astro-ph.CO - 宇宙学和天体物理学
cs.AI - 人工智能 cs.CG - 计算几何学 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.DS - 数据结构与算法 cs.GR - 计算机图形学 cs.GT - 计算机科学与博弈论 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.MA - 多代理系统 cs.NE - 神经与进化计算 cs.PL - 编程语言 cs.RO - 机器人学 cs.SI - 社交网络与信息网络 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.ST - 统计理论 physics.ao-ph - 大气和海洋物理 physics.comp-ph - 计算物理学 physics.data-an - 数据分析、 统计和概率 physics.soc-ph - 物理学与社会 q-fin.ST - 统计金融学 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [astro-ph.CO]Gaussbock: Fast parallel-iterative cosmological parameter estimation with Bayesian nonparametrics
• [cs.AI]Automatic Generation of Level Maps with the Do What’s Possible Representation
• [cs.AI]Deep Q-Learning with Q-Matrix Transfer Learning for Novel Fire Evacuation Environment
• [cs.AI]ENIGMAWatch: ProofWatch Meets ENIGMA
• [cs.AI]Knowledge Graph Embedding Bi-Vector Models for Symmetric Relation
• [cs.AI]Minimizing the Negative Side Effects of Planning with Reduced Models
• [cs.AI]On modelling the emergence of logical thinking
• [cs.AI]The African Wildlife Ontology tutorial ontologies: requirements, design, and content
• [cs.CG]Automated Process Planning for Turning: A Feature-Free Approach
• [cs.CL]An Investigation of Transfer Learning-Based Sentiment Analysis in Japanese
• [cs.CL]Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned
• [cs.CL]FastSpeech: Fast, Robust and Controllable Text to Speech
• [cs.CL]GWU NLP Lab at SemEval-2019 Task 3: EmoContext: Effective Contextual Information in Models for Emotion Detection in Sentence-level in a Multigenre Corpus
• [cs.CL]MCScript2.0: A Machine Comprehension Corpus Focused on Script Events and Participants
• [cs.CL]Misspelling Oblivious Word Embeddings
• [cs.CL]Multi-hop Reading Comprehension via Deep Reinforcement Learning based Document Traversal
• [cs.CR]Detecting Malicious PowerShell Scripts Using Contextual Embeddings
• [cs.CR]Elliptical Perturbations for Differential Privacy
• [cs.CR]KNG: The K-Norm Gradient Mechanism
• [cs.CR]Privacy-Preserving Obfuscation of Critical Infrastructure Networks
• [cs.CR]StrongChain: Transparent and Collaborative Proof-of-Work Consensus
• [cs.CV]A Convolutional Cost-Sensitive Crack Localization Algorithm for Automated and Reliable RC Bridge Inspection
• [cs.CV]A Direct Approach to Robust Deep Learning Using Adversarial Networks
• [cs.CV]AttentionRNN: A Structured Spatial Attention Mechanism
• [cs.CV]Automating Whole Brain Histology to MRI Registration: Implementation of a Computational Pipeline
• [cs.CV]Constrained Design of Deep Iris Networks
• [cs.CV]Depth Estimation on Underwater Omni-directional Images Using a Deep Neural Network
• [cs.CV]Image Fusion via Sparse Regularization with Non-Convex Penalties
• [cs.CV]Network Pruning via Transformable Architecture Search
• [cs.CV]Pose estimator and tracker using temporal flow maps for limbs
• [cs.CV]PoseRBPF: A Rao-Blackwellized Particle Filter for 6D Object Pose Tracking
• [cs.CV]Prototype Reminding for Continual Learning
• [cs.CV]Robust Point Cloud Based Reconstruction of Large-Scale Outdoor Scenes
• [cs.CV]Spatial Group-wise Enhance: Improving Semantic Feature Learning in Convolutional Networks
• [cs.CV]Speech2Face: Learning the Face Behind a Voice
• [cs.CV]Watermark retrieval from 3D printed objects via synthetic data training
• [cs.CY]Digital Normativity: A challenge for human subjectivization and free will
• [cs.CY]The tradeoff between the utility and risk of location data and implications for public good
• [cs.DB]COBS: a Compact Bit-Sliced Signature Index
• [cs.DB]Towards Global Asset Management in Blockchain Systems
• [cs.DC]Cross-chain Deals and Adversarial Commerce
• [cs.DC]KPynq: A Work-Efficient Triangle-Inequality based K-means on FPGA
• [cs.DC]Kaleido: An Efficient Out-of-core Graph Mining System on A Single Machine
• [cs.DC]Positional Encoding by Robots with Non-Rigid Movements
• [cs.DC]Topological Characterization of Consensus under General Message Adversaries
• [cs.DC]Workflow Design Analysis for High Resolution Satellite Image Analysis
• [cs.DS]An Efficient Approach for Super and Nested Term Indexing and Retrieval
• [cs.GR]Data-Driven Crowd Simulation with Generative Adversarial Networks
• [cs.GT]Diffusion and Auction on Graphs
• [cs.IR]Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction
• [cs.IT]A Simple Receive Diversity Technique for Distributed Beamforming
• [cs.IT]Downlink Non-Orthogonal Multiple Access without SIC for Block Fading Channels: An Algebraic Rotation Approach
• [cs.IT]Johnson-Lindenstrauss Property Implies Subspace Restricted Isometry Property
• [cs.IT]Optimum Low-Complexity Decoder for Spatial Modulation
• [cs.IT]Rate-Distortion-Memory Trade-offs in Heterogeneous Caching Networks
• [cs.IT]Simple Bounds for the Symmetric Capacity of the Rayleigh Fading Multiple Access Channel
• [cs.LG]Accelerating DNN Training in Wireless Federated Edge Learning System
• [cs.LG]Action Assembly: Sparse Imitation Learning for Text Based Games with Combinatorial Action Spaces
• [cs.LG]Adversarially Robust Distillation
• [cs.LG]Augmenting correlation structures in spatial data using deep generative models
• [cs.LG]Average reward reinforcement learning with unknown mixing times
• [cs.LG]Binary Classification with Bounded Abstention Rate
• [cs.LG]Causal Discovery with Cascade Nonlinear Additive Noise Models
• [cs.LG]Cognitive Model Priors for Predicting Human Decisions
• [cs.LG]Combination of linear classifiers using score function — analysis of possible combination strategies
• [cs.LG]Combine PPO with NES to Improve Exploration
• [cs.LG]Compression with Flows via Local Bits-Back Coding
• [cs.LG]Convergence Analyses of Online ADAM Algorithm in Convex Setting and Two-Layer ReLU Neural Network
• [cs.LG]DEEP-BO for Hyperparameter Optimization of Deep Networks
• [cs.LG]Decentralized Learning of Generative Adversarial Networks from Multi-Client Non-iid Data
• [cs.LG]Disentangling Redundancy for Multi-Task Pruning
• [cs.LG]Ensemble Model Patching: A Parameter-Efficient Variational Bayesian Neural Network
• [cs.LG]Estimating Risk and Uncertainty in Deep Reinforcement Learning
• [cs.LG]FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction
• [cs.LG]Fire Now, Fire Later: Alarm-Based Systems for Prescriptive Process Monitoring
• [cs.LG]From semantics to execution: Integrating action planning with reinforcement learning for robotic tool use
• [cs.LG]Fully Neural Network based Model for General Temporal Point Processes
• [cs.LG]Generative Imputation and Stochastic Prediction
• [cs.LG]Geometric Laplacian Eigenmap Embedding
• [cs.LG]Glioma Grade Predictions using Scattering Wavelet Transform-Based Radiomics
• [cs.LG]Gravity-Inspired Graph Autoencoders for Directed Link Prediction
• [cs.LG]Hierarchical Annotation of Images with Two-Alternative-Forced-Choice Metric Learning
• [cs.LG]How degenerate is the parametrization of neural networks with the ReLU activation function?
• [cs.LG]Imitation Learning from Video by Leveraging Proprioception
• [cs.LG]Interpreting Adversarially Trained Convolutional Neural Networks
• [cs.LG]Inverse Reinforcement Learning in Contextual MDPs
• [cs.LG]Kernel Wasserstein Distance
• [cs.LG]Learning Discrete and Continuous Factors of Data via Alternating Disentanglement
• [cs.LG]Leveraging Uncertainty in Deep Learning for Selective Classification
• [cs.LG]MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling
• [cs.LG]MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies
• [cs.LG]MR-GNN: Multi-Resolution and Dual Graph Neural Network for Predicting Structured Entity Interactions
• [cs.LG]Meta-GNN: On Few-shot Node Classification in Graph Meta-learning
• [cs.LG]Multi-Service Mobile Traffic Forecasting via Convolutional Long Short-Term Memories
• [cs.LG]Multi-relational Poincaré Graph Embeddings
• [cs.LG]Multinomial Distribution Learning for Effective Neural Architecture Search
• [cs.LG]New methods for SVM feature selection
• [cs.LG]Non-monotone DR-submodular Maximization: Approximation and Regret Guarantees
• [cs.LG]Outlier Robust Extreme Learning Machine for Multi-Target Regression
• [cs.LG]Parsimonious Deep Learning: A Differential Inclusion Approach with Global Convergence
• [cs.LG]Quantifying Long Range Dependence in Language and User Behavior to improve RNNs
• [cs.LG]Recurrent Value Functions
• [cs.LG]Some limitations of norm based generalization bounds in deep neural networks
• [cs.LG]The Convolutional Tsetlin Machine
• [cs.LG]The Journey is the Reward: Unsupervised Learning of Influential Trajectories
• [cs.LG]Tucker Decomposition Network: Expressive Power and Comparison
• [cs.LG]Zero-shot Knowledge Transfer via Adversarial Belief Matching
• [cs.LO]Learning to Prove Theorems via Interacting with Proof Assistants
• [cs.MA]Nature-Inspired Computational Model of Population Desegregation under Group Leaders Influence
• [cs.NE]CUDA-Self-Organizing feature map based visual sentiment analysis of bank customer complaints for Analytical CRM
• [cs.NE]Comparing and Combining Lexicase Selection and Novelty Search
• [cs.NE]Effect of shapes of activation functions on predictability in the echo state network
• [cs.NE]Improving Neural Networks by Adopting Amplifying and Attenuating Neurons
• [cs.NE]Lexicase Selection of Specialists
• [cs.NE]Multi-Sample Dropout for Accelerated Training and Better Generalization
• [cs.PL]Hypothetical answers to continuous queries over data streams
• [cs.RO]A ROS2 based communication architecture for control in collaborative and intelligent automation systems
• [cs.RO]Deep Drone Racing: From Simulation to Reality with Domain Randomization
• [cs.RO]Hierarchical Reinforcement Learning for Concurrent Discovery of Compound and Composable Policies
• [cs.RO]IN2LAAMA: INertial Lidar Localisation Autocalibration And MApping
• [cs.RO]Incorporating Human Domain Knowledge in 3D LiDAR-based Semantic Segmentation
• [cs.RO]Nullspace Structure in Model Predictive Control
• [cs.RO]Predictive Control for Chasing a Ground Vehicle using a UAV
• [cs.RO]Reachable Space Characterization of Markov Decision Processes with Time Variability
• [cs.RO]Teleoperator Imitation with Continuous-time Safety
• [cs.RO]Towards Generation and Evaluation of Comprehensive Mapping Robot Datasets
• [cs.RO]Towards Safety-Aware Computing System Design in Autonomous Vehicles
• [cs.RO]Variational Inference with Mixture Model Approximation: Robotic Applications
• [cs.SI]Network Density of States
• [cs.SI]Price of Dependence: Stochastic Submodular Maximization with Dependent Items
• [eess.IV]Fusion of heterogeneous bands and kernels in hyperspectral image processing
• [eess.IV]Learning Fast Magnetic Resonance Imaging
• [eess.IV]Self-supervised learning of inverse problem solvers in medical imaging
• [eess.IV]Spatio-Temporal Deep Learning Models for Tip Force Estimation During Needle Insertion
• [eess.IV]Underwater Stereo using Refraction-free Image Synthesized from Light Field Camera
• [eess.SP]A Comparative Study of Analog/Digital Self-Interference Cancellation for Full Duplex Radios
• [eess.SP]One-bit LFMCW Radar: Spectrum Analysis and Target Detection
• [math.ST]On generalized Piterbarg-Berman function
• [math.ST]Sparse Equisigned PCA: Algorithms and Performance Bounds in the Noisy Rank-1 Setting
• [math.ST]Sparse Minimax Optimality of Bayes Predictive Density Estimates from Clustered Discrete Priors
• [physics.ao-ph]Learning the Representations of Moist Convection with Convolutional Neural Networks
• [physics.comp-ph]The Stabilized Explicit Variable-Load Solver with Machine Learning Acceleration for the Rapid Solution of Stiff Chemical Kinetics
• [physics.data-an]A Predictive Model for Steady-State Multiphase Pipe Flow: Machine Learning on Lab Data
• [physics.data-an]Shades of Dark Uncertainty and Consensus Value for the Newtonian Constant of Gravitation
• [physics.soc-ph]Applied hybrid binary mixed logit to investigate pedestrian crossing safety at midblock and unsignalized intersection
• [physics.soc-ph]Scale-free networks revealed from finite-size scaling
• [physics.soc-ph]What is the Entropy of a Social Organization?
• [q-fin.ST]Detection of Chinese Stock Market Bubbles with LPPLS Confidence Indicator
• [q-fin.ST]Diagnosis and Prediction of the 2015 Chinese Stock Market Bubble
• [q-fin.ST]Real-time Prediction of Bitcoin bubble Crashes
• [stat.AP]Targeted Smooth Bayesian Causal Forests: An analysis of heterogeneous treatment effects for simultaneous versus interval medical abortion regimens over gestation
• [stat.AP]semopy: A Python package for Structural Equation Modeling
• [stat.CO]A Condition Number for Hamiltonian Monte Carlo
• [stat.ME]Atlantic Causal Inference Conference (ACIC) Data Analysis Challenge 2017
• [stat.ME]Learning When-to-Treat Policies
• [stat.ME]Random Norming Aids Analysis of Non-linear Regression Models with Sequential Informative Dose Selection
• [stat.ME]Restricted Spatial Regression Methods: Implications for Inference
• [stat.ME]Slamming the sham: A Bayesian model for adaptive adjustment with noisy control data
• [stat.ML]An Optimal Private Stochastic-MAB Algorithm Based on an Optimal Private Stopping Rule
• [stat.ML]Bayesian Optimization over Sets
• [stat.ML]Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation
• [stat.ML]Population-based Global Optimisation Methods for Learning Long-term Dependencies with RNNs
• [stat.ML]Replicated Vector Approximate Message Passing For Resampling Problem
• [stat.ML]Revisiting Graph Neural Networks: All We Have is Low-Pass Filters
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• [astro-ph.CO]Gaussbock: Fast parallel-iterative cosmological parameter estimation with Bayesian nonparametrics
Ben Moews, Joe Zuntz
http://arxiv.org/abs/1905.09800v1
• [cs.AI]Automatic Generation of Level Maps with the Do What’s Possible Representation
Daniel Ashlock, Christoph Salge
http://arxiv.org/abs/1905.09618v1
• [cs.AI]Deep Q-Learning with Q-Matrix Transfer Learning for Novel Fire Evacuation Environment
Jivitesh Sharma, Per-Arne Andersen, Ole-Chrisoffer Granmo, Morten Goodwin
http://arxiv.org/abs/1905.09673v1
• [cs.AI]ENIGMAWatch: ProofWatch Meets ENIGMA
Zarathustra Goertzel, Jan Jakubův, Josef Urban
http://arxiv.org/abs/1905.09565v1
• [cs.AI]Knowledge Graph Embedding Bi-Vector Models for Symmetric Relation
Jinkui Yao, Lianghua Xu
http://arxiv.org/abs/1905.09557v1
• [cs.AI]Minimizing the Negative Side Effects of Planning with Reduced Models
Sandhya Saisubramanian, Shlomo Zilberstein
http://arxiv.org/abs/1905.09355v1
• [cs.AI]On modelling the emergence of logical thinking
Cristian Ivan, Bipin Indurkhya
http://arxiv.org/abs/1905.09730v1
• [cs.AI]The African Wildlife Ontology tutorial ontologies: requirements, design, and content
C Maria Keet
http://arxiv.org/abs/1905.09519v1
• [cs.CG]Automated Process Planning for Turning: A Feature-Free Approach
Morad Behandish, Saigopal Nelaturi, Chaman Singh Verma, Mats Allard
http://arxiv.org/abs/1905.09434v1
• [cs.CL]An Investigation of Transfer Learning-Based Sentiment Analysis in Japanese
Enkhbold Bataa, Joshua Wu
http://arxiv.org/abs/1905.09642v1
• [cs.CL]Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned
Elena Voita, David Talbot, Fedor Moiseev, Rico Sennrich, Ivan Titov
http://arxiv.org/abs/1905.09418v1
• [cs.CL]FastSpeech: Fast, Robust and Controllable Text to Speech
Yi Ren, Yangjun Ruan, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu
http://arxiv.org/abs/1905.09263v2
• [cs.CL]GWU NLP Lab at SemEval-2019 Task 3: EmoContext: Effective Contextual Information in Models for Emotion Detection in Sentence-level in a Multigenre Corpus
Shabnam Tafreshi, Mona Diab
http://arxiv.org/abs/1905.09439v1
• [cs.CL]MCScript2.0: A Machine Comprehension Corpus Focused on Script Events and Participants
Simon Ostermann, Michael Roth, Manfred Pinkal
http://arxiv.org/abs/1905.09531v1
• [cs.CL]Misspelling Oblivious Word Embeddings
Bora Edizel, Aleksandra Piktus, Piotr Bojanowski, Rui Ferreira, Edouard Grave, Fabrizio Silvestri
http://arxiv.org/abs/1905.09755v1
• [cs.CL]Multi-hop Reading Comprehension via Deep Reinforcement Learning based Document Traversal
Alex Long, Joel Mason, Alan Blair, Wei Wang
http://arxiv.org/abs/1905.09438v1
• [cs.CR]Detecting Malicious PowerShell Scripts Using Contextual Embeddings
Amir Rubin, Shay Kels, Danny Hendler
http://arxiv.org/abs/1905.09538v1
• [cs.CR]Elliptical Perturbations for Differential Privacy
Matthew Reimherr, Jordan Awan
http://arxiv.org/abs/1905.09420v1
• [cs.CR]KNG: The K-Norm Gradient Mechanism
Matthew Reimherr, Jordan Awan
http://arxiv.org/abs/1905.09436v1
• [cs.CR]Privacy-Preserving Obfuscation of Critical Infrastructure Networks
Ferdinando Fioretto, Terrence W. K. Mak, Pascal Van Hentenryck
http://arxiv.org/abs/1905.09778v1
• [cs.CR]StrongChain: Transparent and Collaborative Proof-of-Work Consensus
Pawel Szalachowski, Daniel Reijsbergen, Ivan Homoliak, Siwei Sun
http://arxiv.org/abs/1905.09655v1
• [cs.CV]A Convolutional Cost-Sensitive Crack Localization Algorithm for Automated and Reliable RC Bridge Inspection
Seyed Omid Sajedi, Xiao Liang
http://arxiv.org/abs/1905.09716v1
• [cs.CV]A Direct Approach to Robust Deep Learning Using Adversarial Networks
Huaxia Wang, Chun-Nam Yu
http://arxiv.org/abs/1905.09591v1
• [cs.CV]AttentionRNN: A Structured Spatial Attention Mechanism
Siddhesh Khandelwal, Leonid Sigal
http://arxiv.org/abs/1905.09400v1
• [cs.CV]Automating Whole Brain Histology to MRI Registration: Implementation of a Computational Pipeline
Maryana Alegro, Eduardo J. L. Alho, Maria da Graca Morais Martin, Lea Teneholz Grinberg, Helmut Heinsen, Roseli de Deus Lopes, Edson Amaro-Jr, Lilla Zöllei
http://arxiv.org/abs/1905.09339v1
• [cs.CV]Constrained Design of Deep Iris Networks
Kien Nguyen, Clinton Fookes, Sridha Sridharan
http://arxiv.org/abs/1905.09481v1
• [cs.CV]Depth Estimation on Underwater Omni-directional Images Using a Deep Neural Network
Haofei Kuang, Qingwen Xu, Sören Schwertfeger
http://arxiv.org/abs/1905.09441v1
• [cs.CV]Image Fusion via Sparse Regularization with Non-Convex Penalties
Nantheera Anantrasirichai, Rencheng Zheng, Ivan Selesnick, Alin Achim
http://arxiv.org/abs/1905.09645v1
• [cs.CV]Network Pruning via Transformable Architecture Search
Xuanyi Dong, Yi Yang
http://arxiv.org/abs/1905.09717v1
• [cs.CV]Pose estimator and tracker using temporal flow maps for limbs
Jihye Hwang, Jieun Lee, Sungheon Park, Nojun Kwak
http://arxiv.org/abs/1905.09500v1
• [cs.CV]PoseRBPF: A Rao-Blackwellized Particle Filter for 6D Object Pose Tracking
Xinke Deng, Arsalan Mousavian, Yu Xiang, Fei Xia, Timothy Bretl, Dieter Fox
http://arxiv.org/abs/1905.09304v1
• [cs.CV]Prototype Reminding for Continual Learning
Mengmi Zhang, Tao Wang, Joo Hwee Lim, Jiashi Feng
http://arxiv.org/abs/1905.09447v1
• [cs.CV]Robust Point Cloud Based Reconstruction of Large-Scale Outdoor Scenes
Ziquan Lan, Zi Jian Yew, Gim Hee Lee
http://arxiv.org/abs/1905.09634v1
• [cs.CV]Spatial Group-wise Enhance: Improving Semantic Feature Learning in Convolutional Networks
Xiang Li, Xiaolin Hu, Jian Yang
http://arxiv.org/abs/1905.09646v1
• [cs.CV]Speech2Face: Learning the Face Behind a Voice
Tae-Hyun Oh, Tali Dekel, Changil Kim, Inbar Mosseri, William T. Freeman, Michael Rubinstein, Wojciech Matusik
http://arxiv.org/abs/1905.09773v1
• [cs.CV]Watermark retrieval from 3D printed objects via synthetic data training
Xin Zhang, Ning Jia, Ioannis Ivrissimtzis
http://arxiv.org/abs/1905.09706v1
• [cs.CY]Digital Normativity: A challenge for human subjectivization and free will
Éric Fourneret, Blaise Yvert
http://arxiv.org/abs/1905.09735v1
• [cs.CY]The tradeoff between the utility and risk of location data and implications for public good
Dan Calacci, Alex Berke, Kent Larson, Alex, Pentland
http://arxiv.org/abs/1905.09350v1
• [cs.DB]COBS: a Compact Bit-Sliced Signature Index
Timo Bingmann, Phelim Bradley, Florian Gauger, Zamin Iqbal
http://arxiv.org/abs/1905.09624v1
• [cs.DB]Towards Global Asset Management in Blockchain Systems
Victor Zakhary, Mohammad Javad Amiri, Sujaya Maiyya, Divyakant Agrawal, Amr El Abbadi
http://arxiv.org/abs/1905.09359v1
• [cs.DC]Cross-chain Deals and Adversarial Commerce
Maurice Herlihy, Barbara Liskov, Liuba Shrira
http://arxiv.org/abs/1905.09743v1
• [cs.DC]KPynq: A Work-Efficient Triangle-Inequality based K-means on FPGA
Yuke Wang, Zhaorui Zeng, Boyuan Feng, Lei Deng, Yufei Ding
http://arxiv.org/abs/1905.09345v1
• [cs.DC]Kaleido: An Efficient Out-of-core Graph Mining System on A Single Machine
Cheng Zhao, Zhibin Zhang, Peng Xu, Tianqi Zheng, Xueqi Cheng
http://arxiv.org/abs/1905.09572v1
• [cs.DC]Positional Encoding by Robots with Non-Rigid Movements
Kaustav Bose, Ranendu Adhikary, Manash Kumar Kundu, Buddhadeb Sau
http://arxiv.org/abs/1905.09786v1
• [cs.DC]Topological Characterization of Consensus under General Message Adversaries
Thomas Nowak, Ulrich Schmid, Kyrill Winkler
http://arxiv.org/abs/1905.09590v1
• [cs.DC]Workflow Design Analysis for High Resolution Satellite Image Analysis
Ioannis Paraskevakos, Matteo Turrili, Bento Collares Gonçalves, Heather J. Lynch, Shantenu Jha
http://arxiv.org/abs/1905.09766v1
• [cs.DS]An Efficient Approach for Super and Nested Term Indexing and Retrieval
Md Faisal Mahbub Chowdhury, Robert Farrell
http://arxiv.org/abs/1905.09761v1
• [cs.GR]Data-Driven Crowd Simulation with Generative Adversarial Networks
Javad Amirian, Wouter van Toll, Jean-Bernard Hayet, Julien Pettré
http://arxiv.org/abs/1905.09661v1
• [cs.GT]Diffusion and Auction on Graphs
Bin Li, Dong Hao, Dengji Zhao, Makoto Yokoo
http://arxiv.org/abs/1905.09604v1
• [cs.IR]Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction
Qi Pi, Weijie Bian, Guorui Zhou, Xiaoqiang Zhu, Kun Gai
http://arxiv.org/abs/1905.09248v2
• [cs.IT]A Simple Receive Diversity Technique for Distributed Beamforming
Elad Domanovitz, Uri Erez
http://arxiv.org/abs/1905.09321v1
• [cs.IT]Downlink Non-Orthogonal Multiple Access without SIC for Block Fading Channels: An Algebraic Rotation Approach
Min Qiu, Yu-Chih Huang, Jinhong Yuan
http://arxiv.org/abs/1905.09514v1
• [cs.IT]Johnson-Lindenstrauss Property Implies Subspace Restricted Isometry Property
Xingyu Xv, Gen Li, Yuantao Gu
http://arxiv.org/abs/1905.09608v1
• [cs.IT]Optimum Low-Complexity Decoder for Spatial Modulation
Ibrahim Al-Nahhal, Ertugrul Basar, Octavia A. Dobre, Salama Ikki
http://arxiv.org/abs/1905.09401v1
• [cs.IT]Rate-Distortion-Memory Trade-offs in Heterogeneous Caching Networks
Parisa Hassanzadeh, Antonia M. Tulino, Jaime Llorca, Elza Erkip
http://arxiv.org/abs/1905.09446v1
• [cs.IT]Simple Bounds for the Symmetric Capacity of the Rayleigh Fading Multiple Access Channel
Elad Domanovitz, Uri Erez
http://arxiv.org/abs/1905.09486v1
• [cs.LG]Accelerating DNN Training in Wireless Federated Edge Learning System
Jinke Ren, Guanding Yu, Guangyao Ding
http://arxiv.org/abs/1905.09712v1
• [cs.LG]Action Assembly: Sparse Imitation Learning for Text Based Games with Combinatorial Action Spaces
Chen Tessler, Tom Zahavy, Deborah Cohen, Daniel J. Mankowitz, Shie Mannor
http://arxiv.org/abs/1905.09700v1
• [cs.LG]Adversarially Robust Distillation
Micah Goldblum, Liam Fowl, Soheil Feizi, Tom Goldstein
http://arxiv.org/abs/1905.09747v1
• [cs.LG]Augmenting correlation structures in spatial data using deep generative models
Konstantin Klemmer, Adriano Koshiyama, Sebastian Flennerhag
http://arxiv.org/abs/1905.09796v1
• [cs.LG]Average reward reinforcement learning with unknown mixing times
Tom Zahavy, Alon Cohen, Haim Kaplan, Yishay Mansour
http://arxiv.org/abs/1905.09704v1
• [cs.LG]Binary Classification with Bounded Abstention Rate
Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
http://arxiv.org/abs/1905.09561v1
• [cs.LG]Causal Discovery with Cascade Nonlinear Additive Noise Models
Ruichu Cai, Jie Qiao, Kun Zhang, Zhenjie Zhang, Zhifeng Hao
http://arxiv.org/abs/1905.09442v1
• [cs.LG]Cognitive Model Priors for Predicting Human Decisions
David D. Bourgin, Joshua C. Peterson, Daniel Reichman, Thomas L. Griffiths, Stuart J. Russell
http://arxiv.org/abs/1905.09397v1
• [cs.LG]Combination of linear classifiers using score function — analysis of possible combination strategies
Pawel Trajdos, Robert Burduk
http://arxiv.org/abs/1905.09522v1
• [cs.LG]Combine PPO with NES to Improve Exploration
Lianjiang Li, Yunrong Yang, Bingna Li
http://arxiv.org/abs/1905.09492v1
• [cs.LG]Compression with Flows via Local Bits-Back Coding
Jonathan Ho, Evan Lohn, Pieter Abbeel
http://arxiv.org/abs/1905.08500v2
• [cs.LG]Convergence Analyses of Online ADAM Algorithm in Convex Setting and Two-Layer ReLU Neural Network
Biyi Fang, Diego Klabjan
http://arxiv.org/abs/1905.09356v1
• [cs.LG]DEEP-BO for Hyperparameter Optimization of Deep Networks
Hyunghun Cho, Yongjin Kim, Eunjung Lee, Daeyoung Choi, Yongjae Lee, Wonjong Rhee
http://arxiv.org/abs/1905.09680v1
• [cs.LG]Decentralized Learning of Generative Adversarial Networks from Multi-Client Non-iid Data
Ryo Yonetani, Tomohiro Takahashi, Atsushi Hashimoto, Yoshitaka Ushiku
http://arxiv.org/abs/1905.09684v1
• [cs.LG]Disentangling Redundancy for Multi-Task Pruning
Xiaoxi He, Dawei Gao, Zimu Zhou, Yongxin Tong, Lothar Thiele
http://arxiv.org/abs/1905.09676v1
• [cs.LG]Ensemble Model Patching: A Parameter-Efficient Variational Bayesian Neural Network
Oscar Chang, Yuling Yao, David Williams-King, Hod Lipson
http://arxiv.org/abs/1905.09453v1
• [cs.LG]Estimating Risk and Uncertainty in Deep Reinforcement Learning
William R. Clements, Benoît-Marie Robaglia, Bastien Van Delft, Reda Bahi Slaoui, Sébastien Toth
http://arxiv.org/abs/1905.09638v1
• [cs.LG]FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction
Tongwen Huang, Zhiqi Zhang, Junlin Zhang
http://arxiv.org/abs/1905.09433v1
• [cs.LG]Fire Now, Fire Later: Alarm-Based Systems for Prescriptive Process Monitoring
Stephan A. Fahrenkrog-Petersen, Niek Tax, Irene Teinemaa, Marlon Dumas, Massimiliano de Leoni, Fabrizio Maria Maggi, Matthias Weidlich
http://arxiv.org/abs/1905.09568v1
• [cs.LG]From semantics to execution: Integrating action planning with reinforcement learning for robotic tool use
Manfred Eppe, Phuong D. H. Nguyen, Stefan Wermter
http://arxiv.org/abs/1905.09683v1
• [cs.LG]Fully Neural Network based Model for General Temporal Point Processes
Takahiro Omi, Naonori Ueda, Kazuyuki Aihara
http://arxiv.org/abs/1905.09690v1
• [cs.LG]Generative Imputation and Stochastic Prediction
Mohammad Kachuee, Kimmo Karkkainen, Orpaz Goldstein, Sajad Darabi, Majid Sarrafzadeh
http://arxiv.org/abs/1905.09340v1
• [cs.LG]Geometric Laplacian Eigenmap Embedding
Leo Torres, Kevin S Chan, Tina Eliassi-Rad
http://arxiv.org/abs/1905.09763v1
• [cs.LG]Glioma Grade Predictions using Scattering Wavelet Transform-Based Radiomics
Qijian Chen, Lihui Wang, Li Wang, Zeyu Deng, Jian Zhang, Yuemin Zhu
http://arxiv.org/abs/1905.09589v1
• [cs.LG]Gravity-Inspired Graph Autoencoders for Directed Link Prediction
Guillaume Salha, Stratis Limnios, Romain Hennequin, Viet Anh Tran, Michalis Vazirgiannis
http://arxiv.org/abs/1905.09570v1
• [cs.LG]Hierarchical Annotation of Images with Two-Alternative-Forced-Choice Metric Learning
Niels Hellinga, Vlado Menkovski
http://arxiv.org/abs/1905.09523v1
• [cs.LG]How degenerate is the parametrization of neural networks with the ReLU activation function?
Julius Berner, Dennis Elbrächter, Philipp Grohs
http://arxiv.org/abs/1905.09803v1
• [cs.LG]Imitation Learning from Video by Leveraging Proprioception
Faraz Torabi, Garrett Warnell, Peter Stone
http://arxiv.org/abs/1905.09335v1
• [cs.LG]Interpreting Adversarially Trained Convolutional Neural Networks
Tianyuan Zhang, Zhanxing Zhu
http://arxiv.org/abs/1905.09797v1
• [cs.LG]Inverse Reinforcement Learning in Contextual MDPs
Philip Korsunsky, Stav Belo, Tom Zahavy, Chen Tessler, Shie Mannor
http://arxiv.org/abs/1905.09710v1
• [cs.LG]Kernel Wasserstein Distance
Jung Hun Oh, Maryam Pouryahya, Aditi Iyer, Aditya P. Apte, Allen Tannenbaum, Joseph O. Deasy
http://arxiv.org/abs/1905.09314v1
• [cs.LG]Learning Discrete and Continuous Factors of Data via Alternating Disentanglement
Yeonwoo Jeong, Hyun Oh Song
http://arxiv.org/abs/1905.09432v1
• [cs.LG]Leveraging Uncertainty in Deep Learning for Selective Classification
Mehmet Yigit Yildirim, Mert Ozer, Hasan Davulcu
http://arxiv.org/abs/1905.09509v1
• [cs.LG]MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling
Jianyu Wang, Anit Kumar Sahu, Zhouyi Yang, Gauri Joshi, Soummya Kar
http://arxiv.org/abs/1905.09435v1
• [cs.LG]MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies
Xue Bin Peng, Michael Chang, Grace Zhang, Pieter Abbeel, Sergey Levine
http://arxiv.org/abs/1905.09808v1
• [cs.LG]MR-GNN: Multi-Resolution and Dual Graph Neural Network for Predicting Structured Entity Interactions
Nuo Xu, Pinghui Wang, Long Chen, Jing Tao, Junzhou Zhao
http://arxiv.org/abs/1905.09558v1
• [cs.LG]Meta-GNN: On Few-shot Node Classification in Graph Meta-learning
Fan Zhou, Chengtai Cao, Kunpeng Zhang, Goce Trajcevski, Ting Zhong, Ji Geng
http://arxiv.org/abs/1905.09718v1
• [cs.LG]Multi-Service Mobile Traffic Forecasting via Convolutional Long Short-Term Memories
Chaoyun Zhang, Marco Fiore, Paul Patras
http://arxiv.org/abs/1905.09771v1
• [cs.LG]Multi-relational Poincaré Graph Embeddings
Ivana Balažević, Carl Allen, Timothy Hospedales
http://arxiv.org/abs/1905.09791v1
• [cs.LG]Multinomial Distribution Learning for Effective Neural Architecture Search
Xiawu Zheng, Rongrong Ji, Lang Tang, Baochang Zhang, Jianzhuang Liu, Qi Tian
http://arxiv.org/abs/1905.07529v2
• [cs.LG]New methods for SVM feature selection
Tangui Aladjidi, François Pasqualini
http://arxiv.org/abs/1905.09653v1
• [cs.LG]Non-monotone DR-submodular Maximization: Approximation and Regret Guarantees
Christoph Dürr, Nguyen Kim Thang, Abhinav Srivastav, Léo Tible
http://arxiv.org/abs/1905.09595v1
• [cs.LG]Outlier Robust Extreme Learning Machine for Multi-Target Regression
Bruno Légora Souza da Silva, Fernando Kentaro Inaba, Evandro Ottoni Teatini Salles, Patrick Marques Ciarelli
http://arxiv.org/abs/1905.09368v1
• [cs.LG]Parsimonious Deep Learning: A Differential Inclusion Approach with Global Convergence
Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan Zeng, Yuan Yao
http://arxiv.org/abs/1905.09449v1
• [cs.LG]Quantifying Long Range Dependence in Language and User Behavior to improve RNNs
Francois Belletti, Minmin Chen, Ed H. Chi
http://arxiv.org/abs/1905.09414v1
• [cs.LG]Recurrent Value Functions
Pierre Thodoroff, Nishanth Anand, Lucas Caccia, Doina Precup, Joelle Pineau
http://arxiv.org/abs/1905.09562v1
• [cs.LG]Some limitations of norm based generalization bounds in deep neural networks
Konstantinos Pitas, Andreas Loukas, Mike Davies, Pierre Vandergheynst
http://arxiv.org/abs/1905.09677v1
• [cs.LG]The Convolutional Tsetlin Machine
Ole-Christoffer Granmo, Sondre Glimsdal, Lei Jiao, Morten Goodwin, Christian W. Omlin, Geir Thore Berge
http://arxiv.org/abs/1905.09688v1
• [cs.LG]The Journey is the Reward: Unsupervised Learning of Influential Trajectories
Jonathan Binas, Sherjil Ozair, Yoshua Bengio
http://arxiv.org/abs/1905.09334v1
• [cs.LG]Tucker Decomposition Network: Expressive Power and Comparison
Ye Liu, Junjun Pan, Michael Ng
http://arxiv.org/abs/1905.09635v1
• [cs.LG]Zero-shot Knowledge Transfer via Adversarial Belief Matching
Paul Micaelli, Amos Storkey
http://arxiv.org/abs/1905.09768v1
• [cs.LO]Learning to Prove Theorems via Interacting with Proof Assistants
Kaiyu Yang, Jia Deng
http://arxiv.org/abs/1905.09381v1
• [cs.MA]Nature-Inspired Computational Model of Population Desegregation under Group Leaders Influence
Kashif Zia, Dinesh Kumar Saini, Arshad Muhammad, Alois Ferscha
http://arxiv.org/abs/1905.09795v1
• [cs.NE]CUDA-Self-Organizing feature map based visual sentiment analysis of bank customer complaints for Analytical CRM
Rohit Gavval, Vadlamani Ravi, Kalavala Revanth Harshal, Akhilesh Gangwar, Kumar Ravi
http://arxiv.org/abs/1905.09598v1
• [cs.NE]Comparing and Combining Lexicase Selection and Novelty Search
Lia Jundt, Thomas Helmuth
http://arxiv.org/abs/1905.09374v1
• [cs.NE]Effect of shapes of activation functions on predictability in the echo state network
Hanten Chang, Shinji Nakaoka, Hiroyasu Ando
http://arxiv.org/abs/1905.09419v1
• [cs.NE]Improving Neural Networks by Adopting Amplifying and Attenuating Neurons
Seongmun Jung, Oh Joon Kwon
http://arxiv.org/abs/1905.09574v1
• [cs.NE]Lexicase Selection of Specialists
Thomas Helmuth, Edward Pantridge, Lee Spector
http://arxiv.org/abs/1905.09372v1
• [cs.NE]Multi-Sample Dropout for Accelerated Training and Better Generalization
Hiroshi Inoue
http://arxiv.org/abs/1905.09788v1
• [cs.PL]Hypothetical answers to continuous queries over data streams
Luís Cruz-Filipe, Graça Gaspar, Isabel Nunes
http://arxiv.org/abs/1905.09610v1
• [cs.RO]A ROS2 based communication architecture for control in collaborative and intelligent automation systems
Endre Erős, Martin Dahl, Kristofer Bengtsson, Atieh Hanna, Petter Falkman
http://arxiv.org/abs/1905.09654v1
• [cs.RO]Deep Drone Racing: From Simulation to Reality with Domain Randomization
Antonio Loquercio, Elia Kaufmann, René Ranftl, Alexey Dosovitskiy, Vladlen Koltun, Davide Scaramuzza
http://arxiv.org/abs/1905.09727v1
• [cs.RO]Hierarchical Reinforcement Learning for Concurrent Discovery of Compound and Composable Policies
Domingo Esteban, Leonel Rozo, Darwin G. Caldwell
http://arxiv.org/abs/1905.09668v1
• [cs.RO]IN2LAAMA: INertial Lidar Localisation Autocalibration And MApping
Cedric Le Gentil, Teresa Vidal-Calleja, Shoudong Huang
http://arxiv.org/abs/1905.09517v1
• [cs.RO]Incorporating Human Domain Knowledge in 3D LiDAR-based Semantic Segmentation
Jilin Mei, Huijing Zhao
http://arxiv.org/abs/1905.09533v1
• [cs.RO]Nullspace Structure in Model Predictive Control
Hakan Girgin, Sylvain Calinon
http://arxiv.org/abs/1905.09679v1
• [cs.RO]Predictive Control for Chasing a Ground Vehicle using a UAV
Jaeseung Byun, Karan P. Jain, Siddharth H. Nair, Haoyun Xu, Jiaming Zha
http://arxiv.org/abs/1905.09396v1
• [cs.RO]Reachable Space Characterization of Markov Decision Processes with Time Variability
Junhong Xu, Yin Kai, Lantao Liu
http://arxiv.org/abs/1905.09342v1
• [cs.RO]Teleoperator Imitation with Continuous-time Safety
Bachir El Khadir, Jake Varley, Vikas Sindhwani
http://arxiv.org/abs/1905.09499v1
• [cs.RO]Towards Generation and Evaluation of Comprehensive Mapping Robot Datasets
Hongyu Chen, Xiting Zhao, Jianwen Luo, Zhijie Yang, Zehao Zhao, Haochuan Wan, Xiaoya Ye, Guangyuan Weng, Zhenpeng He, Tian Dong, Sören Schwertfeger
http://arxiv.org/abs/1905.09483v1
• [cs.RO]Towards Safety-Aware Computing System Design in Autonomous Vehicles
Hengyu Zhao, Yubo Zhang, Pingfan Meng, Hui Shi, Li Erran Li, Tiancheng Lou, Jishen Zhao
http://arxiv.org/abs/1905.08453v2
• [cs.RO]Variational Inference with Mixture Model Approximation: Robotic Applications
Emmanuel Pignat, Teguh Lembono, Sylvain Calinon
http://arxiv.org/abs/1905.09597v1
• [cs.SI]Network Density of States
Kun Dong, Austin R. Benson, David Bindel
http://arxiv.org/abs/1905.09758v1
• [cs.SI]Price of Dependence: Stochastic Submodular Maximization with Dependent Items
Shaojie Tang
http://arxiv.org/abs/1905.09719v1
• [eess.IV]Fusion of heterogeneous bands and kernels in hyperspectral image processing
Muhammad Aminul Islam, Derek T. Anderson, John E. Ball, Nicolas H. Younan
http://arxiv.org/abs/1905.09698v1
• [eess.IV]Learning Fast Magnetic Resonance Imaging
Tomer Weiss, Sanketh Vedula, Ortal Senouf, Alex Bronstein, Oleg Michailovich, Michael Zibulevsky
http://arxiv.org/abs/1905.09324v1
• [eess.IV]Self-supervised learning of inverse problem solvers in medical imaging
Ortal Senouf, Sanketh Vedula, Tomer Weiss, Alex Bronstein, Oleg Michailovich, Michael Zibulevsky
http://arxiv.org/abs/1905.09325v1
• [eess.IV]Spatio-Temporal Deep Learning Models for Tip Force Estimation During Needle Insertion
Nils Gessert, Torben Priegnitz, Thore Saathoff, Sven-Thomas Antoni, David Meyer, Moritz Franz Hamann, Klaus-Peter Jünemann, Christoph Otte, Alexander Schlaefer
http://arxiv.org/abs/1905.09282v1
• [eess.IV]Underwater Stereo using Refraction-free Image Synthesized from Light Field Camera
Kazuto Ichimaru, Hiroshi Kawasaki
http://arxiv.org/abs/1905.09588v1
• [eess.SP]A Comparative Study of Analog/Digital Self-Interference Cancellation for Full Duplex Radios
Jong Woo Kwak, Min Soo Sim, In-Woong Kang, Jong Sung Park, Jaedon Park, Chan-Byoung Chae
http://arxiv.org/abs/1905.09616v1
• [eess.SP]One-bit LFMCW Radar: Spectrum Analysis and Target Detection
Benzhou Jin, Jiang Zhu, Qihui Wu, Yuhong Zhang, Zhiwei Xu
http://arxiv.org/abs/1905.09440v1
• [math.ST]On generalized Piterbarg-Berman function
Chengxiu Ling, Hong Zhang, Long Bai
http://arxiv.org/abs/1905.09599v1
• [math.ST]Sparse Equisigned PCA: Algorithms and Performance Bounds in the Noisy Rank-1 Setting
Arvind Prasadan, Raj Rao Nadakuditi, Debashis Paul
http://arxiv.org/abs/1905.09369v1
• [math.ST]Sparse Minimax Optimality of Bayes Predictive Density Estimates from Clustered Discrete Priors
Ujan Gangopadhyay, Gourab Mukherjee
http://arxiv.org/abs/1905.09451v1
• [physics.ao-ph]Learning the Representations of Moist Convection with Convolutional Neural Networks
Shih-Wen Tsou, Chun-Yian Su, Chien-Ming Wu
http://arxiv.org/abs/1905.09614v1
• [physics.comp-ph]The Stabilized Explicit Variable-Load Solver with Machine Learning Acceleration for the Rapid Solution of Stiff Chemical Kinetics
Kyle Buchheit, Opeoluwa Owoyele, Terry Jordan, Dirk Van Essendelft
http://arxiv.org/abs/1905.09395v1
• [physics.data-an]A Predictive Model for Steady-State Multiphase Pipe Flow: Machine Learning on Lab Data
Evgenii Kanin, Andrei Osiptsov, Albert Vainshtein, Evgeny Burnaev
http://arxiv.org/abs/1905.09746v1
• [physics.data-an]Shades of Dark Uncertainty and Consensus Value for the Newtonian Constant of Gravitation
Christos Merkatas, Blaza Toman, Antonio Possolo, Stephan Schlamminger
http://arxiv.org/abs/1905.09551v1
• [physics.soc-ph]Applied hybrid binary mixed logit to investigate pedestrian crossing safety at midblock and unsignalized intersection
Mohammad Ali Arman, Amir Rafe, Tobias Kretz
http://arxiv.org/abs/1905.09403v1
• [physics.soc-ph]Scale-free networks revealed from finite-size scaling
Matteo Serafino, Giulio Cimini, Amos Maritan, Samir Suweis, Jayanth R. Banavar, Guido Caldarelli
http://arxiv.org/abs/1905.09512v1
• [physics.soc-ph]What is the Entropy of a Social Organization?
Christian Zingg, Giona Casiraghi, Giacomo Vaccario, Frank Schweitzer
http://arxiv.org/abs/1905.09772v1
• [q-fin.ST]Detection of Chinese Stock Market Bubbles with LPPLS Confidence Indicator
Min Shu, Wei Zhu
http://arxiv.org/abs/1905.09640v1
• [q-fin.ST]Diagnosis and Prediction of the 2015 Chinese Stock Market Bubble
Min Shu, Wei Zhu
http://arxiv.org/abs/1905.09633v1
• [q-fin.ST]Real-time Prediction of Bitcoin bubble Crashes
Min Shu, Wei Zhu
http://arxiv.org/abs/1905.09647v1
• [stat.AP]Targeted Smooth Bayesian Causal Forests: An analysis of heterogeneous treatment effects for simultaneous versus interval medical abortion regimens over gestation
Jennifer E. Starling, Jared S. Murray, Patricia A. Lohr, Abigail R. A. Aiken, Carlos M. Carvalho, James G. Scott
http://arxiv.org/abs/1905.09405v1
• [stat.AP]semopy: A Python package for Structural Equation Modeling
Meshcheryakov Georgy, Igolkina Anna
http://arxiv.org/abs/1905.09376v1
• [stat.CO]A Condition Number for Hamiltonian Monte Carlo
Ian Langmore
http://arxiv.org/abs/1905.09813v1
• [stat.ME]Atlantic Causal Inference Conference (ACIC) Data Analysis Challenge 2017
P. Richard Hahn, Vincent Dorie, Jared S. Murray
http://arxiv.org/abs/1905.09515v1
• [stat.ME]Learning When-to-Treat Policies
Xinkun Nie, Emma Brunskill, Stefan Wager
http://arxiv.org/abs/1905.09751v1
• [stat.ME]Random Norming Aids Analysis of Non-linear Regression Models with Sequential Informative Dose Selection
Zhantao Lin, Nancy Flournoy, William F. Rosenberger
http://arxiv.org/abs/1905.09722v1
• [stat.ME]Restricted Spatial Regression Methods: Implications for Inference
Kori Khan, Catherine A. Calder
http://arxiv.org/abs/1905.09371v1
• [stat.ME]Slamming the sham: A Bayesian model for adaptive adjustment with noisy control data
Andrew Gelman, Matthijs Vákár
http://arxiv.org/abs/1905.09693v1
• [stat.ML]An Optimal Private Stochastic-MAB Algorithm Based on an Optimal Private Stopping Rule
Touqir Sajed, Or Sheffet
http://arxiv.org/abs/1905.09383v1
• [stat.ML]Bayesian Optimization over Sets
Jungtaek Kim, Michael McCourt, Tackgeun You, Saehoon Kim, Seungjin Choi
http://arxiv.org/abs/1905.09780v1
• [stat.ML]Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation
Théo Galy-Fajou, Florian Wenzel, Christian Donner, Manfred Opper
http://arxiv.org/abs/1905.09670v1
• [stat.ML]Population-based Global Optimisation Methods for Learning Long-term Dependencies with RNNs
Bryan Lim, Stefan Zohren, Stephen Roberts
http://arxiv.org/abs/1905.09691v1
• [stat.ML]Replicated Vector Approximate Message Passing For Resampling Problem
Takashi Takahashi, Yoshiyuki Kabashima
http://arxiv.org/abs/1905.09545v1
• [stat.ML]Revisiting Graph Neural Networks: All We Have is Low-Pass Filters
Hoang NT, Takanori Maehara
http://arxiv.org/abs/1905.09550v1