Visualization
Maël Chiapino, Stéphan Clémençon, Vincent Feuillard, Anne Sabourin
http://arxiv.org/abs/1907.07523v1
• [stat.ME]Assessing Treatment Effect Variation in Observational Studies: Results from a Data Challenge
Carlos Carvalho, Avi Feller, Jared Murray, Spencer Woody, David Yeager
http://arxiv.org/abs/1907.07592v1
• [stat.ME]Factor copula models for mixed data
Sayed H. Kadhem, Aristidis K. Nikoloulopoulos
http://arxiv.org/abs/1907.07395v1
• [stat.ME]Optimal Sampling for Generalized Linear Models under Measurement Constraints
Tao Zhang, Yang Ning, David Ruppert
http://arxiv.org/abs/1907.07309v1
• [stat.ME]Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics
Guido W. Imbens
http://arxiv.org/abs/1907.07271v1
• [stat.ML]Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing
Zhiqi Bu, Jason Klusowski, Cynthia Rush, Weijie Su
http://arxiv.org/abs/1907.07502v1
• [stat.ML]Clustering Activity-Travel Behavior Time Series using Topological Data Analysis
Renjie Chen, Jingyue Zhang, Nalini Ravishanker, Karthik Konduri
http://arxiv.org/abs/1907.07603v1
• [stat.ML]Output-weighted optimal sampling for Bayesian regression and rare event statistics using few samples
Themistoklis P. Sapsis
http://arxiv.org/abs/1907.07552v1