astro-ph.GA - 星系天体物理学
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.DL - 数字图书馆 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.RO - 机器人学 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 nlin.AO - 适应和自组织系统 physics.comp-ph - 计算物理学 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
• [astro-ph.GA]Morpheus: A Deep Learning Framework For Pixel-Level Analysis of Astronomical Image Data
• [cs.AI]Approximate Causal Abstraction
• [cs.AI]Beyond DAGs: Modeling Causal Feedback with Fuzzy Cognitive Maps
• [cs.AI]Generalization of Dempster-Shafer theory: A complex belief function
• [cs.AI]Generalization to Novel Objects using Prior Relational Knowledge
• [cs.CL]A Corpus for Modeling User and Language Effects in Argumentation on Online Debating
• [cs.CL]A Generative Model for Punctuation in Dependency Trees
• [cs.CL]Compositional Semantic Parsing Across Graphbanks
• [cs.CL]Determining Relative Argument Specificity and Stance for Complex Argumentative Structures
• [cs.CL]Eliciting Knowledge from Experts:Automatic Transcript Parsing for Cognitive Task Analysis
• [cs.CL]EmotionX-KU: BERT-Max based Contextual Emotion Classifier
• [cs.CL]Exploring the Role of Prior Beliefs for Argument Persuasion
• [cs.CL]Gated Embeddings in End-to-End Speech Recognition for Conversational-Context Fusion
• [cs.CL]Inducing Syntactic Trees from BERT Representations
• [cs.CL]Lattice-Based Unsupervised Test-Time Adaptation of Neural Network Acoustic Models
• [cs.CL]Morphological Irregularity Correlates with Frequency
• [cs.CL]PKUSEG: A Toolkit for Multi-Domain Chinese Word Segmentation
• [cs.CL]Semantic expressive capacity with bounded memory
• [cs.CL]Simple Natural Language Processing Tools for Danish
• [cs.CL]The Impact of Preprocessing on Arabic-English Statistical and Neural Machine Translation
• [cs.CR]A Trust Architecture for Blockchain in IoT
• [cs.CR]Identifying DNS-tunneled traffic with predictive models
• [cs.CV]A Convolutional Decoder for Point Clouds using Adaptive Instance Normalization
• [cs.CV]A Generalized Framework for Agglomerative Clustering of Signed Graphs applied to Instance Segmentation
• [cs.CV]A New Benchmark Dataset for Texture Image Analysis and Surface Defect Detection
• [cs.CV]A shallow residual neural network to predict the visual cortex response
• [cs.CV]Automatic Colon Polyp Detection using Region based Deep CNN and Post Learning Approaches
• [cs.CV]Automatically Extract the Semi-transparent Motion-blurred Hand from a Single Image
• [cs.CV]CaDSS: Cataract Dataset for Semantic Segmentation
• [cs.CV]Dealing with Topological Information within a Fully Convolutional Neural Network
• [cs.CV]Detection of small changes in medical and random-dot images comparing self-organizing map performance to human detection
• [cs.CV]Developing an App to interpret Chest X-rays to support the diagnosis of respiratory pathology with Artificial Intelligence
• [cs.CV]ELKPPNet: An Edge-aware Neural Network with Large Kernel Pyramid Pooling for Learning Discriminative Features in Semantic Segmentation
• [cs.CV]Effective Rotation-invariant Point CNN with Spherical Harmonics kernels
• [cs.CV]Emergence of Exploratory Look-Around Behaviors through Active Observation Completion
• [cs.CV]Few-Shot Video Classification via Temporal Alignment
• [cs.CV]Hard Pixels Mining: Learning Using Privileged Information for Semantic Segmentation
• [cs.CV]Loss Switching Fusion with Similarity Search for Video Classification
• [cs.CV]Region Refinement Network for Salient Object Detection
• [cs.CV]SpliceRadar: A Learned Method For Blind Image Forensics
• [cs.CY]Artificial Intelligence: the global landscape of ethics guidelines
• [cs.CY]Data Consortia
• [cs.CY]Fairness criteria through the lens of directed acyclic graphical models
• [cs.DC]DiPETrans: A Framework for Distributed Parallel Execution of Transactions of Blocks in Blockchain
• [cs.DC]HEATS: Heterogeneity- and Energy-Aware Task-based Scheduling
• [cs.DC]Improved Distributed Approximation to Maximum Independent Set
• [cs.DL]Improving Academic Plagiarism Detection for STEM Documents by Analyzing Mathematical Content and Citations
• [cs.DS]A Tight Analysis of Greedy Yields Subexponential Time Approximation for Uniform Decision Tree
• [cs.DS]Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection
• [cs.DS]The Adversarial Robustness of Sampling
• [cs.GR]ORRB — OpenAI Remote Rendering Backend
• [cs.GR]Optimizing for Aesthetically Pleasing Quadrotor Camera Motion
• [cs.HC]Airways: Optimization-Based Planning of Quadrotor Trajectories according to High-Level User Goals
• [cs.HC]User Validation of Recommendation Serendipity Metrics
• [cs.IR]A Simple Deep Personalized Recommendation System
• [cs.IR]Re-ranking Based Diversification: A Unifying View
• [cs.IR]Reducing Popularity Bias in Recommendation Over Time
• [cs.IR]Representation Learning of Music Using Artist, Album, and Track Information
• [cs.IR]Toward Simulating Environments in Reinforcement Learning Based Recommendations
• [cs.IT]Array Codes with Local Properties
• [cs.IT]On the Energy Efficiency of Limited-Backhaul Cell-Free Massive MIMO
• [cs.IT]On the Sparseness of Certain MRD Codes
• [cs.IT]Private Information Retrieval with Private Coded Side Information: The Multi-Server Case
• [cs.LG]A Survey on GANs for Anomaly Detection
• [cs.LG]A Tractable Algorithm For Finite-Horizon Continuous Reinforcement Learning
• [cs.LG]Accelerating Large-Kernel Convolution Using Summed-Area Tables
• [cs.LG]Adversarial FDI Attack against AC State Estimation with ANN
• [cs.LG]Adversarial Robustness via Adversarial Label-Smoothing
• [cs.LG]Clustering by the way of atomic fission
• [cs.LG]Curriculum Learning for Deep Generative Models with Clustering
• [cs.LG]Encoding Database Schemas with Relation-Aware Self-Attention for Text-to-SQL Parsers
• [cs.LG]ExTra: Transfer-guided Exploration
• [cs.LG]Hyp-RL : Hyperparameter Optimization by Reinforcement Learning
• [cs.LG]Latent Optimization for Non-adversarial Representation Disentanglement
• [cs.LG]Learning Fair Representations for Kernel Models
• [cs.LG]Mind2Mind : transfer learning for GANs
• [cs.LG]Near Optimal Stratified Sampling
• [cs.LG]No Pressure! Addressing the Problem of Local Minima in Manifold Learning Algorithms
• [cs.LG]One Size Does Not Fit All: Quantifying and Exposing the Accuracy-Latency Trade-off in Machine Learning Cloud Service APIs via Tolerance Tiers
• [cs.LG]Personalized Student Stress Prediction with Deep Multitask Network
• [cs.LG]Regularized Hierarchical Policies for Compositional Transfer in Robotics
• [cs.LG]Singular Value Decomposition and Neural Networks
• [cs.LG]Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference
• [cs.LG]Uncertainty Estimates for Ordinal Embeddings
• [cs.LG]User-Oriented Summaries Using a PSO Based Scoring Optimization Method
• [cs.LG]Using Intuition from Empirical Properties to Simplify Adversarial Training Defense
• [cs.NE]Evolving Robust Neural Architectures to Defend from Adversarial Attacks
• [cs.NE]On improving deep learning generalization with adaptive sparse connectivity
• [cs.NI]A Key 6G Challenge and Opportunity — Connecting the Remaining 4 Billions: A Survey on Rural Connectivity
• [cs.NI]An Algorithm for Transmitting VR Video Based on Adaptive Modulation
• [cs.NI]Capacity and Coverage Enhancement Using Long-Endurance Tethered Airborne Base Stations
• [cs.NI]Security of 5G-Mobile Backhaul Networks: A Survey
• [cs.RO]A Constant-Factor Approximation Algorithm for Online Coverage Path Planning with Energy Constraint
• [cs.RO]Automatic Coverage Selection for Surface-Based Visual Localization
• [cs.RO]Automatic Detection of Myocontrol Failures Based upon Situational Context Information
• [cs.RO]DeepVIO: Self-supervised Deep Learning of Monocular Visual Inertial Odometry using 3D Geometric Constraints
• [cs.RO]Demonstration-Guided Deep Reinforcement Learning of Control Policies for Dexterous Human-Robot Interaction
• [cs.RO]Generative grasp synthesis from demonstration using parametric mixtures
• [cs.RO]Methodology of Designing Multi-agent Robot Control Systems Utilising Hierarchical Petri Nets
• [cs.RO]Modal-based Kinematics and Contact Detection of Soft Robots
• [cs.RO]Multi-Robot Patrolling with Sensing Idleness and Data Delay Objectives
• [cs.RO]Raven: Open Surgical Robotic Platforms
• [cs.SI]Deception Strategies and Threats for Online Discussions
• [cs.SI]Link weights recovery in heterogeneous information networks
• [cs.SI]Reducing Spreading Processes on Networks to Markov Population Models
• [eess.AS]RUSLAN: Russian Spoken Language Corpus for Speech Synthesis
• [eess.IV]Abnormal Colon Polyp Image Synthesis Using Conditional Adversarial Networks for Improved Detection Performance
• [eess.IV]Automated Segmentation of Hip and Thigh Muscles in Metal Artifact-Contaminated CT using Convolutional Neural Network-Enhanced Normalized Metal Artifact Reduction
• [eess.IV]Deep Siamese Multi-scale Convolutional Network for Change Detection in Multi-temporal VHR Images
• [eess.IV]More chemical detection through less sampling: amplifying chemical signals in hyperspectral data cubes through compressive sensing
• [eess.SP]A PolSAR Scattering Power Factorization Framework and Novel Roll-Invariant Parameters Based Unsupervised Classification Scheme Using a Geodesic Distance
• [eess.SP]Large-scale 3D point cloud representations via graph inception networks with applications to autonomous driving
• [eess.SY]Approximate Dynamic Programming For Linear Systems with State and Input Constraints
• [math.OC]A Tutorial on Concentration Bounds for System Identification
• [math.OC]Bilinear Compressed Sensing under known Signs via Convex Programming
• [math.OC]From self-tuning regulators to reinforcement learning and back again
• [math.OC]High-Dimensional Optimization in Adaptive Random Subspaces
• [math.PR]Correlators of Polynomial Processes
• [math.ST]Empirical Process Results for Exchangeable Arrays
• [math.ST]Rerandomization and Regression Adjustment
• [math.ST]Statistically and Computationally Efficient Change Point Localization in Regression Settings
• [math.ST]The exact form of the ‘Ockham factor’ in model selection
• [nlin.AO]Repeated sequential learning increases memory capacity via effective decorrelation in a recurrent neural network
• [physics.comp-ph]Deep neural network for Wannier function centers
• [physics.soc-ph]Broken Detailed Balance and Non-Equilibrium Dynamics in Noisy Social Learning Models
• [physics.soc-ph]Hypernetwork Science via High-Order Hypergraph Walks
• [quant-ph]Reachability Deficits in Quantum Approximate Optimization
• [stat.AP]A strategy for the matching of mobile phone signals with census data
• [stat.AP]An anisotropic model for global climate data
• [stat.AP]Detecting and classifying moments in basketball matches using sensor tracked data
• [stat.AP]How response designs and class proportions affect the accuracy of validation data
• [stat.AP]Know your population and know your model: Using model-based regression and poststratification to generalize findings beyond the observed sample
• [stat.AP]Quality analysis in acyclic production networks
• [stat.AP]Unsupervised Methods for Identifying Pass Coverage Among Defensive Backs with NFL Player Tracking Data
• [stat.ME]A Simultaneous Transformation and Rounding Approach for Modeling Integer-Valued Data
• [stat.ME]Estimation of treatment effects following a sequential trial of multiple treatments
• [stat.ME]Interpretable Almost-Matching-Exactly With Instrumental Variables
• [stat.ME]Selective Inference via Marginal Screening for High Dimensional Classification
• [stat.ML]’In-Between’ Uncertainty in Bayesian Neural Networks
• [stat.ML]A global approach for learning sparse Ising models
• [stat.ML]Benign Overfitting in Linear Regression
• [stat.ML]Deep Active Learning with Adaptive Acquisition
• [stat.ML]Fast Training of Sparse Graph Neural Networks on Dense Hardware
• [stat.ML]Hierarchical Data Reduction and Learning
• [stat.ML]Hierarchical Optimal Transport for Multimodal Distribution Alignment
• [stat.ML]Tuning-Free Disentanglement via Projection
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• [astro-ph.GA]Morpheus: A Deep Learning Framework For Pixel-Level Analysis of Astronomical Image Data
Ryan Hausen, Brant Robertson
http://arxiv.org/abs/1906.11248v1
• [cs.AI]Approximate Causal Abstraction
Sander Beckers, Frederick Eberhardt, Joseph Y. Halpern
http://arxiv.org/abs/1906.11583v1
• [cs.AI]Beyond DAGs: Modeling Causal Feedback with Fuzzy Cognitive Maps
Osonde Osoba, Bart Kosko
http://arxiv.org/abs/1906.11247v1
• [cs.AI]Generalization of Dempster-Shafer theory: A complex belief function
Fuyuan Xiao
http://arxiv.org/abs/1906.11409v1
• [cs.AI]Generalization to Novel Objects using Prior Relational Knowledge
Varun Kumar Vijay, Abhinav Ganesh, Hanlin Tang, Arjun Bansal
http://arxiv.org/abs/1906.11315v1
• [cs.CL]A Corpus for Modeling User and Language Effects in Argumentation on Online Debating
Esin Durmus, Claire Cardie
http://arxiv.org/abs/1906.11310v1
• [cs.CL]A Generative Model for Punctuation in Dependency Trees
Xiang Lisa Li, Dingquan Wang, Jason Eisner
http://arxiv.org/abs/1906.11298v1
• [cs.CL]Compositional Semantic Parsing Across Graphbanks
Matthias Lindemann, Jonas Groschwitz, Alexander Koller
http://arxiv.org/abs/1906.11746v1
• [cs.CL]Determining Relative Argument Specificity and Stance for Complex Argumentative Structures
Esin Durmus, Faisal Ladhak, Claire Cardie
http://arxiv.org/abs/1906.11313v1
• [cs.CL]Eliciting Knowledge from Experts:Automatic Transcript Parsing for Cognitive Task Analysis
Junyi Du, He Jiang, Jiaming Shen, Xiang Ren
http://arxiv.org/abs/1906.11384v1
• [cs.CL]EmotionX-KU: BERT-Max based Contextual Emotion Classifier
Kisu Yang, Dongyub Lee, Taesun Whang, Seolhwa Lee, Heuiseok Lim
http://arxiv.org/abs/1906.11565v1
• [cs.CL]Exploring the Role of Prior Beliefs for Argument Persuasion
Esin Durmus, Claire Cardie
http://arxiv.org/abs/1906.11301v1
• [cs.CL]Gated Embeddings in End-to-End Speech Recognition for Conversational-Context Fusion
Suyoun Kim, Siddharth Dalmia, Florian Metze
http://arxiv.org/abs/1906.11604v1
• [cs.CL]Inducing Syntactic Trees from BERT Representations
Rudolf Rosa, David Mareček
http://arxiv.org/abs/1906.11511v1
• [cs.CL]Lattice-Based Unsupervised Test-Time Adaptation of Neural Network Acoustic Models
Ondrej Klejch, Joachim Fainberg, Peter Bell, Steve Renals
http://arxiv.org/abs/1906.11521v1
• [cs.CL]Morphological Irregularity Correlates with Frequency
Shijie Wu, Ryan Cotterell, Timothy J. O’Donnell
http://arxiv.org/abs/1906.11483v1
• [cs.CL]PKUSEG: A Toolkit for Multi-Domain Chinese Word Segmentation
Ruixuan Luo, Jingjing Xu, Yi Zhang, Xuancheng Ren, Xu Sun
http://arxiv.org/abs/1906.11455v1
• [cs.CL]Semantic expressive capacity with bounded memory
Antoine Venant, Alexander Koller
http://arxiv.org/abs/1906.11752v1
• [cs.CL]Simple Natural Language Processing Tools for Danish
Leon Derczynski
http://arxiv.org/abs/1906.11608v1
• [cs.CL]The Impact of Preprocessing on Arabic-English Statistical and Neural Machine Translation
Mai Oudah, Amjad Almahairi, Nizar Habash
http://arxiv.org/abs/1906.11751v1
• [cs.CR]A Trust Architecture for Blockchain in IoT
Volkan Dedeoglu, Raja Jurdak, Guntur D. Putra, Ali Dorri, Salil S. Kanhere
http://arxiv.org/abs/1906.11461v1
• [cs.CR]Identifying DNS-tunneled traffic with predictive models
Andreas Berg, Daniel Forsberg
http://arxiv.org/abs/1906.11246v1
• [cs.CV]A Convolutional Decoder for Point Clouds using Adaptive Instance Normalization
Isaak Lim, Moritz Ibing, Leif Kobbelt
http://arxiv.org/abs/1906.11478v1
• [cs.CV]A Generalized Framework for Agglomerative Clustering of Signed Graphs applied to Instance Segmentation
Alberto Bailoni, Constantin Pape, Steffen Wolf, Thorsten Beier, Anna Kreshuk, Fred A. Hamprecht
http://arxiv.org/abs/1906.11713v1
• [cs.CV]A New Benchmark Dataset for Texture Image Analysis and Surface Defect Detection
Shervan Fekri-Ershad
http://arxiv.org/abs/1906.11561v1
• [cs.CV]A shallow residual neural network to predict the visual cortex response
Anne-Ruth José Meijer, Arnoud Visser
http://arxiv.org/abs/1906.11578v1
• [cs.CV]Automatic Colon Polyp Detection using Region based Deep CNN and Post Learning Approaches
Younghak Shin, Hemin Ali Qadir, Lars Aabakken, Jacob Bergsland, Ilangko Balasingham
http://arxiv.org/abs/1906.11463v1
• [cs.CV]Automatically Extract the Semi-transparent Motion-blurred Hand from a Single Image
Xiaomei Zhao, Yihong Wu
http://arxiv.org/abs/1906.11470v1
• [cs.CV]CaDSS: Cataract Dataset for Semantic Segmentation
Evangello Flouty, Abdolrahim Kadkhodamohammadi, Imanol Luengo, Felix Fuentes-Hurtado, Hinde Taleb, Santiago Barbarisi, Gwenole Quellec, Danail Stoyanov
http://arxiv.org/abs/1906.11586v1
• [cs.CV]Dealing with Topological Information within a Fully Convolutional Neural Network
Etienne Decencière, Santiago Velasco-Forero, Fu Min, Juanjuan Chen, Hélène Burdin, Gervais Gauthier, Bruno Laÿ, Thomas Bornschloegl, Thérèse Baldeweck
http://arxiv.org/abs/1906.11600v1
• [cs.CV]Detection of small changes in medical and random-dot images comparing self-organizing map performance to human detection
John Wandeto, Henry Nyongesa, Yves Remond, Birgitta Dresp-Langley
http://arxiv.org/abs/1906.11675v1
• [cs.CV]Developing an App to interpret Chest X-rays to support the diagnosis of respiratory pathology with Artificial Intelligence
Andrew Elkins, Felipe F. Freitas, Veronica Sanz
http://arxiv.org/abs/1906.11282v1
• [cs.CV]ELKPPNet: An Edge-aware Neural Network with Large Kernel Pyramid Pooling for Learning Discriminative Features in Semantic Segmentation
Xianwei Zheng, Linxi Huan, Hanjiang Xiong, Jianya Gong
http://arxiv.org/abs/1906.11428v1
• [cs.CV]Effective Rotation-invariant Point CNN with Spherical Harmonics kernels
Adrien Poulenard, Marie-Julie Rakotosaona, Yann Ponty, Maks Ovsjanikov
http://arxiv.org/abs/1906.11555v1
• [cs.CV]Emergence of Exploratory Look-Around Behaviors through Active Observation Completion
Santhosh K. Ramakrishnan, Dinesh Jayaraman, Kristen Grauman
http://arxiv.org/abs/1906.11407v1
• [cs.CV]Few-Shot Video Classification via Temporal Alignment
Kaidi Cao, Jingwei Ji, Zhangjie Cao, Chien-Yi Chang, Juan Carlos Niebles
http://arxiv.org/abs/1906.11415v1
• [cs.CV]Hard Pixels Mining: Learning Using Privileged Information for Semantic Segmentation
Zhangxuan Gu, Li Niu, Liqing Zhang
http://arxiv.org/abs/1906.11437v1
• [cs.CV]Loss Switching Fusion with Similarity Search for Video Classification
Lei Wang, Du Q. Huynh, Moussa Reda Mansour
http://arxiv.org/abs/1906.11465v1
• [cs.CV]Region Refinement Network for Salient Object Detection
Zhuotao Tian, Hengshuang Zhao, Michelle Shu, Jiaze Wang, Ruiyu Li, Xiaoyong Shen, Jiaya Jia
http://arxiv.org/abs/1906.11443v1
• [cs.CV]SpliceRadar: A Learned Method For Blind Image Forensics
Aurobrata Ghosh, Zheng Zhong, Terrance E Boult, Maneesh Singh
http://arxiv.org/abs/1906.11663v1
• [cs.CY]Artificial Intelligence: the global landscape of ethics guidelines
Anna Jobin, Marcello Ienca, Effy Vayena
http://arxiv.org/abs/1906.11668v1
• [cs.CY]Data Consortia
Eric Bax, John Donald, Melissa Gerber, Lisa Giaffo, Tanisha Sharma, Nikki Thompson, Kimberly Williams
http://arxiv.org/abs/1906.11803v1
• [cs.CY]Fairness criteria through the lens of directed acyclic graphical models
Benjamin R. Baer, Daniel E. Gilbert, Martin T. Wells
http://arxiv.org/abs/1906.11333v1
• [cs.DC]DiPETrans: A Framework for Distributed Parallel Execution of Transactions of Blocks in Blockchain
Baheti Shrey, Anjana Parwat Singh, Peri Sathya, Simmhan Yogesh
http://arxiv.org/abs/1906.11721v1
• [cs.DC]HEATS: Heterogeneity- and Energy-Aware Task-based Scheduling
Isabelly Rocha, Christian Göttel, Pascal Felber, Marcelo Pasin, Romain Rouvoy, Valerio Schiavoni
http://arxiv.org/abs/1906.11321v1
• [cs.DC]Improved Distributed Approximation to Maximum Independent Set
Ken-ichi Kawarabayashi, Seri Khoury, Aaron Schild, Gregory Schwartzman
http://arxiv.org/abs/1906.11524v1
• [cs.DL]Improving Academic Plagiarism Detection for STEM Documents by Analyzing Mathematical Content and Citations
Norman Meuschke, Vincent Stange, Moritz Schubotz, Michael Karmer, Bela Gipp
http://arxiv.org/abs/1906.11761v1
• [cs.DS]A Tight Analysis of Greedy Yields Subexponential Time Approximation for Uniform Decision Tree
Ray Li, Percy Liang, Stephen Mussmann
http://arxiv.org/abs/1906.11385v1
• [cs.DS]Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection
Yihe Dong, Samuel B. Hopkins, Jerry Li
http://arxiv.org/abs/1906.11366v1
• [cs.DS]The Adversarial Robustness of Sampling
Omri Ben-Eliezer, Eylon Yogev
http://arxiv.org/abs/1906.11327v1
• [cs.GR]ORRB — OpenAI Remote Rendering Backend
Maciek Chociej, Peter Welinder, Lilian Weng
http://arxiv.org/abs/1906.11633v1
• [cs.GR]Optimizing for Aesthetically Pleasing Quadrotor Camera Motion
Christoph Gebhardt, Stefan Stevsic, Otmar Hilliges
http://arxiv.org/abs/1906.11686v1
• [cs.HC]Airways: Optimization-Based Planning of Quadrotor Trajectories according to High-Level User Goals
Christoph Gebhardt, Benjamin Hepp, Tobias Naegeli, Stefan Stevsic, Otmar Hilliges
http://arxiv.org/abs/1906.11669v1
• [cs.HC]User Validation of Recommendation Serendipity Metrics
Li Chen, Ningxia Wang, Yonghua Yang, Keping Yang, Quan Yuan
http://arxiv.org/abs/1906.11431v1
• [cs.IR]A Simple Deep Personalized Recommendation System
Pavlos Mitsoulis-Ntompos, Meisam Hejazinia, Serena Zhang, Travis Brady
http://arxiv.org/abs/1906.11336v1
• [cs.IR]Re-ranking Based Diversification: A Unifying View
Shameem A Puthiya Parambath
http://arxiv.org/abs/1906.11285v1
• [cs.IR]Reducing Popularity Bias in Recommendation Over Time
Himan Abdollahpouri, Robin Burke
http://arxiv.org/abs/1906.11711v1
• [cs.IR]Representation Learning of Music Using Artist, Album, and Track Information
Jongpil Lee, Jiyoung Park, Juhan Nam
http://arxiv.org/abs/1906.11783v1
• [cs.IR]Toward Simulating Environments in Reinforcement Learning Based Recommendations
Xiangyu Zhao, Long Xia, Zhuoye Ding, Dawei Yin, Jiliang Tang
http://arxiv.org/abs/1906.11462v1
• [cs.IT]Array Codes with Local Properties
Mario Blaum, Steven R. Hetzler
http://arxiv.org/abs/1906.11731v1
• [cs.IT]On the Energy Efficiency of Limited-Backhaul Cell-Free Massive MIMO
Manijeh Bashar, Kanapathippillai Cumanan, Alister G. Burr, Hien Quoc Ngo, Erik G. Larsson, Pei Xiao
http://arxiv.org/abs/1906.11639v1
• [cs.IT]On the Sparseness of Certain MRD Codes
Heide Gluesing-Luerssen
http://arxiv.org/abs/1906.11691v1
• [cs.IT]Private Information Retrieval with Private Coded Side Information: The Multi-Server Case
Fatemeh Kazemi, Esmaeil Karimi, Anoosheh Heidarzadeh, Alex Sprintson
http://arxiv.org/abs/1906.11278v1
• [cs.LG]A Survey on GANs for Anomaly Detection
Federico Di Mattia, Paolo Galeone, Michele De Simoni, Emanuele Ghelfi
http://arxiv.org/abs/1906.11632v1
• [cs.LG]A Tractable Algorithm For Finite-Horizon Continuous Reinforcement Learning
Phanideep Gampa, Sairam Satwik Kondamudi, Lakshmanan Kailasam
http://arxiv.org/abs/1906.11245v1
• [cs.LG]Accelerating Large-Kernel Convolution Using Summed-Area Tables
Linguang Zhang, Maciej Halber, Szymon Rusinkiewicz
http://arxiv.org/abs/1906.11367v1
• [cs.LG]Adversarial FDI Attack against AC State Estimation with ANN
Tian Liu, Tao Shu
http://arxiv.org/abs/1906.11328v1
• [cs.LG]Adversarial Robustness via Adversarial Label-Smoothing
Morgane Goibert, Elvis Dohmatob
http://arxiv.org/abs/1906.11567v1
• [cs.LG]Clustering by the way of atomic fission
Shizhan Lu
http://arxiv.org/abs/1906.11416v1
• [cs.LG]Curriculum Learning for Deep Generative Models with Clustering
Deli Zhao, Jiapeng Zhu, Zhenfang Guo, Bo Zhang
http://arxiv.org/abs/1906.11594v1
• [cs.LG]Encoding Database Schemas with Relation-Aware Self-Attention for Text-to-SQL Parsers
Richard Shin
http://arxiv.org/abs/1906.11790v1
• [cs.LG]ExTra: Transfer-guided Exploration
Anirban Santara, Rishabh Madan, Balaraman Ravindran, Pabitra Mitra
http://arxiv.org/abs/1906.11785v1
• [cs.LG]Hyp-RL : Hyperparameter Optimization by Reinforcement Learning
Hadi S. Jomaa, Josif Grabocka, Lars Schmidt-Thieme
http://arxiv.org/abs/1906.11527v1
• [cs.LG]Latent Optimization for Non-adversarial Representation Disentanglement
Aviv Gabbay, Yedid Hoshen
http://arxiv.org/abs/1906.11796v1
• [cs.LG]Learning Fair Representations for Kernel Models
Zilong Tan, Samuel Yeom, Matt Fredrikson, Ameet Talwalkar
http://arxiv.org/abs/1906.11813v1
• [cs.LG]Mind2Mind : transfer learning for GANs
Yaël Frégier, Jean-Baptiste Gouray
http://arxiv.org/abs/1906.11613v1
• [cs.LG]Near Optimal Stratified Sampling
Tiancheng Yu, Xiyu Zhai, Suvrit Sra
http://arxiv.org/abs/1906.11289v1
• [cs.LG]No Pressure! Addressing the Problem of Local Minima in Manifold Learning Algorithms
Max Vladymyrov
http://arxiv.org/abs/1906.11389v1
• [cs.LG]One Size Does Not Fit All: Quantifying and Exposing the Accuracy-Latency Trade-off in Machine Learning Cloud Service APIs via Tolerance Tiers
Matthew Halpern, Behzad Boroujerdian, Todd Mummert, Evelyn Duesterwald, Vijay Janapa Reddi
http://arxiv.org/abs/1906.11307v1
• [cs.LG]Personalized Student Stress Prediction with Deep Multitask Network
Abhinav Shaw, Natcha Simsiri, Iman Deznaby, Madalina Fiterau, Tauhidur Rahaman
http://arxiv.org/abs/1906.11356v1
• [cs.LG]Regularized Hierarchical Policies for Compositional Transfer in Robotics
Markus Wulfmeier, Abbas Abdolmaleki, Roland Hafner, Jost Tobias Springenberg, Michael Neunert, Tim Hertweck, Thomas Lampe, Noah Siegel, Nicolas Heess, Martin Riedmiller
http://arxiv.org/abs/1906.11228v2
• [cs.LG]Singular Value Decomposition and Neural Networks
Bernhard Bermeitinger, Tomas Hrycej, Siegfried Handschuh
http://arxiv.org/abs/1906.11755v1
• [cs.LG]Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference
Klas Leino, Matt Fredrikson
http://arxiv.org/abs/1906.11798v1
• [cs.LG]Uncertainty Estimates for Ordinal Embeddings
Michael Lohaus, Philipp Hennig, Ulrike von Luxburg
http://arxiv.org/abs/1906.11655v1
• [cs.LG]User-Oriented Summaries Using a PSO Based Scoring Optimization Method
Augusto Villa-Monte, Laura Lanzarini, Aurelio F. Bariviera, José A. Olivas
http://arxiv.org/abs/1906.11290v1
• [cs.LG]Using Intuition from Empirical Properties to Simplify Adversarial Training Defense
Guanxiong Liu, Issa Khalil, Abdallah Khreishah
http://arxiv.org/abs/1906.11729v1
• [cs.NE]Evolving Robust Neural Architectures to Defend from Adversarial Attacks
Danilo Vasconcellos Vargas, Shashank Kotyan
http://arxiv.org/abs/1906.11667v1
• [cs.NE]On improving deep learning generalization with adaptive sparse connectivity
Shiwei Liu, Decebal Constantin Mocanu, Mykola Pechenizkiy
http://arxiv.org/abs/1906.11626v1
• [cs.NI]A Key 6G Challenge and Opportunity — Connecting the Remaining 4 Billions: A Survey on Rural Connectivity
Elias Yaacoub, Mohamed-Slim Alouini
http://arxiv.org/abs/1906.11541v1
• [cs.NI]An Algorithm for Transmitting VR Video Based on Adaptive Modulation
Jie Feng, Yongpeng Wu, Guangtao Zhai, Ning Liu, Wenjun Zhang
http://arxiv.org/abs/1906.11402v1
• [cs.NI]Capacity and Coverage Enhancement Using Long-Endurance Tethered Airborne Base Stations
Mustafa A. Kishk, Ahmed Bader, Mohamed-Slim Alouini
http://arxiv.org/abs/1906.11559v1
• [cs.NI]Security of 5G-Mobile Backhaul Networks: A Survey
Gaurav Choudhary, Jiyoon Kim, Vishal Sharma
http://arxiv.org/abs/1906.11427v1
• [cs.RO]A Constant-Factor Approximation Algorithm for Online Coverage Path Planning with Energy Constraint
Ayan Dutta, Gokarna Sharma
http://arxiv.org/abs/1906.11750v1
• [cs.RO]Automatic Coverage Selection for Surface-Based Visual Localization
James Mount, Les Dawes, Michael Milford
http://arxiv.org/abs/1906.11419v1
• [cs.RO]Automatic Detection of Myocontrol Failures Based upon Situational Context Information
Karoline Heiwolt, Claudio Zito, Markus Nowak, Claudio Castellini, Rustam Stolkin
http://arxiv.org/abs/1906.11564v1
• [cs.RO]DeepVIO: Self-supervised Deep Learning of Monocular Visual Inertial Odometry using 3D Geometric Constraints
Liming Han, Yimin Lin, Guoguang Du, Shiguo Lian
http://arxiv.org/abs/1906.11435v1
• [cs.RO]Demonstration-Guided Deep Reinforcement Learning of Control Policies for Dexterous Human-Robot Interaction
Sammy Christen, Stefan Stevsic, Otmar Hilliges
http://arxiv.org/abs/1906.11695v1
• [cs.RO]Generative grasp synthesis from demonstration using parametric mixtures
Ermano Arruda, Claudio Zito, Mohan Sridharan, Marek Kopicki, Jeremy L. Wyatt
http://arxiv.org/abs/1906.11548v1
• [cs.RO]Methodology of Designing Multi-agent Robot Control Systems Utilising Hierarchical Petri Nets
Maksym Figat, Cezary Zieliński
http://arxiv.org/abs/1906.11614v1
• [cs.RO]Modal-based Kinematics and Contact Detection of Soft Robots
Yue Chen, Long Wang, Kevin Galloway, Isuru Godage, Nabil Simaan, Eric Barth
http://arxiv.org/abs/1906.11654v1
• [cs.RO]Multi-Robot Patrolling with Sensing Idleness and Data Delay Objectives
Jürgen Scherer, Bernhard Rinner
http://arxiv.org/abs/1906.11539v1
• [cs.RO]Raven: Open Surgical Robotic Platforms
Yangming Li, Blake Hannaford, Jacob Rosen
http://arxiv.org/abs/1906.11747v1
• [cs.SI]Deception Strategies and Threats for Online Discussions
Onur Varol, Ismail Uluturk
http://arxiv.org/abs/1906.11371v1
• [cs.SI]Link weights recovery in heterogeneous information networks
Hong-Lan Botterman, Robin Lamarche-Perrin
http://arxiv.org/abs/1906.11727v1
• [cs.SI]Reducing Spreading Processes on Networks to Markov Population Models
Gerrit Großmann, Luca Bortolussi
http://arxiv.org/abs/1906.11508v1
• [eess.AS]RUSLAN: Russian Spoken Language Corpus for Speech Synthesis
Lenar Gabdrakhmanov, Rustem Garaev, Evgenii Razinkov
http://arxiv.org/abs/1906.11645v1
• [eess.IV]Abnormal Colon Polyp Image Synthesis Using Conditional Adversarial Networks for Improved Detection Performance
Younghak Shin, Hemin Ali Qadir, Ilangko Balasingham
http://arxiv.org/abs/1906.11467v1
• [eess.IV]Automated Segmentation of Hip and Thigh Muscles in Metal Artifact-Contaminated CT using Convolutional Neural Network-Enhanced Normalized Metal Artifact Reduction
Mitsuki Sakamoto, Yuta Hiasa, Yoshito Otake, Masaki Takao, Yuki Suzuki, Nobuhiko Sugano, Yoshinobu Sato
http://arxiv.org/abs/1906.11484v1
• [eess.IV]Deep Siamese Multi-scale Convolutional Network for Change Detection in Multi-temporal VHR Images
Hongruixuan Chen, Chen Wu, Bo Du, Liangpei Zhang
http://arxiv.org/abs/1906.11479v1
• [eess.IV]More chemical detection through less sampling: amplifying chemical signals in hyperspectral data cubes through compressive sensing
Henry Kvinge, Elin Farnell, Julia R. Dupuis, Michael Kirby, Chris Peterson, Elizabeth C. Schundler
http://arxiv.org/abs/1906.11818v1
• [eess.SP]A PolSAR Scattering Power Factorization Framework and Novel Roll-Invariant Parameters Based Unsupervised Classification Scheme Using a Geodesic Distance
Debanshu Ratha, Eric Pottier, Avik Bhattacharya, Alejandro C. Frery
http://arxiv.org/abs/1906.11577v1
• [eess.SP]Large-scale 3D point cloud representations via graph inception networks with applications to autonomous driving
Siheng Chen, Sufeng. Niu, Tian Lan, Baoan Liu
http://arxiv.org/abs/1906.11359v1
• [eess.SY]Approximate Dynamic Programming For Linear Systems with State and Input Constraints
Ankush Chakrabarty, Rien Quirynen, Claus Danielson, Weinan Gao
http://arxiv.org/abs/1906.11369v1
• [math.OC]A Tutorial on Concentration Bounds for System Identification
Nikolai Matni, Stephen Tu
http://arxiv.org/abs/1906.11395v1
• [math.OC]Bilinear Compressed Sensing under known Signs via Convex Programming
Alireza Aghasi, Ali Ahmed, Paul Hand, Babhru Joshi
http://arxiv.org/abs/1906.11636v1
• [math.OC]From self-tuning regulators to reinforcement learning and back again
Nikolai Matni, Alexandre Proutiere, Anders Rantzer, Stephen Tu
http://arxiv.org/abs/1906.11392v1
• [math.OC]High-Dimensional Optimization in Adaptive Random Subspaces
Jonathan Lacotte, Mert Pilanci, Marco Pavone
http://arxiv.org/abs/1906.11809v1
• [math.PR]Correlators of Polynomial Processes
Fred Espen Benth, Silvia Lavagnini
http://arxiv.org/abs/1906.11320v1
• [math.ST]Empirical Process Results for Exchangeable Arrays
Laurent Davezies, Xavier D’Haultfoeuille, Yannick Guyonvarch
http://arxiv.org/abs/1906.11293v1
• [math.ST]Rerandomization and Regression Adjustment
Xinran Li, Peng Ding
http://arxiv.org/abs/1906.11291v1
• [math.ST]Statistically and Computationally Efficient Change Point Localization in Regression Settings
Daren Wang, Kevin Lin, Rebecca Willett
http://arxiv.org/abs/1906.11364v1
• [math.ST]The exact form of the ‘Ockham factor’ in model selection
Jonathan Rougier, Carey Priebe
http://arxiv.org/abs/1906.11592v1
• [nlin.AO]Repeated sequential learning increases memory capacity via effective decorrelation in a recurrent neural network
Tomoki Kurikawa, Omri Barak, Kunihiko Kaneko
http://arxiv.org/abs/1906.11770v1
• [physics.comp-ph]Deep neural network for Wannier function centers
Linfeng Zhang, Mohan Chen, Xifan Wu, Han Wang, Weinan E, Roberto Car
http://arxiv.org/abs/1906.11434v1
• [physics.soc-ph]Broken Detailed Balance and Non-Equilibrium Dynamics in Noisy Social Learning Models
Tushar Vaidya, Thiparat Chotibut, Georgios Piliouras
http://arxiv.org/abs/1906.11481v1
• [physics.soc-ph]Hypernetwork Science via High-Order Hypergraph Walks
Sinan G. Aksoy, Cliff Joslyn, Carlos Ortiz Marrero, Brenda Praggastis, Emilie Purvine
http://arxiv.org/abs/1906.11295v1
• [quant-ph]Reachability Deficits in Quantum Approximate Optimization
V. Akshay, H. Philathong, M. E. S. Morales, J. Biamonte
http://arxiv.org/abs/1906.11259v1
• [stat.AP]A strategy for the matching of mobile phone signals with census data
Rodolfo Metulini, Maurizio Carpita
http://arxiv.org/abs/1906.11739v1
• [stat.AP]An anisotropic model for global climate data
Nil Venet, Alessandro Fassò
http://arxiv.org/abs/1906.11585v1
• [stat.AP]Detecting and classifying moments in basketball matches using sensor tracked data
Tullio Facchinetti, Rodolfo Metulini, Paola Zuccolotto
http://arxiv.org/abs/1906.11720v1
• [stat.AP]How response designs and class proportions affect the accuracy of validation data
Julien Radoux, François Waldner, Patrick Bogaert
http://arxiv.org/abs/1906.11396v1
• [stat.AP]Know your population and know your model: Using model-based regression and poststratification to generalize findings beyond the observed sample
Lauren Kennedy, Andrew Gelman
http://arxiv.org/abs/1906.11323v1
• [stat.AP]Quality analysis in acyclic production networks
Abraham Gutierrez, Sebastian Mueller
http://arxiv.org/abs/1906.11609v1
• [stat.AP]Unsupervised Methods for Identifying Pass Coverage Among Defensive Backs with NFL Player Tracking Data
Rishav Dutta, Ronald Yurko, Samuel Ventura
http://arxiv.org/abs/1906.11373v1
• [stat.ME]A Simultaneous Transformation and Rounding Approach for Modeling Integer-Valued Data
Daniel R. Kowal, Antonio Canale
http://arxiv.org/abs/1906.11653v1
• [stat.ME]Estimation of treatment effects following a sequential trial of multiple treatments
John Whitehead, Yasin Desai, Thomas Jaki
http://arxiv.org/abs/1906.11324v1
• [stat.ME]Interpretable Almost-Matching-Exactly With Instrumental Variables
M. Usaid Awan, Yameng Liu, Marco Morucci, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
http://arxiv.org/abs/1906.11658v1
• [stat.ME]Selective Inference via Marginal Screening for High Dimensional Classification
Yuta Umezu, Ichiro Takeuchi
http://arxiv.org/abs/1906.11382v1
• [stat.ML]‘In-Between’ Uncertainty in Bayesian Neural Networks
Andrew Y. K. Foong, Yingzhen Li, José Miguel Hernández-Lobato, Richard E. Turner
http://arxiv.org/abs/1906.11537v1
• [stat.ML]A global approach for learning sparse Ising models
Daniela De Canditiis
http://arxiv.org/abs/1906.11641v1
• [stat.ML]Benign Overfitting in Linear Regression
Peter L. Bartlett, Philip M. Long, Gábor Lugosi, Alexander Tsigler
http://arxiv.org/abs/1906.11300v1
• [stat.ML]Deep Active Learning with Adaptive Acquisition
Manuel Haussmann, Fred A. Hamprecht, Melih Kandemir
http://arxiv.org/abs/1906.11471v1
• [stat.ML]Fast Training of Sparse Graph Neural Networks on Dense Hardware
Matej Balog, Bart van Merriënboer, Subhodeep Moitra, Yujia Li, Daniel Tarlow
http://arxiv.org/abs/1906.11786v1
• [stat.ML]Hierarchical Data Reduction and Learning
Prashant Shekhar, Abani Patra
http://arxiv.org/abs/1906.11426v1
• [stat.ML]Hierarchical Optimal Transport for Multimodal Distribution Alignment
John Lee, Max Dabagia, Eva L. Dyer, Christopher J. Rozell
http://arxiv.org/abs/1906.11768v1
• [stat.ML]Tuning-Free Disentanglement via Projection
Yue Bai, Leo L. Duan
http://arxiv.org/abs/1906.11732v1