cond-mat.mtrl-sci - 材料科学
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.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.MM - 多媒体 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SD - 声音处理 cs.SI - 社交网络与信息网络 cs.SY - 系统与控制 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.OC - 优化与控制 math.ST - 统计理论 physics.soc-ph - 物理学与社会 q-bio.NC - 神经元与认知 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
• [cond-mat.mtrl-sci]Materials property prediction using symmetry-labeled graphs as atomic-position independent descriptors
• [cs.AI]Generative Design in Minecraft: Chronicle Challenge
• [cs.AI]Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning
• [cs.CL]A Dynamic Evolutionary Framework for Timeline Generation based on Distributed Representations
• [cs.CL]A Surprisingly Robust Trick for Winograd Schema Challenge
• [cs.CL]Aligning Visual Regions and Textual Concepts: Learning Fine-Grained Image Representations for Image Captioning
• [cs.CL]Atom Responding Machine for Dialog Generation
• [cs.CL]BERT Rediscovers the Classical NLP Pipeline
• [cs.CL]Curriculum Learning for Domain Adaptation in Neural Machine Translation
• [cs.CL]Dual Supervised Learning for Natural Language Understanding and Generation
• [cs.CL]Exact Hard Monotonic Attention for Character-Level Transduction
• [cs.CL]Extraction and Analysis of Clinically Important Follow-up Recommendations in a Large Radiology Dataset
• [cs.CL]Multi-task Learning for Multi-modal Emotion Recognition and Sentiment Analysis
• [cs.CL]Ontology-Aware Clinical Abstractive Summarization
• [cs.CL]Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing
• [cs.CL]Selection Bias Explorations and Debias Methods for Natural Language Sentence Matching Datasets
• [cs.CL]What do you learn from context? Probing for sentence structure in contextualized word representations
• [cs.CL]When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion
• [cs.CR]Autonomous Penetration Testing using Reinforcement Learning
• [cs.CR]Modern Problems Require Modern Solutions: Hybrid Concepts for Industrial Intrusion Detection
• [cs.CR]TAPESTRY: A Blockchain based Service for Trusted Interaction Online
• [cs.CV]3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions
• [cs.CV]3D Semantic Scene Completion from a Single Depth Image using Adversarial Training
• [cs.CV]Arbitrary Shape Scene Text Detection with Adaptive Text Region Representation
• [cs.CV]BiRA-Net: Bilinear Attention Net for Diabetic Retinopathy Grading
• [cs.CV]Budget-Aware Adapters for Multi-Domain Learning
• [cs.CV]Budget-aware Semi-Supervised Semantic and Instance Segmentation
• [cs.CV]Constrained low-tubal-rank tensor recovery for hyperspectral images mixed noise removal by bilateral random projections
• [cs.CV]Crowd Density Estimation using Novel Feature Descriptor
• [cs.CV]DARNet: Deep Active Ray Network for Building Segmentation
• [cs.CV]Deep Kinship Verification via Appearance-shape Joint Prediction and Adaptation-based Approach
• [cs.CV]Joint haze image synthesis and dehazing with mmd-vae losses
• [cs.CV]Reconstruction-Aware Imaging System Ranking by use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference
• [cs.CV]Significance of parallel computing on the performance of Digital Image Correlation algorithms in MATLAB
• [cs.CV]Supervised Learning of the Next-Best-View for 3D Object Reconstruction
• [cs.CV]Synthetic Defocus and Look-Ahead Autofocus for Casual Videography
• [cs.CV]Task-Driven Modular Networks for Zero-Shot Compositional Learning
• [cs.CV]User profiles matching for different social networks based on faces embeddings
• [cs.CV]VICSOM: VIsual Clues from SOcial Media for psychological assessment
• [cs.CY]A Preliminary Theory for Open Source Ecosystem Micro-economics
• [cs.CY]Demographic Inference and Representative Population Estimates from Multilingual Social Media Data
• [cs.DC]Analysis of Pipelined KATAN Ciphers under Handle-C for FPGAs
• [cs.DC]Byzantine Consensus in the Common Case
• [cs.DC]DeXTT: Deterministic Cross-Blockchain Token Transfers
• [cs.DC]DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression
• [cs.DC]Optimizing the Linear Fascicle Evaluation Algorithm for Multi-Core and Many-Core Systems
• [cs.DC]Scaling Distributed Training of Flood-Filling Networks on HPC Infrastructure for Brain Mapping
• [cs.DC]When Internet of Things Meets Blockchain: Challenges in Distributed Consensus
• [cs.HC]A Human-Centered Approach to Interactive Machine Learning
• [cs.IR]Detecting Vietnamese Opinion Spam
• [cs.IR]Passage Ranking with Weak Supervsion
• [cs.IT]An Energy-Efficient Controller for Wirelessly-Powered Communication Networks
• [cs.IT]Deep Reinforcement Learning for Scheduling in Cellular Networks
• [cs.IT]Massive MIMO for Internet of Things (IoT) Connectivity
• [cs.IT]MmWave UAV Networks with Multi-cell Association: Performance Limit and Optimization
• [cs.IT]Performance Analysis of Non-DC-Biased OFDM
• [cs.IT]Performance Analysis of SPAD-based OFDM
• [cs.IT]Time-Varying Downlink Channel Tracking for Quantized Massive MIMO Networks
• [cs.LG]A Learning based Branch and Bound for Maximum Common Subgraph Problems
• [cs.LG]A Neural Network-Evolutionary Computational Framework for Remaining Useful Life Estimation of Mechanical Systems
• [cs.LG]Accelerating Deterministic and Stochastic Binarized Neural Networks on FPGAs Using OpenCL
• [cs.LG]Accuracy Improvement of Neural Network Training using Particle Swarm Optimization and its Stability Analysis for Classification
• [cs.LG]ActiveHNE: Active Heterogeneous Network Embedding
• [cs.LG]Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization
• [cs.LG]Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment
• [cs.LG]Automatic Model Selection for Neural Networks
• [cs.LG]Can Graph Neural Networks Go “Online”? An Analysis of Pretraining and Inference
• [cs.LG]Cluster, Classify, Regress: A General Method For Learning Discountinous Functions
• [cs.LG]Combining Parametric and Nonparametric Models for Off-Policy Evaluation
• [cs.LG]Correlated Variational Auto-Encoders
• [cs.LG]Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models
• [cs.LG]Deep Neural Architecture Search with Deep Graph Bayesian Optimization
• [cs.LG]Detection of Review Abuse via Semi-Supervised Binary Multi-Target Tensor Decomposition
• [cs.LG]Differentiable Linearized ADMM
• [cs.LG]Distributional Reinforcement Learning for Efficient Exploration
• [cs.LG]EasiCS: the objective and fine-grained classification method of cervical spondylosis dysfunction
• [cs.LG]EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis
• [cs.LG]Embeddings and Representation Learning for Structured Data
• [cs.LG]Function Space Pooling For Graph Convolutional Networks
• [cs.LG]GMNN: Graph Markov Neural Networks
• [cs.LG]Game Theoretic Optimization via Gradient-based Nikaido-Isoda Function
• [cs.LG]Ignorance-Aware Approaches and Algorithms for Prototype Selection in Machine Learning
• [cs.LG]Interpretable Deep Neural Networks for Patient Mortality Prediction: A Consensus-based Approach
• [cs.LG]Kernel Mean Matching for Content Addressability of GANs
• [cs.LG]Learning Generative Models across Incomparable Spaces
• [cs.LG]Learning Policies from Self-Play with Policy Gradients and MCTS Value Estimates
• [cs.LG]Learning What and Where to Transfer
• [cs.LG]Misleading Failures of Partial-input Baselines
• [cs.LG]Multi-View Multi-Instance Multi-Label Learning based on Collaborative Matrix Factorization
• [cs.LG]Multiple perspectives HMM-based feature engineering for credit card fraud detection
• [cs.LG]Neural Query Language: A Knowledge Base Query Language for Tensorflow
• [cs.LG]Nonlinear Semi-Parametric Models for Survival Analysis
• [cs.LG]Online Anomaly Detection with Sparse Gaussian Processes
• [cs.LG]Online Normalization for Training Neural Networks
• [cs.LG]Orthogonal Deep Neural Networks
• [cs.LG]Output-Constrained Bayesian Neural Networks
• [cs.LG]Reinforcement Learning for Robotics and Control with Active Uncertainty Reduction
• [cs.LG]Resource-aware Elastic Swap Random Forest for Evolving Data Streams
• [cs.LG]Rethinking the Usage of Batch Normalization and Dropout in the Training of Deep Neural Networks
• [cs.LG]Robust Neural Network Training using Periodic Sampling over Model Weights
• [cs.LG]SMART: Semantic Malware Attribute Relevance Tagging
• [cs.LG]Simitate: A Hybrid Imitation Learning Benchmark
• [cs.LG]Spectral Clustering of Signed Graphs via Matrix Power Means
• [cs.LG]Stochastic approximation with cone-contractive operators: Sharp $\ell_\infty$-bounds for $Q$-learning
• [cs.LG]Survival of the Fittest in PlayerUnknown BattleGround
• [cs.LG]TSXplain: Demystification of DNN Decisions for Time-Series using Natural Language and Statistical Features
• [cs.LG]Task-Driven Data Verification via Gradient Descent
• [cs.LG]Variational Regret Bounds for Reinforcement Learning
• [cs.LO]Generic Encodings of Constructor Rewriting Systems
• [cs.MM]SmartBullets: A Cloud-Assisted Bullet Screen Filter based on Deep Learning
• [cs.NE]Diagonal Acceleration for Covariance Matrix Adaptation Evolution Strategies
• [cs.NE]Origami Inspired Solar Panel Design
• [cs.NE]Regularized Evolutionary Algorithm for Dynamic Neural Topology Search
• [cs.NI]Connectivity-Aware UAV Path Planning with Aerial Coverage Maps
• [cs.NI]Using Bursty Announcements for Early Detection of BGP Routing Anomalies
• [cs.RO]Depth map estimation methodology for detecting free-obstacle navigation areas
• [cs.RO]Explorations and Lessons Learned in Building an Autonomous Formula SAE Car from Simulations
• [cs.RO]Feedback MPC for Torque-Controlled Legged Robots
• [cs.RO]Human Motion Trajectory Prediction: A Survey
• [cs.RO]Learning Active Spine Behaviors for Dynamic and Efficient Locomotion in Quadruped Robots
• [cs.SD]End-to-End Multi-Channel Speech Separation
• [cs.SD]Learning to Groove with Inverse Sequence Transformations
• [cs.SI]GhostLink: Latent Network Inference for Influence-aware Recommendation
• [cs.SI]Planted Hitting Set Recovery in Hypergraphs
• [cs.SI]The Mobility Network of Scientists: Analyzing Temporal Correlations in Scientific Careers
• [cs.SY]Deep reinforcement learning for scheduling in large-scale networked control systems
• [eess.AS]A general-purpose deep learning approach to model time-varying audio effects
• [eess.AS]Zero-Shot Voice Style Transfer with Only Autoencoder Loss
• [eess.IV]From Brain Imaging to Graph Analysis: a study on ADNI’s patient cohort
• [eess.IV]Learning-based Single-step Quantitative Susceptibility Mapping Reconstruction Without Brain Extraction
• [eess.IV]Multi-scale Dynamic Graph Convolutional Network for Hyperspectral Image Classification
• [eess.IV]Unsupervised Deep Power Saving and Contrast Enhancement for OLED Displays
• [eess.SP]Robust Precoding Design for Coarsely Quantized MU-MIMO Under Channel Uncertainties
• [math.OC]Hybrid Stochastic Gradient Descent Algorithms for Stochastic Nonconvex Optimization
• [math.OC]Predictive Online Convex Optimization
• [math.ST]A New Confidence Interval for the Mean of a Bounded Random Variable
• [math.ST]Information criteria for non-normalized models
• [math.ST]Measuring Bayesian Robustness Using Rényi’s Divergence and Relationship with Prior-Data Conflict
• [math.ST]Minimax rates of estimation for smooth optimal transport maps
• [math.ST]Revisiting High Dimensional Bayesian Model Selection for Gaussian Regression
• [math.ST]Robust change point tests by bounded transformations
• [math.ST]Which principal components are most sensitive to distributional changes?
• [physics.soc-ph]Computational Socioeconomics
• [q-bio.NC]Discriminative Sleep Patterns of Alzheimer’s Disease via Tensor Factorization
• [stat.AP]Automated detection of business-relevant outliers in e-commerce conversion rate
• [stat.AP]Combining Representation Learning with Tensor Factorization for Risk Factor Analysis - an application to Epilepsy and Alzheimer’s disease
• [stat.AP]Fast Parameter Inference in a Biomechanical Model of the Left Ventricle using Statistical Emulation
• [stat.AP]Multivariate Modeling for Sustainable and Resilient Infrastructure Systems and Communities
• [stat.AP]Shifting attention to old age: Detecting mortality deceleration using focused model selection
• [stat.AP]Signal detection in extracellular neural ensemble recordings using higher criticism
• [stat.CO]A New Estimation Algorithm for Box-Cox Transformation Cure Rate Model and Comparison With EM Algorithm
• [stat.ME]Approximate Bayesian computation via the energy statistic
• [stat.ME]False Discovery Rates to Detect Signals from Incomplete Spatially Aggregated Data
• [stat.ME]Fast and robust model selection based on ranks
• [stat.ME]Simultaneous Inference Under the Vacuous Orientation Assumption
• [stat.ME]Simultaneous Inference for Pairwise Graphical Models with Generalized Score Matching
• [stat.ML]Distribution Calibration for Regression
• [stat.ML]Domain Adaptive Transfer Learning for Fault Diagnosis
• [stat.ML]Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions
• [stat.ML]Geometric Losses for Distributional Learning
• [stat.ML]Iterative Alpha Expansion for estimating gradient-sparse signals from linear measurements
• [stat.ML]Transferable Clean-Label Poisoning Attacks on Deep Neural Nets
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• [cond-mat.mtrl-sci]Materials property prediction using symmetry-labeled graphs as atomic-position independent descriptors
Peter Bjørn Jørgensen, Estefanía Garijo del Río, Mikkel N. Scmhidt, Karsten Wedel Jacobsen
http://arxiv.org/abs/1905.06048v1
• [cs.AI]Generative Design in Minecraft: Chronicle Challenge
Christoph Salge, Christian Guckelsberger, Michael Cerny Green, Rodrigo Canaan, Julian Togelius
http://arxiv.org/abs/1905.05888v1
• [cs.AI]Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning
Artur d’Avila Garcez, Marco Gori, Luis C. Lamb, Luciano Serafini, Michael Spranger, Son N. Tran
http://arxiv.org/abs/1905.06088v1
• [cs.CL]A Dynamic Evolutionary Framework for Timeline Generation based on Distributed Representations
Dongyun Liang, Guohua Wang, Jing Nie
http://arxiv.org/abs/1905.05550v2
• [cs.CL]A Surprisingly Robust Trick for Winograd Schema Challenge
Vid Kocijan, Ana-Maria Cretu, Oana-Maria Camburu, Yordan Yordanov, Thomas Lukasiewicz
http://arxiv.org/abs/1905.06290v1
• [cs.CL]Aligning Visual Regions and Textual Concepts: Learning Fine-Grained Image Representations for Image Captioning
Fenglin Liu, Yuanxin Liu, Xuancheng Ren, Kai Lei, Xu Sun
http://arxiv.org/abs/1905.06139v1
• [cs.CL]Atom Responding Machine for Dialog Generation
Ganbin Zhou, Ping Luo, Jingwu Chen, Fen Lin, Leyu Lin, Qing He
http://arxiv.org/abs/1905.05532v2
• [cs.CL]BERT Rediscovers the Classical NLP Pipeline
Ian Tenney, Dipanjan Das, Ellie Pavlick
http://arxiv.org/abs/1905.05950v1
• [cs.CL]Curriculum Learning for Domain Adaptation in Neural Machine Translation
Xuan Zhang, Pamela Shapiro, Gaurav Kumar, Paul McNamee, Marine Carpuat, Kevin Duh
http://arxiv.org/abs/1905.05816v1
• [cs.CL]Dual Supervised Learning for Natural Language Understanding and Generation
Shang-Yu Su, Chao-Wei Huang, Yun-Nung Chen
http://arxiv.org/abs/1905.06196v1
• [cs.CL]Exact Hard Monotonic Attention for Character-Level Transduction
Shijie Wu, Ryan Cotterell
http://arxiv.org/abs/1905.06319v1
• [cs.CL]Extraction and Analysis of Clinically Important Follow-up Recommendations in a Large Radiology Dataset
Wilson Lau, Thomas H Payne, Ozlem Uzuner, Meliha Yetisgen
http://arxiv.org/abs/1905.05877v1
• [cs.CL]Multi-task Learning for Multi-modal Emotion Recognition and Sentiment Analysis
Md Shad Akhtar, Dushyant Singh Chauhan, Deepanway Ghosal, Soujanya Poria, Asif Ekbal, Pushpak Bhattacharyya
http://arxiv.org/abs/1905.05812v1
• [cs.CL]Ontology-Aware Clinical Abstractive Summarization
Sean MacAvaney, Sajad Sotudeh, Arman Cohan, Nazli Goharian, Ish Talati, Ross W. Filice
http://arxiv.org/abs/1905.05818v1
• [cs.CL]Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing
Ben Bogin, Matt Gardner, Jonathan Berant
http://arxiv.org/abs/1905.06241v1
• [cs.CL]Selection Bias Explorations and Debias Methods for Natural Language Sentence Matching Datasets
Guanhua Zhang, Bing Bai, Jian Liang, Kun Bai, Shiyu Chang, Mo Yu, Conghui Zhu, Tiejun Zhao
http://arxiv.org/abs/1905.06221v1
• [cs.CL]What do you learn from context? Probing for sentence structure in contextualized word representations
Ian Tenney, Patrick Xia, Berlin Chen, Alex Wang, Adam Poliak, R Thomas McCoy, Najoung Kim, Benjamin Van Durme, Samuel R. Bowman, Dipanjan Das, Ellie Pavlick
http://arxiv.org/abs/1905.06316v1
• [cs.CL]When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion
Elena Voita, Rico Sennrich, Ivan Titov
http://arxiv.org/abs/1905.05979v1
• [cs.CR]Autonomous Penetration Testing using Reinforcement Learning
Jonathon Schwartz, Hanna Kurniawati
http://arxiv.org/abs/1905.05965v1
• [cs.CR]Modern Problems Require Modern Solutions: Hybrid Concepts for Industrial Intrusion Detection
Simon D. Duque Anton, Mathias Strufe, Hans Dieter Schotten
http://arxiv.org/abs/1905.05984v1
• [cs.CR]TAPESTRY: A Blockchain based Service for Trusted Interaction Online
Yifan Yang, Daniel Cooper, John Collomosse, Constantin C. Drăgan, Mark Manulis, Jamie Steane, Arthi Manohar, Jo Briggs, Helen Jones, Wendy Moncur
http://arxiv.org/abs/1905.06186v1
• [cs.CV]3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions
Dong Wook Shu, Sung Woo Park, Junseok Kwon
http://arxiv.org/abs/1905.06292v1
• [cs.CV]3D Semantic Scene Completion from a Single Depth Image using Adversarial Training
Yueh-Tung Chen, Martin Garbade, Juergen Gall
http://arxiv.org/abs/1905.06231v1
• [cs.CV]Arbitrary Shape Scene Text Detection with Adaptive Text Region Representation
Xiaobing Wang, Yingying Jiang, Zhenbo Luo, Cheng-Lin Liu, Hyunsoo Choi, Sungjin Kim
http://arxiv.org/abs/1905.05980v1
• [cs.CV]BiRA-Net: Bilinear Attention Net for Diabetic Retinopathy Grading
Ziyuan Zhao, Kerui Zhang, Xuejie Hao, Jing Tian, Matthew Chin Heng Chua, Li Chen, Xin Xu
http://arxiv.org/abs/1905.06312v1
• [cs.CV]Budget-Aware Adapters for Multi-Domain Learning
Rodrigo Berriel, Stéphane Lathuilière, Moin Nabi, Tassilo Klein, Thiago Oliveira-Santos, Nicu Sebe, Elisa Ricci
http://arxiv.org/abs/1905.06242v1
• [cs.CV]Budget-aware Semi-Supervised Semantic and Instance Segmentation
Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier-Giro-i-Nieto
http://arxiv.org/abs/1905.05880v1
• [cs.CV]Constrained low-tubal-rank tensor recovery for hyperspectral images mixed noise removal by bilateral random projections
Hao Zhang, Xi-Le Zhao, Tai-Xiang Jiang, Michael Kwok-Po Ng
http://arxiv.org/abs/1905.05941v1
• [cs.CV]Crowd Density Estimation using Novel Feature Descriptor
Adwan Alownie Alanazi, Muhammad Bilal
http://arxiv.org/abs/1905.05891v1
• [cs.CV]DARNet: Deep Active Ray Network for Building Segmentation
Dominic Cheng, Renjie Liao, Sanja Fidler, Raquel Urtasun
http://arxiv.org/abs/1905.05889v1
• [cs.CV]Deep Kinship Verification via Appearance-shape Joint Prediction and Adaptation-based Approach
Heming Zhang, Xiaolong Wang, C. -C. Jay Kuo
http://arxiv.org/abs/1905.05964v1
• [cs.CV]Joint haze image synthesis and dehazing with mmd-vae losses
Zongliang Li, Chi Zhang, Gaofeng Meng, Yuehu Liu
http://arxiv.org/abs/1905.05947v1
• [cs.CV]Reconstruction-Aware Imaging System Ranking by use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference
Yujia Chen, Yang Lou, Kun Wang, Matthew A. Kupinski, Mark A. Anastasio
http://arxiv.org/abs/1905.05820v1
• [cs.CV]Significance of parallel computing on the performance of Digital Image Correlation algorithms in MATLAB
Andreas Thoma, Sridhar Ravi
http://arxiv.org/abs/1905.06228v1
• [cs.CV]Supervised Learning of the Next-Best-View for 3D Object Reconstruction
Miguel Mendoza, J. Irving Vasquez-Gomez, Hind Taud, Luis Enrique Sucar, Carolina Reta
http://arxiv.org/abs/1905.05833v1
• [cs.CV]Synthetic Defocus and Look-Ahead Autofocus for Casual Videography
Xuaner, Zhang, Kevin Matzen, Vivien Nguyen, Dillon Yao, You Zhang, Ren Ng
http://arxiv.org/abs/1905.06326v1
• [cs.CV]Task-Driven Modular Networks for Zero-Shot Compositional Learning
Senthil Purushwalkam, Maximilian Nickel, Abhinav Gupta, Marc’Aurelio Ranzato
http://arxiv.org/abs/1905.05908v1
• [cs.CV]User profiles matching for different social networks based on faces embeddings
Timur Sokhin, Nikolay Butakov, Denis Nasonov
http://arxiv.org/abs/1905.06081v1
• [cs.CV]VICSOM: VIsual Clues from SOcial Media for psychological assessment
Mohammad Mahdi Dehshibi, Gerard Pons, Bita Baiani, David Masip
http://arxiv.org/abs/1905.06203v1
• [cs.CY]A Preliminary Theory for Open Source Ecosystem Micro-economics
Nicolas Jullien, Klaas-Jan Stol, James Herbsleb
http://arxiv.org/abs/1905.05985v1
• [cs.CY]Demographic Inference and Representative Population Estimates from Multilingual Social Media Data
Zijian Wang, Scott A. Hale, David Adelani, Przemyslaw A. Grabowicz, Timo Hartmann, Fabian Flöck, David Jurgens
http://arxiv.org/abs/1905.05961v1
• [cs.DC]Analysis of Pipelined KATAN Ciphers under Handle-C for FPGAs
Palwasha Shaikh, Issam Damaj
http://arxiv.org/abs/1905.06235v1
• [cs.DC]Byzantine Consensus in the Common Case
Guy Goren, Yoram Moses
http://arxiv.org/abs/1905.06087v1
• [cs.DC]DeXTT: Deterministic Cross-Blockchain Token Transfers
Michael Borkowski, Marten Sigwart, Philipp Frauenthaler, Taneli Hukkinen, Stefan Schulte
http://arxiv.org/abs/1905.06204v1
• [cs.DC]DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression
Hanlin Tang, Xiangru Lian, Tong Zhang, Ji Liu
http://arxiv.org/abs/1905.05957v1
• [cs.DC]Optimizing the Linear Fascicle Evaluation Algorithm for Multi-Core and Many-Core Systems
Karan Aggarwal, Uday Bondhugula, Varsha Sreenivasan, Devarajan Sridharan
http://arxiv.org/abs/1905.06234v1
• [cs.DC]Scaling Distributed Training of Flood-Filling Networks on HPC Infrastructure for Brain Mapping
Wushi Dong, Murat Keceli, Rafael Vescovi, Hanyu Li, Corey Adams, Tom Uram, Venkatram Vishwanath, Bobby Kasthuri, Nicola Ferrier, Peter Littlewood
http://arxiv.org/abs/1905.06236v1
• [cs.DC]When Internet of Things Meets Blockchain: Challenges in Distributed Consensus
Bin Cao, Yixin Li, Lei Zhang, Long Zhang, Shahid Mumtaz, Zhenyu Zhou, Mugen Peng
http://arxiv.org/abs/1905.06022v1
• [cs.HC]A Human-Centered Approach to Interactive Machine Learning
Kory W. Mathewson
http://arxiv.org/abs/1905.06289v1
• [cs.IR]Detecting Vietnamese Opinion Spam
T. H. H Duong, T. D. Vu, V. M. Ngo
http://arxiv.org/abs/1905.06112v1
• [cs.IR]Passage Ranking with Weak Supervsion
Peng Xu, Xiaofei Ma, Ramesh Nallapati, Bing Xiang
http://arxiv.org/abs/1905.05910v1
• [cs.IT]An Energy-Efficient Controller for Wirelessly-Powered Communication Networks
Mohammad Movahednasab, Behrooz Makki, Naeimeh Omidvar, Mohammad Reza Pakravan, Tommy Svensson, Michele Zorzi
http://arxiv.org/abs/1905.05958v1
• [cs.IT]Deep Reinforcement Learning for Scheduling in Cellular Networks
Jian Wang, Chen Xu, Yourui Huangfu, Rong Li, Yiqun Ge, Jun Wang
http://arxiv.org/abs/1905.05914v1
• [cs.IT]Massive MIMO for Internet of Things (IoT) Connectivity
Alexandru-Sabin Bana, Elisabeth de Carvalho, Beatriz Soret, Taufik Abrão, José Carlos Marinello, Erik G. Larsson, Petar Popovski
http://arxiv.org/abs/1905.06205v1
• [cs.IT]MmWave UAV Networks with Multi-cell Association: Performance Limit and Optimization
Chun-Hung Liu, Kai-Hsiang Ho, Jwo-Yuh Wu
http://arxiv.org/abs/1905.06099v1
• [cs.IT]Performance Analysis of Non-DC-Biased OFDM
Yichen Li, Dobroslav Tsonev, Harald Haas
http://arxiv.org/abs/1905.05822v1
• [cs.IT]Performance Analysis of SPAD-based OFDM
Yichen Li, Majid Safari, Robert Henderson, Harald Haas
http://arxiv.org/abs/1905.06302v1
• [cs.IT]Time-Varying Downlink Channel Tracking for Quantized Massive MIMO Networks
Jianpeng Ma, Shun Zhang, Hongyan Li, Feifei Gao, Zhu Han
http://arxiv.org/abs/1905.05906v1
• [cs.LG]A Learning based Branch and Bound for Maximum Common Subgraph Problems
Yan-li Liu, Chu-min Li, Hua Jiang, Kun He
http://arxiv.org/abs/1905.05840v1
• [cs.LG]A Neural Network-Evolutionary Computational Framework for Remaining Useful Life Estimation of Mechanical Systems
David Laredo, Zhaoyin Chen, Oliver Schütze, Jian-Qiao Sun
http://arxiv.org/abs/1905.05918v1
• [cs.LG]Accelerating Deterministic and Stochastic Binarized Neural Networks on FPGAs Using OpenCL
Corey Lammie, Wei Xiang, Mostafa Rahimi Azghadi
http://arxiv.org/abs/1905.06105v1
• [cs.LG]Accuracy Improvement of Neural Network Training using Particle Swarm Optimization and its Stability Analysis for Classification
Arijit Nandi, Nanda Dulal Jana
http://arxiv.org/abs/1905.04522v2
• [cs.LG]ActiveHNE: Active Heterogeneous Network Embedding
Xia Chen, Guoxian Yu, Jun Wang, Carlotta Domeniconi, Zhao Li, Xiangliang Zhang
http://arxiv.org/abs/1905.05659v2
• [cs.LG]Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization
Guanghui Wang, Shiyin Lu, Lijun Zhang
http://arxiv.org/abs/1905.05917v1
• [cs.LG]Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment
Chen Huang, Shuangfei Zhai, Walter Talbott, Miguel Angel Bautista, Shih-Yu Sun, Carlos Guestrin, Josh Susskind
http://arxiv.org/abs/1905.05895v1
• [cs.LG]Automatic Model Selection for Neural Networks
David Laredo, Yulin Qin, Oliver Schütze, Jian-Qiao Sun
http://arxiv.org/abs/1905.06010v1
• [cs.LG]Can Graph Neural Networks Go “Online”? An Analysis of Pretraining and Inference
Lukas Galke, Iacopo Vagliano, Ansgar Scherp
http://arxiv.org/abs/1905.06018v1
• [cs.LG]Cluster, Classify, Regress: A General Method For Learning Discountinous Functions
David E. Bernholdt, Mark R. Ciancosa, Clement Etienam, David L. Green, Kody J. H. Law, J. M. Park
http://arxiv.org/abs/1905.06220v1
• [cs.LG]Combining Parametric and Nonparametric Models for Off-Policy Evaluation
Omer Gottesman, Yao Liu, Scott Sussex, Emma Brunskill, Finale Doshi-Velez
http://arxiv.org/abs/1905.05787v1
• [cs.LG]Correlated Variational Auto-Encoders
Da Tang, Dawen Liang, Tony Jebara, Nicholas Ruozzi
http://arxiv.org/abs/1905.05335v2
• [cs.LG]Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models
Michael Oberst, David Sontag
http://arxiv.org/abs/1905.05824v1
• [cs.LG]Deep Neural Architecture Search with Deep Graph Bayesian Optimization
Lizheng Ma, Jiaxu Cui, Bo Yang
http://arxiv.org/abs/1905.06159v1
• [cs.LG]Detection of Review Abuse via Semi-Supervised Binary Multi-Target Tensor Decomposition
Anil R. Yelundur, Vineet Chaoji, Bamdev Mishra
http://arxiv.org/abs/1905.06246v1
• [cs.LG]Differentiable Linearized ADMM
Xingyu Xie, Jianlong Wu, Zhisheng Zhong, Guangcan Liu, Zhouchen Lin
http://arxiv.org/abs/1905.06179v1
• [cs.LG]Distributional Reinforcement Learning for Efficient Exploration
Borislav Mavrin, Shangtong Zhang, Hengshuai Yao, Linglong Kong, Kaiwen Wu, Yaoliang Yu
http://arxiv.org/abs/1905.06125v1
• [cs.LG]EasiCS: the objective and fine-grained classification method of cervical spondylosis dysfunction
Nana Wang, Li Cui, Xi Huang, Yingcong Xiang, Jing Xiao, Yi Rao
http://arxiv.org/abs/1905.05987v1
• [cs.LG]EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis
Chaoqi Wang, Roger Grosse, Sanja Fidler, Guodong Zhang
http://arxiv.org/abs/1905.05934v1
• [cs.LG]Embeddings and Representation Learning for Structured Data
Benjamin Paaßen, Claudio Gallicchio, Alessio Micheli, Alessandro Sperduti
http://arxiv.org/abs/1905.06147v1
• [cs.LG]Function Space Pooling For Graph Convolutional Networks
Padraig Corcoran
http://arxiv.org/abs/1905.06259v1
• [cs.LG]GMNN: Graph Markov Neural Networks
Meng Qu, Yoshua Bengio, Jian Tang
http://arxiv.org/abs/1905.06214v1
• [cs.LG]Game Theoretic Optimization via Gradient-based Nikaido-Isoda Function
Arvind U. Raghunathan, Anoop Cherian, Devesh K. Jha
http://arxiv.org/abs/1905.05927v1
• [cs.LG]Ignorance-Aware Approaches and Algorithms for Prototype Selection in Machine Learning
Vagan Terziyan, Anton Nikulin
http://arxiv.org/abs/1905.06054v1
• [cs.LG]Interpretable Deep Neural Networks for Patient Mortality Prediction: A Consensus-based Approach
Shaeke Salman, Seyedeh Neelufar Payrovnaziri, Xiuwen Liu, Zhe He
http://arxiv.org/abs/1905.05849v1
• [cs.LG]Kernel Mean Matching for Content Addressability of GANs
Wittawat Jitkrittum, Patsorn Sangkloy, Muhammad Waleed Gondal, Amit Raj, James Hays, Bernhard Schölkopf
http://arxiv.org/abs/1905.05882v1
• [cs.LG]Learning Generative Models across Incomparable Spaces
Charlotte Bunne, David Alvarez-Melis, Andreas Krause, Stefanie Jegelka
http://arxiv.org/abs/1905.05461v2
• [cs.LG]Learning Policies from Self-Play with Policy Gradients and MCTS Value Estimates
Dennis J. N. J. Soemers, Éric Piette, Matthew Stephenson, Cameron Browne
http://arxiv.org/abs/1905.05809v1
• [cs.LG]Learning What and Where to Transfer
Yunhun Jang, Hankook Lee, Sung Ju Hwang, Jinwoo Shin
http://arxiv.org/abs/1905.05901v1
• [cs.LG]Misleading Failures of Partial-input Baselines
Shi Feng, Eric Wallace, Jordan Boyd-Graber
http://arxiv.org/abs/1905.05778v1
• [cs.LG]Multi-View Multi-Instance Multi-Label Learning based on Collaborative Matrix Factorization
Yuying Xing, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Zili Zhang, Maozu Guo
http://arxiv.org/abs/1905.05061v2
• [cs.LG]Multiple perspectives HMM-based feature engineering for credit card fraud detection
Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Olivier Caelen, Liyun He-Guelton, Sylvie Calabretto, Michael Granitzer
http://arxiv.org/abs/1905.06247v1
• [cs.LG]Neural Query Language: A Knowledge Base Query Language for Tensorflow
William W. Cohen, Matthew Siegler, Alex Hofer
http://arxiv.org/abs/1905.06209v1
• [cs.LG]Nonlinear Semi-Parametric Models for Survival Analysis
Chirag Nagpal, Rohan Sangave, Amit Chahar, Parth Shah, Artur Dubrawski, Bhiksha Raj
http://arxiv.org/abs/1905.05865v1
• [cs.LG]Online Anomaly Detection with Sparse Gaussian Processes
Jingjing Fei, Shiliang Sun
http://arxiv.org/abs/1905.05761v1
• [cs.LG]Online Normalization for Training Neural Networks
Vitaliy Chiley, Ilya Sharapov, Atli Kosson, Urs Koster, Ryan Reece, Sofia Samaniego de la Fuente, Vishal Subbiah, Michael James
http://arxiv.org/abs/1905.05894v1
• [cs.LG]Orthogonal Deep Neural Networks
Kui Jia, Shuai Li, Yuxin Wen, Tongliang Liu, Dacheng Tao
http://arxiv.org/abs/1905.05929v1
• [cs.LG]Output-Constrained Bayesian Neural Networks
Wanqian Yang, Lars Lorch, Moritz A. Graule, Srivatsan Srinivasan, Anirudh Suresh, Jiayu Yao, Melanie F. Pradier, Finale Doshi-Velez
http://arxiv.org/abs/1905.06287v1
• [cs.LG]Reinforcement Learning for Robotics and Control with Active Uncertainty Reduction
Narendra Patwardhan, Zequn Wang
http://arxiv.org/abs/1905.06274v1
• [cs.LG]Resource-aware Elastic Swap Random Forest for Evolving Data Streams
Diego Marrón, Eduard Ayguadé, José Ramon Herrero, Albert Bifet
http://arxiv.org/abs/1905.05881v1
• [cs.LG]Rethinking the Usage of Batch Normalization and Dropout in the Training of Deep Neural Networks
Guangyong Chen, Pengfei Chen, Yujun Shi, Chang-Yu Hsieh, Benben Liao, Shengyu Zhang
http://arxiv.org/abs/1905.05928v1
• [cs.LG]Robust Neural Network Training using Periodic Sampling over Model Weights
Samarth Tripathi, Jiayi Liu, Unmesh Kurup, Mohak Shah
http://arxiv.org/abs/1905.05774v1
• [cs.LG]SMART: Semantic Malware Attribute Relevance Tagging
Felipe N. Ducau, Ethan M. Rudd, Tad M. Heppner, Alex Long, Konstantin Berlin
http://arxiv.org/abs/1905.06262v1
• [cs.LG]Simitate: A Hybrid Imitation Learning Benchmark
Raphael Memmesheimer, Ivanna Mykhalchyshyna, Viktor Seib, Dietrich Paulus
http://arxiv.org/abs/1905.06002v1
• [cs.LG]Spectral Clustering of Signed Graphs via Matrix Power Means
Pedro Mercado, Francesco Tudisco, Matthias Hein
http://arxiv.org/abs/1905.06230v1
• [cs.LG]Stochastic approximation with cone-contractive operators: Sharp $\ell_\infty$-bounds for $Q$-learning
Martin J. Wainwright
http://arxiv.org/abs/1905.06265v1
• [cs.LG]Survival of the Fittest in PlayerUnknown BattleGround
Brij Rokad, Tushar Karumudi, Omkar Acharya, Akshay Jagtap
http://arxiv.org/abs/1905.06052v1
• [cs.LG]TSXplain: Demystification of DNN Decisions for Time-Series using Natural Language and Statistical Features
Mohsin Munir, Shoaib Ahmed Siddiqui, Ferdinand Küsters, Dominique Mercier, Andreas Dengel, Sheraz Ahmed
http://arxiv.org/abs/1905.06175v1
• [cs.LG]Task-Driven Data Verification via Gradient Descent
Siavash Golkar, Kyunghyun Cho
http://arxiv.org/abs/1905.05843v1
• [cs.LG]Variational Regret Bounds for Reinforcement Learning
Pratik Gajane, Ronald Ortner, Peter Auer
http://arxiv.org/abs/1905.05857v1
• [cs.LO]Generic Encodings of Constructor Rewriting Systems
Horatiu Cirstea, Pierre-Etienne Moreau
http://arxiv.org/abs/1905.06233v1
• [cs.MM]SmartBullets: A Cloud-Assisted Bullet Screen Filter based on Deep Learning
Haoran Niu, Jiangnan Li, Yu Zhao
http://arxiv.org/abs/1905.05925v1
• [cs.NE]Diagonal Acceleration for Covariance Matrix Adaptation Evolution Strategies
Youhei Akimoto, Nikolaus Hansen
http://arxiv.org/abs/1905.05885v1
• [cs.NE]Origami Inspired Solar Panel Design
Chris Whitmire, Brij Rokad, Caleb Crumley
http://arxiv.org/abs/1905.06012v1
• [cs.NE]Regularized Evolutionary Algorithm for Dynamic Neural Topology Search
Cristiano Saltori, Subhankar Roy, Nicu Sebe, Giovanni Iacca
http://arxiv.org/abs/1905.06252v1
• [cs.NI]Connectivity-Aware UAV Path Planning with Aerial Coverage Maps
Hongyu Yang, Jun Zhang, S. H. Song, Khaled B. Lataief
http://arxiv.org/abs/1905.05926v1
• [cs.NI]Using Bursty Announcements for Early Detection of BGP Routing Anomalies
Pablo Moriano, Raquel Hill, L. Jean Camp
http://arxiv.org/abs/1905.05835v1
• [cs.RO]Depth map estimation methodology for detecting free-obstacle navigation areas
Sergio Trejo, Karla Martinez, Gerardo Flores
http://arxiv.org/abs/1905.05946v1
• [cs.RO]Explorations and Lessons Learned in Building an Autonomous Formula SAE Car from Simulations
Dean Zadok, Tom Hirshberg, Amir Biran, Kira Radinsky, Ashish Kapoor
http://arxiv.org/abs/1905.05940v1
• [cs.RO]Feedback MPC for Torque-Controlled Legged Robots
Ruben Grandia, Farbod Farshidian, René Ranftl, Marco Hutter
http://arxiv.org/abs/1905.06144v1
• [cs.RO]Human Motion Trajectory Prediction: A Survey
Andrey Rudenko, Luigi Palmieri, Michael Herman, Kris M. Kitani, Dariu M. Gavrila, Kai O. Arras
http://arxiv.org/abs/1905.06113v1
• [cs.RO]Learning Active Spine Behaviors for Dynamic and Efficient Locomotion in Quadruped Robots
Shounak Bhattacharya, Abhik Singla, Abhimanyu, Dhaivat Dholakiya, Shalabh Bhatnagar, Bharadwaj Amrutur, Ashitava Ghosal, Shishir Kolathaya
http://arxiv.org/abs/1905.06077v1
• [cs.SD]End-to-End Multi-Channel Speech Separation
Rongzhi Gu, Jian Wu, Shi-Xiong Zhang, Lianwu Chen, Yong Xu, Meng Yu, Dan Su, Yuexian Zou, Dong Yu
http://arxiv.org/abs/1905.06286v1
• [cs.SD]Learning to Groove with Inverse Sequence Transformations
Jon Gillick, Adam Roberts, Jesse Engel, Douglas Eck, David Bamman
http://arxiv.org/abs/1905.06118v1
• [cs.SI]GhostLink: Latent Network Inference for Influence-aware Recommendation
Subhabrata Mukherjee, Stephan Guennemann
http://arxiv.org/abs/1905.05955v1
• [cs.SI]Planted Hitting Set Recovery in Hypergraphs
Ilya Amburg, Jon Kleinberg, Austin R. Benson
http://arxiv.org/abs/1905.05839v1
• [cs.SI]The Mobility Network of Scientists: Analyzing Temporal Correlations in Scientific Careers
Giacomo Vaccario, Luca Verginer, Frank Schweitzer
http://arxiv.org/abs/1905.06142v1
• [cs.SY]Deep reinforcement learning for scheduling in large-scale networked control systems
Adrian Redder, Arunselvan Ramaswamy, Daniel E. Quevedo
http://arxiv.org/abs/1905.05992v1
• [eess.AS]A general-purpose deep learning approach to model time-varying audio effects
Marco A. Martinez Ramirez, Emmanouil Benetos, Joshua D. Reiss
http://arxiv.org/abs/1905.06148v1
• [eess.AS]Zero-Shot Voice Style Transfer with Only Autoencoder Loss
Kaizhi Qian, Yang Zhang, Shiyu Chang, Xuesong Yang, Mark Hasegawa-Johnson
http://arxiv.org/abs/1905.05879v1
• [eess.IV]From Brain Imaging to Graph Analysis: a study on ADNI’s patient cohort
Rui Zhang, Luca Giancardo, Danilo A. Pena, Yejin Kim, Hanghang Tong, Xiaoqian Jiang
http://arxiv.org/abs/1905.05861v1
• [eess.IV]Learning-based Single-step Quantitative Susceptibility Mapping Reconstruction Without Brain Extraction
Hongjiang Wei, Steven Cao, Yuyao Zhang, Xiaojun Guan, Fuhua Yan, Kristen W. Yeom, Chunlei Liu
http://arxiv.org/abs/1905.05953v1
• [eess.IV]Multi-scale Dynamic Graph Convolutional Network for Hyperspectral Image Classification
Sheng Wan, Chen Gong, Ping Zhong, Bo Du, Lefei Zhang, Jian Yang
http://arxiv.org/abs/1905.06133v1
• [eess.IV]Unsupervised Deep Power Saving and Contrast Enhancement for OLED Displays
Yong-Goo Shin, Seung Park, Min-Jae Yoo, Sung-Jea Ko
http://arxiv.org/abs/1905.05916v1
• [eess.SP]Robust Precoding Design for Coarsely Quantized MU-MIMO Under Channel Uncertainties
Lei Chu, Fei Wen, Robert Caiming Qiu
http://arxiv.org/abs/1905.05797v1
• [math.OC]Hybrid Stochastic Gradient Descent Algorithms for Stochastic Nonconvex Optimization
Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen
http://arxiv.org/abs/1905.05920v1
• [math.OC]Predictive Online Convex Optimization
Antoine Lesage-Landry, Iman Shames, Joshua A. Taylor
http://arxiv.org/abs/1905.06263v1
• [math.ST]A New Confidence Interval for the Mean of a Bounded Random Variable
Erik Learned-Miller, Philip S. Thomas
http://arxiv.org/abs/1905.06208v1
• [math.ST]Information criteria for non-normalized models
Takeru Matsuda, Masatoshi Uehara, Aapo Hyvarinen
http://arxiv.org/abs/1905.05976v1
• [math.ST]Measuring Bayesian Robustness Using Rényi’s Divergence and Relationship with Prior-Data Conflict
Luai Al-Labadi, Ce Wang
http://arxiv.org/abs/1905.05945v1
• [math.ST]Minimax rates of estimation for smooth optimal transport maps
Jan-Christian Hütter, Philippe Rigollet
http://arxiv.org/abs/1905.05828v1
• [math.ST]Revisiting High Dimensional Bayesian Model Selection for Gaussian Regression
Zikun Yang, Andrew Womack
http://arxiv.org/abs/1905.06224v1
• [math.ST]Robust change point tests by bounded transformations
Alexander Dürre, Roland Fried
http://arxiv.org/abs/1905.06201v1
• [math.ST]Which principal components are most sensitive to distributional changes?
Martin Tveten
http://arxiv.org/abs/1905.06318v1
• [physics.soc-ph]Computational Socioeconomics
Jian Gao, Yi-Cheng Zhang, Tao Zhou
http://arxiv.org/abs/1905.06166v1
• [q-bio.NC]Discriminative Sleep Patterns of Alzheimer’s Disease via Tensor Factorization
Yejin Kim, Xiaoqian Jiang, Luyao Chen, Xiaojin Li, Licong Cui
http://arxiv.org/abs/1905.05827v1
• [stat.AP]Automated detection of business-relevant outliers in e-commerce conversion rate
Rohan Wickramasuriya, Dean Marchiori
http://arxiv.org/abs/1905.05938v1
• [stat.AP]Combining Representation Learning with Tensor Factorization for Risk Factor Analysis - an application to Epilepsy and Alzheimer’s disease
Xiaoqian Jiang, Samden Lhatoo, Guo-Qiang Zhang, Luyao Chen, Yejin Kim
http://arxiv.org/abs/1905.05830v1
• [stat.AP]Fast Parameter Inference in a Biomechanical Model of the Left Ventricle using Statistical Emulation
Vinny Davies, Umberto Noè, Alan Lazarus, Hao Gao, Benn Macdonald, Colin Berry, Xiaoyu Luo, Dirk Husmeier
http://arxiv.org/abs/1905.06310v1
• [stat.AP]Multivariate Modeling for Sustainable and Resilient Infrastructure Systems and Communities
Renee Obringer, Roshanak Nateghi
http://arxiv.org/abs/1905.05803v1
• [stat.AP]Shifting attention to old age: Detecting mortality deceleration using focused model selection
Marie Böhnstedt, Hein Putter, Nadine Ouellette, Gerda Claeskens, Jutta Gampe
http://arxiv.org/abs/1905.05760v1
• [stat.AP]Signal detection in extracellular neural ensemble recordings using higher criticism
Farzad Fathizadeh, Ekaterina Mitricheva, Rui Kimura, Nikos Logothetis, Hamid Reza Noori
http://arxiv.org/abs/1905.06225v1
• [stat.CO]A New Estimation Algorithm for Box-Cox Transformation Cure Rate Model and Comparison With EM Algorithm
Suvra Pal, Souvik Roy
http://arxiv.org/abs/1905.05963v1
• [stat.ME]Approximate Bayesian computation via the energy statistic
Hien D. Nguyen, Julyan Arbel, Hongliang Lü, Florence Forbes
http://arxiv.org/abs/1905.05884v1
• [stat.ME]False Discovery Rates to Detect Signals from Incomplete Spatially Aggregated Data
Hsin-Cheng Huang, Noel Cressie, Andrew Zammit-Mangion, Guowen Huang
http://arxiv.org/abs/1905.06268v1
• [stat.ME]Fast and robust model selection based on ranks
Wojciech Rejchel, Malgorzata Bogdan
http://arxiv.org/abs/1905.05876v1
• [stat.ME]Simultaneous Inference Under the Vacuous Orientation Assumption
Ruobin Gong
http://arxiv.org/abs/1905.05935v1
• [stat.ME]Simultaneous Inference for Pairwise Graphical Models with Generalized Score Matching
Ming Yu, Varun Gupta, Mladen Kolar
http://arxiv.org/abs/1905.06261v1
• [stat.ML]Distribution Calibration for Regression
Hao Song, Tom Diethe, Meelis Kull, Peter Flach
http://arxiv.org/abs/1905.06023v1
• [stat.ML]Domain Adaptive Transfer Learning for Fault Diagnosis
Qin Wang, Gabriel Michau, Olga Fink
http://arxiv.org/abs/1905.06004v1
• [stat.ML]Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions
Tim Pearce, Mohamed Zaki, Alexandra Brintrup, Andy Neely
http://arxiv.org/abs/1905.06076v1
• [stat.ML]Geometric Losses for Distributional Learning
Arthur Mensch, Mathieu Blondel, Gabriel Peyré
http://arxiv.org/abs/1905.06005v1
• [stat.ML]Iterative Alpha Expansion for estimating gradient-sparse signals from linear measurements
Sheng Xu, Zhou Fan
http://arxiv.org/abs/1905.06097v1
• [stat.ML]Transferable Clean-Label Poisoning Attacks on Deep Neural Nets
Chen Zhu, W. Ronny Huang, Ali Shafahi, Hengduo Li, Gavin Taylor, Christoph Studer, Tom Goldstein
http://arxiv.org/abs/1905.05897v1
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