cs.AI - 人工智能
cs.CL - 计算与语言
cs.CR - 加密与安全
cs.CV - 机器视觉与模式识别
cs.CY - 计算与社会
cs.DB - 数据库
cs.DC - 分布式、并行与集群计算
cs.GT - 计算机科学与博弈论
cs.HC - 人机接口
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.RO - 机器人学
cs.SI - 社交网络与信息网络
cs.SY - 系统与控制
econ.GN - 一般经济学
eess.SP - 信号处理
math.CO - 组合数学
math.OC - 优化与控制
math.PR - 概率
math.ST - 统计理论
physics.ins-det - 仪器和探测器
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
stat.OT - 其他统计学
• [cs.AI]An Approach to Characterize Graded Entailment of Arguments through a Label-based Framework
• [cs.AI]An approach to Decision Making based on Dynamic Argumentation Systems
• [cs.AI]Applying Active Diagnosis to Space Systems by On-Board Control Procedures
• [cs.AI]Bipolar in Temporal Argumentation Framework
• [cs.AI]Competitive Bridge Bidding with Deep Neural Networks
• [cs.AI]Complexity Results and Algorithms for Bipolar Argumentation
• [cs.AI]Dealing with Qualitative and Quantitative Features in Legal Domains
• [cs.AI]The Regretful Agent: Heuristic-Aided Navigation through Progress Estimation
• [cs.AI]Using a Segmenting Description approach in Multiple Criteria Decision Aiding
• [cs.CL]Exploiting Emotions for Fake News Detection on Social Media
• [cs.CL]Improving Cross-Domain Chinese Word Segmentation with Word Embeddings
• [cs.CL]Language and Dialect Identification of Cuneiform Texts
• [cs.CL]SECNLP: A Survey of Embeddings in Clinical Natural Language Processing
• [cs.CR]DeepStego: Protecting Intellectual Property of Deep Neural Networks by Steganography
• [cs.CV]A DenseNet Based Approach for Multi-Frame In-Loop Filter in HEVC
• [cs.CV]Deep Learning Based Motion Planning For Autonomous Vehicle Using Spatiotemporal LSTM Network
• [cs.CV]Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search
• [cs.CV]Distinguishing mirror from glass: A 'big data' approach to material perception
• [cs.CV]EdgeStereo: An Effective Multi-Task Learning Network for Stereo Matching and Edge Detection
• [cs.CV]FastReg: Fast Non-Rigid Registration via Accelerated Optimisation on the Manifold of Diffeomorphisms
• [cs.CV]Fine-grained lesion annotation in CT images with knowledge mined from radiology reports
• [cs.CV]Frustum ConvNet: Sliding Frustums to Aggregate Local Point-Wise Features for Amodal 3D Object Detection
• [cs.CV]HexagDLy - Processing hexagonally sampled data with CNNs in PyTorch
• [cs.CV]Hue Modification Localization By Pair Matching
• [cs.CV]Improve Object Detection by Data Enhancement based on Generative Adversarial Nets
• [cs.CV]Learning a smooth kernel regularizer for convolutional neural networks
• [cs.CV]Learning of Image Dehazing Models for Segmentation Tasks
• [cs.CV]Leveraging Shape Completion for 3D Siamese Tracking
• [cs.CV]M-VAD Names: a Dataset for Video Captioning with Naming
• [cs.CV]MS-TCN: Multi-Stage Temporal Convolutional Network for Action Segmentation
• [cs.CV]O-GAN: Extremely Concise Approach for Auto-Encoding Generative Adversarial Networks
• [cs.CV]On measuring the iconicity of a face
• [cs.CV]Real-time Multiple People Hand Localization in 4D Point Clouds
• [cs.CV]Selective Sensor Fusion for Neural Visual-Inertial Odometry
• [cs.CV]TKD: Temporal Knowledge Distillation for Active Perception
• [cs.CV]TableBank: Table Benchmark for Image-based Table Detection and Recognition
• [cs.CV]The H3D Dataset for Full-Surround 3D Multi-Object Detection and Tracking in Crowded Urban Scenes
• [cs.CV]Unsupervised Domain-Specific Deblurring via Disentangled Representations
• [cs.CV]Unsupervised Rank-Preserving Hashing for Large-Scale Image Retrieval
• [cs.CV]Using Big Five Personality Model to Detect Cultural Aspects in Crowds
• [cs.CV]Virtual Ground Truth, and Pre-selection of 3D Interest Points for Improved Repeatability Evaluation of 2D Detectors
• [cs.CY]Analysis of the Influence of Internet TV Station on Wikipedia Page Views
• [cs.DB]Voyageur: An Experiential Travel Search Engine
• [cs.DC]BOINC: A Platform for Volunteer Computing
• [cs.DC]Blockchain Meets Database: Design and Implementation of a Blockchain Relational Database
• [cs.DC]Communication Aspects of the Integration of Wireless IoT Devices with Distributed Ledger Technology
• [cs.DC]Flexible MEC service consumption through edge host zoning in 5G networks
• [cs.DC]Lessons Learned from a Decade of Providing Interactive, On-Demand High Performance Computing to Scientists and Engineers
• [cs.GT]Multi-Agent Learning in Network Zero-Sum Games is a Hamiltonian System
• [cs.HC]A Serious Game for Introducing Software Engineering Ethics to University Students
• [cs.IT]Approximations of Shannon Mutual Information for Discrete Variables with Applications to Neural Population Coding
• [cs.IT]Closed-Loop Sparse Channel Estimation for Wideband MmWave FD-MIMO Systems
• [cs.IT]Cooperative Caching in Fog Radio Access Networks: A Graph-based Approach
• [cs.IT]DoF Region of the MISO BC with Partial CSIT: Proof by Inductive Fourier-Motzkin Elimination
• [cs.IT]Gradient Coding with Clustering and Multi-message Communication
• [cs.IT]Learning to Branch: Accelerating Resource Allocation in Wireless Networks
• [cs.IT]Multi-tone Signal Optimization for Wireless Power Transfer in the Presence of Wireless Communication Links
• [cs.IT]Noncoherent Multiuser Massive SIMO for Low-Latency Industrial IoT Communications
• [cs.IT]Noncoherent and Non-orthogonal Massive SIMO for Critical Industrial IoT Communications
• [cs.IT]On the Performance Gain of NOMA over OMA in Uplink Communication Systems
• [cs.IT]Performance Analysis of NOMA-based Cooperative Relaying in α - μ Fading Channels
• [cs.IT]Reduced-rank Analysis of the Total Least Squares
• [cs.IT]Twin-Timescale Radio Resource Management for Ultra-Reliable and Low-Latency Vehicular Networks
• [cs.LG]A Deep Learning based approach to VM behavior identification in cloud systems
• [cs.LG]A Novel Efficient Approach with Data-Adaptive Capability for OMP-based Sparse Subspace Clustering
• [cs.LG]Causal Discovery and Hidden Driving Force Estimation from Nonstationary/Heterogeneous Data
• [cs.LG]Copying Machine Learning Classifiers
• [cs.LG]Do Neural Networks Show Gestalt Phenomena? An Exploration of the Law of Closure
• [cs.LG]Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment
• [cs.LG]Efficient Winograd or Cook-Toom Convolution Kernel Implementation on Widely Used Mobile CPUs
• [cs.LG]Gated Graph Convolutional Recurrent Neural Networks
• [cs.LG]Generative Adversarial Nets for Robust Scatter Estimation: A Proper Scoring Rule Perspective
• [cs.LG]Generative Design Exploration by Integrating Deep Generative Models and Topology Optimization
• [cs.LG]Hedging the Drift: Learning to Optimize under Non-Stationarity
• [cs.LG]L 1-norm double backpropagation adversarial defense
• [cs.LG]Making the Dynamic Time Warping Distance Warping-Invariant
• [cs.LG]Model Primitive Hierarchical Lifelong Reinforcement Learning
• [cs.LG]Modeling Social Group Communication with Multi-Agent Imitation Learning
• [cs.LG]Multiple-Kernel Dictionary Learning for Reconstruction and Clustering of Unseen Multivariate Time-series
• [cs.LG]Online Data Poisoning Attack
• [cs.LG]PDP: A General Neural Framework for Learning Constraint Satisfaction Solvers
• [cs.LG]Probabilistic Modeling for Novelty Detection with Applications to Fraud Identification
• [cs.LG]Statistical Guarantees for the Robustness of Bayesian Neural Networks
• [cs.LG]Streaming Batch Eigenupdates for Hardware Neuromorphic Networks
• [cs.LG]Ternary Hybrid Neural-Tree Networks for Highly Constrained IoT Applications
• [cs.LG]The Complexity of Morality: Checking Markov Blanket Consistency with DAGs via Morality
• [cs.LG]The Lottery Ticket Hypothesis at Scale
• [cs.LG]The Vulnerabilities of Graph Convolutional Networks: Stronger Attacks and Defensive Techniques
• [cs.LG]Towards Understanding Chinese Checkers with Heuristics, Monte Carlo Tree Search, and Deep Reinforcement Learning
• [cs.LG]Two-Stream Multi-Channel Convolutional Neural Network (TM-CNN) for Multi-Lane Traffic Speed Prediction Considering Traffic Volume Impact
• [cs.LG]Ultra-Scalable Spectral Clustering and Ensemble Clustering
• [cs.LG]Universal approximations of permutation invariant/equivariant functions by deep neural networks
• [cs.LG]What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features
• [cs.NE]Two-level protein folding optimization on a three-dimensional AB off-lattice model
• [cs.NE]Visualisation of Pareto Front Approximation: A Short Survey and Empirical Comparisons
• [cs.NI]Socially-Aware Congestion Control in Ad-Hoc Networks: Current Status and The Way Forward
• [cs.RO]Automated Generation of Reactive Programs from Human Demonstration for Orchestration of Robot Behaviors
• [cs.RO]Creating Navigable Space from Sparse Noisy Map Points
• [cs.RO]Deep Active Localization
• [cs.RO]Episodic Learning with Control Lyapunov Functions for Uncertain Robotic Systems
• [cs.RO]Learning Exploration Policies for Navigation
• [cs.RO]Learning Latent Plans from Play
• [cs.RO]Mechanical Search: Multi-Step Retrieval of a Target Object Occluded by Clutter
• [cs.RO]Planning Grasps for Assembly Tasks
• [cs.RO]Robot Localization in Floor Plans Using a Room Layout Edge Extraction Network
• [cs.RO]Stochastic Sampling Simulation for Pedestrian Trajectory Prediction
• [cs.RO]Vision-Depth Landmarks and Inertial Fusion for Navigation in Degraded Visual Environments
• [cs.RO]Visual-Thermal Landmarks and Inertial Fusion for Navigation in Degraded Visual Environments
• [cs.SI]Less is More: Semi-Supervised Causal Inference for Detecting Pathogenic Users in Social Media
• [cs.SI]Selective Exposure shapes the Facebook News Diet
• [cs.SI]Trust and Trustworthiness in Social Recommender Systems
• [cs.SY]A behavior driven approach for sampling rare event situations for autonomous vehicles
• [econ.GN]Externalities in Knowledge Production: Evidence from a Randomized Field Experiment
• [eess.SP]Study of Sparsity-Aware Reduced-Dimension Beam-Doppler Space-Time Adaptive Processing
• [eess.SP]Towards Design Space Exploration and Optimization of Fast Algorithms for Convolutional Neural Networks (CNNs) on FPGAs
• [eess.SP]V2X System Architecture Utilizing Hybrid Gaussian Process-based Model Structures
• [math.CO]Probabilistic refinement of the asymptotic spectrum of graphs
• [math.OC]A Stochastic Trust Region Method for Non-convex Minimization
• [math.OC]Inertial Block Mirror Descent Method for Non-Convex Non-Smooth Optimization
• [math.OC]SGD without Replacement: Sharper Rates for General Smooth Convex Functions
• [math.PR]Theoretical guarantees for sampling and inference in generative models with latent diffusions
• [math.ST]Change Detection with the Kernel Cumulative Sum Algorithm
• [math.ST]Concentration-based confidence intervals for U-statistics
• [math.ST]Data Amplification: Instance-Optimal Property Estimation
• [math.ST]Local differential privacy: Elbow effect in optimal density estimation and adaptation over Besov ellipsoids
• [math.ST]Measuring and Controlling Bias for Some Bayesian Inferences and the Relation to Frequentist Criteria
• [math.ST]Multiscale clustering of nonparametric regression curves
• [math.ST]Tutorial: Deriving The Efficient Influence Curve for Large Models
• [physics.ins-det]Deep learning based pulse shape discrimination for germanium detectors
• [physics.soc-ph]Analysing Motifs in Multilayer Networks
• [q-bio.NC]Deep Learning for Cognitive Neuroscience
• [q-fin.ST]Influence of petroleum and gas trade on EU economies from the reduced Google matrix analysis of UN COMTRADE data
• [stat.AP]A Factor Stochastic Volatility Model with Markov-Switching Panic Regimes
• [stat.AP]The power disaggregation algorithms and their applications to demand dispatch
• [stat.CO]Convex Covariate Clustering for Classification
• [stat.CO]Quantifying Gait Changes Using Microsoft Kinect and Sample Entropy
• [stat.CO]Similarity-based Random Survival Forest
• [stat.ME]A multinomial Asymptotic Representation of Zenga's Discrete Index, its Influence Function and Data-driven Applications
• [stat.ME]Change-point detection for multivariate and non-Euclidean data with local dependency
• [stat.ME]Spike-and-Slab Group Lassos for Grouped Regression and Sparse Generalized Additive Models
• [stat.ME]Statistical approach to detection of signals by Monte Carlo singular spectrum analysis: Multiple testing
• [stat.ML]A New Approach to Adaptive Data Analysis and Learning via Maximal Leakage
• [stat.ML]Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future
• [stat.OT]The Fuzzy ROC
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• [cs.AI]An Approach to Characterize Graded Entailment of Arguments through a Label-based Framework
Maximiliano C. D. Budán, Gerardo I. Simari, Ignacio Viglizzo, Guillermo R. Simari
http://arxiv.org/abs/1903.01865v1
• [cs.AI]An approach to Decision Making based on Dynamic Argumentation Systems
Edgardo Ferretti, Luciano H. Tamargo, Alejandro J. Garcia, Marcelo L. Errecalde, Guillermo R. Simari
http://arxiv.org/abs/1903.01920v1
• [cs.AI]Applying Active Diagnosis to Space Systems by On-Board Control Procedures
Elodie Chanthery, Louise Travé-Massuyès, Yannick Pencolé, Régis De Ferluc, Brice Dellandrea
http://arxiv.org/abs/1903.01710v1
• [cs.AI]Bipolar in Temporal Argumentation Framework
Maximiliano C. D. Budán, Maria Laura Cobo, Diego C. Martinez, Guillermo R. Simari
http://arxiv.org/abs/1903.01874v1
• [cs.AI]Competitive Bridge Bidding with Deep Neural Networks
Jiang Rong, Tao Qin, Bo An
http://arxiv.org/abs/1903.00900v2
• [cs.AI]Complexity Results and Algorithms for Bipolar Argumentation
Amin Karamlou, Kristijonas Čyras, Francesca Toni
http://arxiv.org/abs/1903.01964v1
• [cs.AI]Dealing with Qualitative and Quantitative Features in Legal Domains
Maximiliano C. D. Budán, María Laura Cobo, Diego I. Martínez, Antonino Rotolo
http://arxiv.org/abs/1903.01966v1
• [cs.AI]The Regretful Agent: Heuristic-Aided Navigation through Progress Estimation
Chih-Yao Ma, Zuxuan Wu, Ghassan AlRegib, Caiming Xiong, Zsolt Kira
http://arxiv.org/abs/1903.01602v1
• [cs.AI]Using a Segmenting Description approach in Multiple Criteria Decision Aiding
Milosz Kadzinski, Jan Badura, Jose Rui Figueira
http://arxiv.org/abs/1903.01923v1
• [cs.CL]Exploiting Emotions for Fake News Detection on Social Media
Chuan Guo, Juan Cao, Xueyao Zhang, Kai Shu, Miao Yu
http://arxiv.org/abs/1903.01728v1
• [cs.CL]Improving Cross-Domain Chinese Word Segmentation with Word Embeddings
Yuxiao Ye, Weikang Li, Yue Zhang, Likun Qiu, Jian Sun
http://arxiv.org/abs/1903.01698v1
• [cs.CL]Language and Dialect Identification of Cuneiform Texts
Tommi Jauhiainen, Heidi Jauhiainen, Tero Alstola, Krister Lindén
http://arxiv.org/abs/1903.01891v1
• [cs.CL]SECNLP: A Survey of Embeddings in Clinical Natural Language Processing
Kalyan KS, S Sangeetha
http://arxiv.org/abs/1903.01039v2
• [cs.CR]DeepStego: Protecting Intellectual Property of Deep Neural Networks by Steganography
Zheng Li, Shanqing Guo
http://arxiv.org/abs/1903.01743v1
• [cs.CV]A DenseNet Based Approach for Multi-Frame In-Loop Filter in HEVC
Tianyi Li, Mai Xu, Ren Yang, Xiaoming Tao
http://arxiv.org/abs/1903.01648v1
• [cs.CV]Deep Learning Based Motion Planning For Autonomous Vehicle Using Spatiotemporal LSTM Network
Zhengwei Bai, Baigen Cai, Wei Shangguan, Linguo Chai
http://arxiv.org/abs/1903.01712v1
• [cs.CV]Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search
Abhimanyu Dubey, Laurens van der Maaten, Zeki Yalniz, Yixuan Li, Dhruv Mahajan
http://arxiv.org/abs/1903.01612v1
• [cs.CV]Distinguishing mirror from glass: A 'big data' approach to material perception
Hideki Tamura, Konrad E. Prokott, Roland W. Fleming
http://arxiv.org/abs/1903.01671v1
• [cs.CV]EdgeStereo: An Effective Multi-Task Learning Network for Stereo Matching and Edge Detection
Xiao Song, Xu Zhao, Liangji Fang, Hanwen Hu
http://arxiv.org/abs/1903.01700v1
• [cs.CV]FastReg: Fast Non-Rigid Registration via Accelerated Optimisation on the Manifold of Diffeomorphisms
Daniel Grzech, Loïc le Folgoc, Mattias P. Heinrich, Bishesh Khanal, Jakub Moll, Julia A. Schnabel, Ben Glocker, Bernhard Kainz
http://arxiv.org/abs/1903.01905v1
• [cs.CV]Fine-grained lesion annotation in CT images with knowledge mined from radiology reports
Ke Yan, Yifan Peng, Zhiyong Lu, Ronald M. Summers
http://arxiv.org/abs/1903.01505v1
• [cs.CV]Frustum ConvNet: Sliding Frustums to Aggregate Local Point-Wise Features for Amodal 3D Object Detection
Zhixin Wang, Kui Jia
http://arxiv.org/abs/1903.01864v1
• [cs.CV]HexagDLy - Processing hexagonally sampled data with CNNs in PyTorch
Constantin Steppa, Tim Lukas Holch
http://arxiv.org/abs/1903.01814v1
• [cs.CV]Hue Modification Localization By Pair Matching
Quoc-Tin Phan, Michele Vascotto, Giulia Boato
http://arxiv.org/abs/1903.01735v1
• [cs.CV]Improve Object Detection by Data Enhancement based on Generative Adversarial Nets
Wei Jiang, Na Ying
http://arxiv.org/abs/1903.01716v1
• [cs.CV]Learning a smooth kernel regularizer for convolutional neural networks
Reuben Feinman, Brenden M. Lake
http://arxiv.org/abs/1903.01882v1
• [cs.CV]Learning of Image Dehazing Models for Segmentation Tasks
Sébastien de Blois, Ihsen Hedhli, Christian Gagné
http://arxiv.org/abs/1903.01530v1
• [cs.CV]Leveraging Shape Completion for 3D Siamese Tracking
Silvio Giancola, Jesus Zarzar, Bernard Ghanem
http://arxiv.org/abs/1903.01784v1
• [cs.CV]M-VAD Names: a Dataset for Video Captioning with Naming
Stefano Pini, Marcella Cornia, Federico Bolelli, Lorenzo Baraldi, Rita Cucchiara
http://arxiv.org/abs/1903.01489v1
• [cs.CV]MS-TCN: Multi-Stage Temporal Convolutional Network for Action Segmentation
Yazan Abu Farha, Juergen Gall
http://arxiv.org/abs/1903.01945v1
• [cs.CV]O-GAN: Extremely Concise Approach for Auto-Encoding Generative Adversarial Networks
Jianlin Su
http://arxiv.org/abs/1903.01931v1
• [cs.CV]On measuring the iconicity of a face
Prithviraj Dhar, Carlos D. Castillo, Rama Chellappa
http://arxiv.org/abs/1903.01581v1
• [cs.CV]Real-time Multiple People Hand Localization in 4D Point Clouds
Hao Jiang, Quanzeng You
http://arxiv.org/abs/1903.01695v1
• [cs.CV]Selective Sensor Fusion for Neural Visual-Inertial Odometry
Changhao Chen, Stefano Rosa, Yishu Miao, Chris Xiaoxuan Lu, Wei Wu, Andrew Markham, Niki Trigoni
http://arxiv.org/abs/1903.01534v1
• [cs.CV]TKD: Temporal Knowledge Distillation for Active Perception
Mohammad Farhadi, Yezhou Yang
http://arxiv.org/abs/1903.01522v1
• [cs.CV]TableBank: Table Benchmark for Image-based Table Detection and Recognition
Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, Ming Zhou, Zhoujun Li
http://arxiv.org/abs/1903.01949v1
• [cs.CV]The H3D Dataset for Full-Surround 3D Multi-Object Detection and Tracking in Crowded Urban Scenes
Abhishek Patil, Srikanth Malla, Haiming Gang, Yi-Ting Chen
http://arxiv.org/abs/1903.01568v1
• [cs.CV]Unsupervised Domain-Specific Deblurring via Disentangled Representations
Boyu Lu, Jun-Cheng Chen, Rama Chellappa
http://arxiv.org/abs/1903.01594v1
• [cs.CV]Unsupervised Rank-Preserving Hashing for Large-Scale Image Retrieval
Svebor Karaman, Xudong Lin, Xuefeng Hu, Shih-Fu Chang
http://arxiv.org/abs/1903.01545v1
• [cs.CV]Using Big Five Personality Model to Detect Cultural Aspects in Crowds
Rodolfo Migon Favaretto, Leandro Dihl, Soraia Raupp Musse, Felipe Vilanova, Angelo Brandelli Costa
http://arxiv.org/abs/1903.01688v1
• [cs.CV]Virtual Ground Truth, and Pre-selection of 3D Interest Points for Improved Repeatability Evaluation of 2D Detectors
Simon R Lang, Martin H Luerssen, David M Powers
http://arxiv.org/abs/1903.01828v1
• [cs.CY]Analysis of the Influence of Internet TV Station on Wikipedia Page Views
Hiroshi Hayano, Masanori Takano, Soichiro Morishita, Mitsuo Yoshida, Kyoji Umemura
http://arxiv.org/abs/1903.01704v1
• [cs.DB]Voyageur: An Experiential Travel Search Engine
Sara Evensen, Aaron Feng, Alon Halevy, Jinfeng Li, Vivian Li, Yuliang Li, Huining Liu, George Mihaila, John Morales, Natalie Nuno, Ekaterina Pavlovic, Wang-Chiew Tan, Xiaolan Wang
http://arxiv.org/abs/1903.01498v1
• [cs.DC]BOINC: A Platform for Volunteer Computing
David P. Anderson
http://arxiv.org/abs/1903.01699v1
• [cs.DC]Blockchain Meets Database: Design and Implementation of a Blockchain Relational Database
Senthil Nathan, Chander Govindarajan, Adarsh Saraf, Manish Sethi, Praveen Jayachandran
http://arxiv.org/abs/1903.01919v1
• [cs.DC]Communication Aspects of the Integration of Wireless IoT Devices with Distributed Ledger Technology
Pietro Danzi, Anders E. Kalør, René B. Sørensen, Alexander K. Hagelskjær, Lam D. Nguyen, Čedomir Stefanović, Petar Popovski
http://arxiv.org/abs/1903.01758v1
• [cs.DC]Flexible MEC service consumption through edge host zoning in 5G networks
Miltiades C. Filippou, Dario Sabella, Vincenzo Riccobene
http://arxiv.org/abs/1903.01794v1
• [cs.DC]Lessons Learned from a Decade of Providing Interactive, On-Demand High Performance Computing to Scientists and Engineers
Julia Mullen, Albert Reuther, William Arcand, Bill Bergeron, David Bestor, Chansup Byun, Vijay Gadepally, Michael Houle, Matthew Hubbell, Michael Jones, Anna Klein, Peter Michaleas, Lauren Milechin, Andrew Prout, Antonio Rosa, Siddharth Samsi, Charles Yee, Jeremy Kepner
http://arxiv.org/abs/1903.01982v1
• [cs.GT]Multi-Agent Learning in Network Zero-Sum Games is a Hamiltonian System
James P. Bailey, Georgios Piliouras
http://arxiv.org/abs/1903.01720v1
• [cs.HC]A Serious Game for Introducing Software Engineering Ethics to University Students
Michalis Xenos, Vasiliki Velli
http://arxiv.org/abs/1903.01333v1
• [cs.IT]Approximations of Shannon Mutual Information for Discrete Variables with Applications to Neural Population Coding
Wentao Huang, Kechen Zhang
http://arxiv.org/abs/1903.01500v1
• [cs.IT]Closed-Loop Sparse Channel Estimation for Wideband MmWave FD-MIMO Systems
Anwen Liao, Zhen Gao, Hua Wang, Sheng Chen, Mohamed-Slim Alouini, Hao Yin
http://arxiv.org/abs/1903.01921v1
• [cs.IT]Cooperative Caching in Fog Radio Access Networks: A Graph-based Approach
Yanxiang Jiang, Xiaoting Cui, Mehdi Bennis, Fu-Chun Zheng
http://arxiv.org/abs/1903.01858v1
• [cs.IT]DoF Region of the MISO BC with Partial CSIT: Proof by Inductive Fourier-Motzkin Elimination
Hamdi Joudeh, Bruno Clerckx
http://arxiv.org/abs/1903.01767v1
• [cs.IT]Gradient Coding with Clustering and Multi-message Communication
Emre Ozfatura, Deniz Gunduz, Sennur Ulukus
http://arxiv.org/abs/1903.01974v1
• [cs.IT]Learning to Branch: Accelerating Resource Allocation in Wireless Networks
Mengyuan Lee, Guanding Yu, Geoffrey Ye Li
http://arxiv.org/abs/1903.01819v1
• [cs.IT]Multi-tone Signal Optimization for Wireless Power Transfer in the Presence of Wireless Communication Links
Boules A. Mouris, Hadi Ghauch, Ragnar Thobaben, B. L. G. Jonsson
http://arxiv.org/abs/1903.01798v1
• [cs.IT]Noncoherent Multiuser Massive SIMO for Low-Latency Industrial IoT Communications
Zheng Dong, He Chen, Jian-Kang Zhang, Branka Vucetic
http://arxiv.org/abs/1903.01642v1
• [cs.IT]Noncoherent and Non-orthogonal Massive SIMO for Critical Industrial IoT Communications
He Chen, Zheng Dong, Branka Vucetic
http://arxiv.org/abs/1903.01650v1
• [cs.IT]On the Performance Gain of NOMA over OMA in Uplink Communication Systems
Zhiqiang Wei, Lei Yang, Derrick Wing Kwan Ng, Jinhong Yuan, Lajos Hanzo
http://arxiv.org/abs/1903.01683v1
• [cs.IT]Performance Analysis of NOMA-based Cooperative Relaying in α - μ Fading Channels
Vaibhav Kumar, Barry Cardiff, Mark F. Flanagan
http://arxiv.org/abs/1903.01946v1
• [cs.IT]Reduced-rank Analysis of the Total Least Squares
K. G. Nagananda, Pramod Khargonekar
http://arxiv.org/abs/1903.01745v1
• [cs.IT]Twin-Timescale Radio Resource Management for Ultra-Reliable and Low-Latency Vehicular Networks
Haojun Yang, Kan Zheng, Long Zhao, Lajos Hanzo
http://arxiv.org/abs/1903.01604v1
• [cs.LG]A Deep Learning based approach to VM behavior identification in cloud systems
Matteo Stefanini, Riccardo Lancellotti, Lorenzo Baraldi, Simone Calderara
http://arxiv.org/abs/1903.01930v1
• [cs.LG]A Novel Efficient Approach with Data-Adaptive Capability for OMP-based Sparse Subspace Clustering
Jiaqiyu Zhan, Zhiqiang Bai, Yuesheng Zhu
http://arxiv.org/abs/1903.01734v1
• [cs.LG]Causal Discovery and Hidden Driving Force Estimation from Nonstationary/Heterogeneous Data
Biwei Huang, Kun Zhang, Jiji Zhang, Joseph Ramsey, Bernhard Schölkopf, Clark Glymour
http://arxiv.org/abs/1903.01672v1
• [cs.LG]Copying Machine Learning Classifiers
Irene Unceta, Jordi Nin, Oriol Pujol
http://arxiv.org/abs/1903.01879v1
• [cs.LG]Do Neural Networks Show Gestalt Phenomena? An Exploration of the Law of Closure
Been Kim, Emily Reif, Martin Wattenberg, Samy Bengio
http://arxiv.org/abs/1903.01069v2
• [cs.LG]Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment
Yifan Wu, Ezra Winston, Divyansh Kaushik, Zachary Lipton
http://arxiv.org/abs/1903.01689v1
• [cs.LG]Efficient Winograd or Cook-Toom Convolution Kernel Implementation on Widely Used Mobile CPUs
Partha Maji, Andrew Mundy, Ganesh Dasika, Jesse Beu, Matthew Mattina, Robert Mullins
http://arxiv.org/abs/1903.01521v1
• [cs.LG]Gated Graph Convolutional Recurrent Neural Networks
Luana Ruiz, Fernando Gama, Alejandro Ribeiro
http://arxiv.org/abs/1903.01888v1
• [cs.LG]Generative Adversarial Nets for Robust Scatter Estimation: A Proper Scoring Rule Perspective
Chao Gao, Yuan Yao, Weizhi Zhu
http://arxiv.org/abs/1903.01944v1
• [cs.LG]Generative Design Exploration by Integrating Deep Generative Models and Topology Optimization
Sangeun Oh, Yongsu Jung, Seongsin Kim, Ikjin Lee, Namwoo Kang
http://arxiv.org/abs/1903.01548v1
• [cs.LG]Hedging the Drift: Learning to Optimize under Non-Stationarity
Wang Chi Cheung, David Simchi-Levi, Ruihao Zhu
http://arxiv.org/abs/1903.01461v1
• [cs.LG]L 1-norm double backpropagation adversarial defense
Ismaïla Seck, Gaëlle Loosli, Stephane Canu
http://arxiv.org/abs/1903.01715v1
• [cs.LG]Making the Dynamic Time Warping Distance Warping-Invariant
Brijnesh Jain
http://arxiv.org/abs/1903.01454v1
• [cs.LG]Model Primitive Hierarchical Lifelong Reinforcement Learning
Bohan Wu, Jayesh K. Gupta, Mykel J. Kochenderfer
http://arxiv.org/abs/1903.01567v1
• [cs.LG]Modeling Social Group Communication with Multi-Agent Imitation Learning
Navyata Sanghvi, Ryo Yonetani, Kris Kitani
http://arxiv.org/abs/1903.01537v1
• [cs.LG]Multiple-Kernel Dictionary Learning for Reconstruction and Clustering of Unseen Multivariate Time-series
Babak Hosseini, Barbara Hammer
http://arxiv.org/abs/1903.01867v1
• [cs.LG]Online Data Poisoning Attack
Xuezhou Zhang, Xiaojin Zhu
http://arxiv.org/abs/1903.01666v1
• [cs.LG]PDP: A General Neural Framework for Learning Constraint Satisfaction Solvers
Saeed Amizadeh, Sergiy Matusevych, Markus Weimer
http://arxiv.org/abs/1903.01969v1
• [cs.LG]Probabilistic Modeling for Novelty Detection with Applications to Fraud Identification
Rémi Domingues
http://arxiv.org/abs/1903.01730v1
• [cs.LG]Statistical Guarantees for the Robustness of Bayesian Neural Networks
Luca Cardelli, Marta Kwiatkowska, Luca Laurenti, Nicola Paoletti, Andrea Patane, Matthew Wicker
http://arxiv.org/abs/1903.01980v1
• [cs.LG]Streaming Batch Eigenupdates for Hardware Neuromorphic Networks
Brian D. Hoskins, Matthew W. Daniels, Siyuan Huang, Advait Madhavan, Gina C. Adam, Nikolai Zhitenev, Jabez J. McClelland, Mark D. Stiles
http://arxiv.org/abs/1903.01635v1
• [cs.LG]Ternary Hybrid Neural-Tree Networks for Highly Constrained IoT Applications
Dibakar Gope, Ganesh Dasika, Matthew Mattina
http://arxiv.org/abs/1903.01531v1
• [cs.LG]The Complexity of Morality: Checking Markov Blanket Consistency with DAGs via Morality
Yang Li, Kevin Korb, Lloyd Allison
http://arxiv.org/abs/1903.01707v1
• [cs.LG]The Lottery Ticket Hypothesis at Scale
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin
http://arxiv.org/abs/1903.01611v1
• [cs.LG]The Vulnerabilities of Graph Convolutional Networks: Stronger Attacks and Defensive Techniques
Huijun Wu, Chen Wang, Yuriy Tyshetskiy, Andrew Dotcherty, Kai Lu, Liming Zhu
http://arxiv.org/abs/1903.01610v1
• [cs.LG]Towards Understanding Chinese Checkers with Heuristics, Monte Carlo Tree Search, and Deep Reinforcement Learning
Ziyu Liu, Meng Zhou, Weiqing Cao, Qiang Qu, Henry Wing Fung Yeung, Vera Yuk Ying Chung
http://arxiv.org/abs/1903.01747v1
• [cs.LG]Two-Stream Multi-Channel Convolutional Neural Network (TM-CNN) for Multi-Lane Traffic Speed Prediction Considering Traffic Volume Impact
Ruimin Ke, Wan Li, Zhiyong Cui, Yinhai Wang
http://arxiv.org/abs/1903.01678v1
• [cs.LG]Ultra-Scalable Spectral Clustering and Ensemble Clustering
Dong Huang, Chang-Dong Wang, Jian-Sheng Wu, Jian-Huang Lai, Chee-Keong Kwoh
http://arxiv.org/abs/1903.01057v2
• [cs.LG]Universal approximations of permutation invariant/equivariant functions by deep neural networks
Akiyoshi Sannai, Yuuki Takai, Matthieu Cordonnier
http://arxiv.org/abs/1903.01939v1
• [cs.LG]What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features
Pasha Khosravi, Yitao Liang, YooJung Choi, Guy Van den Broeck
http://arxiv.org/abs/1903.01620v1
• [cs.NE]Two-level protein folding optimization on a three-dimensional AB off-lattice model
Borko Bošković, Janez Brest
http://arxiv.org/abs/1903.01456v1
• [cs.NE]Visualisation of Pareto Front Approximation: A Short Survey and Empirical Comparisons
Huiru Gao, Haifeng Nie, Ke Li
http://arxiv.org/abs/1903.01768v1
• [cs.NI]Socially-Aware Congestion Control in Ad-Hoc Networks: Current Status and The Way Forward
Hannan Bin Liaqat, Amjad Ali, Junaid Qadir, Ali Kashif Bashir, Muhammad Bilal, Fiaz Majeed
http://arxiv.org/abs/1903.01617v1
• [cs.RO]Automated Generation of Reactive Programs from Human Demonstration for Orchestration of Robot Behaviors
Vincent Berenz, Ahmed Bjelic, Jim Mainprice
http://arxiv.org/abs/1903.01352v2
• [cs.RO]Creating Navigable Space from Sparse Noisy Map Points
Zheng Chen, Lantao Liu
http://arxiv.org/abs/1903.01503v1
• [cs.RO]Deep Active Localization
Sai Krishna, Keehong Seo, Dhaivat Bhatt, Vincent Mai, Krishna Murthy, Liam Paull
http://arxiv.org/abs/1903.01669v1
• [cs.RO]Episodic Learning with Control Lyapunov Functions for Uncertain Robotic Systems
Andrew J. Taylor, Victor D. Dorobantu, Hoang M. Le, Yisong Yue, Aaron D. Ames
http://arxiv.org/abs/1903.01577v1
• [cs.RO]Learning Exploration Policies for Navigation
Tao Chen, Saurabh Gupta, Abhinav Gupta
http://arxiv.org/abs/1903.01959v1
• [cs.RO]Learning Latent Plans from Play
Corey Lynch, Mohi Khansari, Ted Xiao, Vikash Kumar, Jonathan Tompson, Sergey Levine, Pierre Sermanet
http://arxiv.org/abs/1903.01973v1
• [cs.RO]Mechanical Search: Multi-Step Retrieval of a Target Object Occluded by Clutter
Michael Danielczuk, Andrey Kurenkov, Ashwin Balakrishna, Matthew Matl, David Wang, Roberto Martín-Martín, Animesh Garg, Silvio Savarese, Ken Goldberg
http://arxiv.org/abs/1903.01588v1
• [cs.RO]Planning Grasps for Assembly Tasks
Weiwei Wan, Kensuke Harada, Fumio Kanehiro
http://arxiv.org/abs/1903.01631v1
• [cs.RO]Robot Localization in Floor Plans Using a Room Layout Edge Extraction Network
Federico Boniardi, Abhinav Valada, Rohit Mohan, Tim Caselitz, Wolfram Burgard
http://arxiv.org/abs/1903.01804v1
• [cs.RO]Stochastic Sampling Simulation for Pedestrian Trajectory Prediction
Cyrus Anderson, Xiaoxiao Du, Ram Vasudevan, Matthew Johnson-Roberson
http://arxiv.org/abs/1903.01860v1
• [cs.RO]Vision-Depth Landmarks and Inertial Fusion for Navigation in Degraded Visual Environments
Shehryar Khattak, Christos Papachristos, Kostas Alexis
http://arxiv.org/abs/1903.01659v1
• [cs.RO]Visual-Thermal Landmarks and Inertial Fusion for Navigation in Degraded Visual Environments
Shehryar Khattak, Christos Papachristos, Kostas Alexis
http://arxiv.org/abs/1903.01656v1
• [cs.SI]Less is More: Semi-Supervised Causal Inference for Detecting Pathogenic Users in Social Media
Hamidreza Alvari, Elham Shaabani, Soumajyoti Sarkar, Ghazaleh Beigi, Paulo Shakarian
http://arxiv.org/abs/1903.01693v1
• [cs.SI]Selective Exposure shapes the Facebook News Diet
Matteo Cinelli, Emanuele Brugnoli, Ana Lucia Schmidt, Fabiana Zollo, Walter Quattrociocchi, Antonio Scala
http://arxiv.org/abs/1903.00699v1
• [cs.SI]Trust and Trustworthiness in Social Recommender Systems
Taha Hassan, D. Scott McCrickard
http://arxiv.org/abs/1903.01780v1
• [cs.SY]A behavior driven approach for sampling rare event situations for autonomous vehicles
Atrisha Sarkar, Krzysztof Czarnecki
http://arxiv.org/abs/1903.01539v1
• [econ.GN]Externalities in Knowledge Production: Evidence from a Randomized Field Experiment
Marit Hinnosaar, Toomas Hinnosaar, Michael Kummer, Olga Slivko
http://arxiv.org/abs/1903.01861v1
• [eess.SP]Study of Sparsity-Aware Reduced-Dimension Beam-Doppler Space-Time Adaptive Processing
Zhaocheng Yang, Rodrigo C. de Lamare
http://arxiv.org/abs/1903.01625v1
• [eess.SP]Towards Design Space Exploration and Optimization of Fast Algorithms for Convolutional Neural Networks (CNNs) on FPGAs
Afzal Ahmad, Muhammad Adeel Pasha
http://arxiv.org/abs/1903.01811v1
• [eess.SP]V2X System Architecture Utilizing Hybrid Gaussian Process-based Model Structures
Hossein Nourkhiz Mahjoub, Behrad Toghi, S M Osman Gani, Yaser P. Fallah
http://arxiv.org/abs/1903.01576v1
• [math.CO]Probabilistic refinement of the asymptotic spectrum of graphs
Péter Vrana
http://arxiv.org/abs/1903.01857v1
• [math.OC]A Stochastic Trust Region Method for Non-convex Minimization
Zebang Shen, Pan Zhou, Cong Fang, Alejandro Ribeiro
http://arxiv.org/abs/1903.01540v1
• [math.OC]Inertial Block Mirror Descent Method for Non-Convex Non-Smooth Optimization
Le Thi Khanh Hien, Nicolas Gillis, Panagiotis Patrinos
http://arxiv.org/abs/1903.01818v1
• [math.OC]SGD without Replacement: Sharper Rates for General Smooth Convex Functions
Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli
http://arxiv.org/abs/1903.01463v1
• [math.PR]Theoretical guarantees for sampling and inference in generative models with latent diffusions
Belinda Tzen, Maxim Raginsky
http://arxiv.org/abs/1903.01608v1
• [math.ST]Change Detection with the Kernel Cumulative Sum Algorithm
Thomas Flynn, Shinjae Yoo
http://arxiv.org/abs/1903.01661v1
• [math.ST]Concentration-based confidence intervals for U-statistics
Hien D. Nguyen
http://arxiv.org/abs/1903.01679v1
• [math.ST]Data Amplification: Instance-Optimal Property Estimation
Yi Hao, Alon Orlitsky
http://arxiv.org/abs/1903.01432v2
• [math.ST]Local differential privacy: Elbow effect in optimal density estimation and adaptation over Besov ellipsoids
Cristina Butucea, Amandine Dubois, Martin Kroll, Adrien Saumard
http://arxiv.org/abs/1903.01927v1
• [math.ST]Measuring and Controlling Bias for Some Bayesian Inferences and the Relation to Frequentist Criteria
Michael Evans, Yang Guo
http://arxiv.org/abs/1903.01696v1
• [math.ST]Multiscale clustering of nonparametric regression curves
Michael Vogt, Oliver Linton
http://arxiv.org/abs/1903.01459v1
• [math.ST]Tutorial: Deriving The Efficient Influence Curve for Large Models
Jonathan Levy
http://arxiv.org/abs/1903.01706v1
• [physics.ins-det]Deep learning based pulse shape discrimination for germanium detectors
P. Holl, L. Hauertmann, B. Majorovits, O. Schulz, M. Schuster, A. J. Zsigmond
http://arxiv.org/abs/1903.01462v1
• [physics.soc-ph]Analysing Motifs in Multilayer Networks
Lu Zhong, Qingpeng Zhang, Dong Yang, Guanrong Chen, Shi Yu
http://arxiv.org/abs/1903.01722v1
• [q-bio.NC]Deep Learning for Cognitive Neuroscience
Katherine R. Storrs, Nikolaus Kriegeskorte
http://arxiv.org/abs/1903.01458v1
• [q-fin.ST]Influence of petroleum and gas trade on EU economies from the reduced Google matrix analysis of UN COMTRADE data
Célestin Coquidé, Leonardo Ermann, José Lages, D. L. Shepelyansky
http://arxiv.org/abs/1903.01820v1
• [stat.AP]A Factor Stochastic Volatility Model with Markov-Switching Panic Regimes
Taylor R. Brown
http://arxiv.org/abs/1903.01841v1
• [stat.AP]The power disaggregation algorithms and their applications to demand dispatch
Arnaud Cadas, Ana Busic
http://arxiv.org/abs/1903.01803v1
• [stat.CO]Convex Covariate Clustering for Classification
Daniel Andrade, Kenji Fukumizu, Yuzuru Okajima
http://arxiv.org/abs/1903.01680v1
• [stat.CO]Quantifying Gait Changes Using Microsoft Kinect and Sample Entropy
Behnam Malmir, Shing I Chang, Malgorzata Rys, Dylan Darter
http://arxiv.org/abs/1903.01601v1
• [stat.CO]Similarity-based Random Survival Forest
Yingying Xu, Joon Lee, Joel A. Dubin
http://arxiv.org/abs/1903.01029v1
• [stat.ME]A multinomial Asymptotic Representation of Zenga's Discrete Index, its Influence Function and Data-driven Applications
Tchilabalo Abozou Kpanzou, Diam Ba, Cherif Moctar Mamadou Traoré, Gane Samb Lo
http://arxiv.org/abs/1903.01603v1
• [stat.ME]Change-point detection for multivariate and non-Euclidean data with local dependency
Hao Chen
http://arxiv.org/abs/1903.01598v1
• [stat.ME]Spike-and-Slab Group Lassos for Grouped Regression and Sparse Generalized Additive Models
Ray Bai, Gemma E. Moran, Joseph Antonelli, Yong Chen, Mary R. Boland
http://arxiv.org/abs/1903.01979v1
• [stat.ME]Statistical approach to detection of signals by Monte Carlo singular spectrum analysis: Multiple testing
Nina Golyandina
http://arxiv.org/abs/1903.01485v1
• [stat.ML]A New Approach to Adaptive Data Analysis and Learning via Maximal Leakage
Amedeo Roberto Esposito, Michael Gastpar, Ibrahim Issa
http://arxiv.org/abs/1903.01777v1
• [stat.ML]Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future
Nan Rosemary Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal, Yoshua Bengio, Devi Parikh, Dhruv Batra
http://arxiv.org/abs/1903.01599v1
• [stat.OT]The Fuzzy ROC
Giovanni Parmigiani
http://arxiv.org/abs/1903.01868v1
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