astro-ph.SR - 太阳和天体物理学恒星
cs.AI - 人工智能 cs.AR - 硬件体系结构 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.DC - 分布式、并行与集群计算 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.NA - 数值分析 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.PL - 编程语言 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 cs.SY - 系统与控制 econ.EM - 计量经济学 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.FA - 泛函演算 math.NA - 数值分析 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.class-ph - 经典物理学 physics.comp-ph - 计算物理学 physics.geo-ph - 地球物理学 physics.soc-ph - 物理学与社会 q-bio.QM - 定量方法 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.SR]Exploring helical dynamos with machine learning
• [cs.AI]Accelerated Discovery of Sustainable Building Materials
• [cs.AI]Guiding Theorem Proving by Recurrent Neural Networks
• [cs.AI]Optimizing Sequential Medical Treatments with Auto-Encoding Heuristic Search in POMDPs
• [cs.AI]The Twin-System Approach as One Generic Solution for XAI: An Overview of ANN-CBR Twins for Explaining Deep Learning
• [cs.AR]HALLS: An Energy-Efficient Highly Adaptable Last Level STT-RAM Cache for Multicore Systems
• [cs.CL]A Multi-Task Learning Framework for Extracting Drugs and Their Interactions from Drug Labels
• [cs.CL]A Neural, Interactive-predictive System for Multimodal Sequence to Sequence Tasks
• [cs.CL]BERTSel: Answer Selection with Pre-trained Models
• [cs.CL]Correlation Coefficients and Semantic Textual Similarity
• [cs.CL]Cross-referencing using Fine-grained Topic Modeling
• [cs.CL]DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrases
• [cs.CL]Earlier Attention? Aspect-Aware LSTM for Aspect Sentiment Analysis
• [cs.CL]HellaSwag: Can a Machine Really Finish Your Sentence?
• [cs.CL]Human-like machine thinking: Language guided imagination
• [cs.CL]Interpretable Neural Predictions with Differentiable Binary Variables
• [cs.CL]Learning to Memorize in Neural Task-Oriented Dialogue Systems
• [cs.CL]Microblog Hashtag Generation via Encoding Conversation Contexts
• [cs.CL]Montague Semantics for Lambek Pregroups
• [cs.CL]Neural Metric Learning for Fast End-to-End Relation Extraction
• [cs.CL]PaperRobot: Incremental Draft Generation of Scientific Ideas
• [cs.CL]Predicting Annotation Difficulty to Improve Task Routing and Model Performance for Biomedical Information Extraction
• [cs.CL]Semantic flow in language networks
• [cs.CL]Story Ending Prediction by Transferable BERT
• [cs.CL]Structured Summarization of Academic Publications
• [cs.CL]Target Based Speech Act Classification in Political Campaign Text
• [cs.CL]Target Conditioned Sampling: Optimizing Data Selection for Multilingual Neural Machine Translation
• [cs.CL]Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation
• [cs.CR]Discrete Logarithmic Fuzzy Vault Scheme
• [cs.CR]Privacy-Preserving P2P Energy Market on the Blockchain
• [cs.CR]The Curious Case of Machine Learning In Malware Detection
• [cs.CV]3DViewGraph: Learning Global Features for 3D Shapes from A Graph of Unordered Views with Attention
• [cs.CV]A 2D dilated residual U-Net for multi-organ segmentation in thoracic CT
• [cs.CV]AutoDispNet: Improving Disparity Estimation with AutoML
• [cs.CV]Boundary Loss for Remote Sensing Imagery Semantic Segmentation
• [cs.CV]Deep Transfer Learning Methods for Colon Cancer Classification in Confocal Laser Microscopy Images
• [cs.CV]Disparity-based HDR imaging
• [cs.CV]Drone Shadow Tracking
• [cs.CV]Enabling Computer Vision Driven Assistive Devices for the Visually Impaired via Micro-architecture Design Exploration
• [cs.CV]FORECAST-CLSTM: A New Convolutional LSTM Network for Cloudage Nowcasting
• [cs.CV]Fast Regularity-Constrained Plane Reconstruction
• [cs.CV]Few-Shot Adversarial Learning of Realistic Neural Talking Head Models
• [cs.CV]Geometric Pose Affordance: 3D Human Pose with Scene Constraints
• [cs.CV]Image Captioning based on Deep Learning Methods: A Survey
• [cs.CV]Implications of Computer Vision Driven Assistive Technologies Towards Individuals with Visual Impairment
• [cs.CV]Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation
• [cs.CV]Learning Perspective Undistortion of Portraits
• [cs.CV]Learning Video Representations from Correspondence Proposals
• [cs.CV]Learning to Count Objects with Few Exemplar Annotations
• [cs.CV]Less Memory, Faster Speed: Refining Self-Attention Module for Image Reconstruction
• [cs.CV]Limitations and Biases in Facial Landmark Detection — An Empirical Study on Older Adults with Dementia
• [cs.CV]Multimodal 3D Object Detection from Simulated Pretraining
• [cs.CV]Multimodal Transformer with Multi-View Visual Representation for Image Captioning
• [cs.CV]Not All Parts Are Created Equal: 3D Pose Estimation by Modelling Bi-directional Dependencies of Body Parts
• [cs.CV]Parts4Feature: Learning 3D Global Features from Generally Semantic Parts in Multiple Views
• [cs.CV]Patch-based 3D Human Pose Refinement
• [cs.CV]Procedural Synthesis of Remote Sensing Images for Robust Change Detection with Neural Networks
• [cs.CV]SAWNet: A Spatially Aware Deep Neural Network for 3D Point Cloud Processing
• [cs.CV]Self-Supervised Similarity Learning for Digital Pathology
• [cs.CV]Semi-Supervised Learning by Augmented Distribution Alignment
• [cs.CV]Semi-Supervised Monocular Depth Estimation with Left-Right Consistency Using Deep Neural Network
• [cs.CV]Skeleton-Based Hand Gesture Recognition by Learning SPD Matrices with Neural Networks
• [cs.CV]Spin Detection in Robotic Table Tennis
• [cs.CV]SplitNet: Sim2Sim and Task2Task Transfer for Embodied Visual Navigation
• [cs.CV]U-Net Based Multi-instance Video Object Segmentation
• [cs.CV]What Do Adversarially Robust Models Look At?
• [cs.CV]Which Tasks Should Be Learned Together in Multi-task Learning?
• [cs.DC]Broadcast Congested Clique: Planted Cliques and Pseudorandom Generators
• [cs.DC]Custom Execution Environments with Containers in Pegasus-enabled Scientific Workflows
• [cs.DC]Distributed Algorithms for Subgraph-Centric Graph Platforms
• [cs.DC]Hyaline: Fast and Transparent Lock-Free Memory Reclamation
• [cs.DC]Locally Self-Adjusting Hypercubic Networks
• [cs.DC]Massively Parallel Computation via Remote Memory Access
• [cs.DC]Online Research Report: rDLB: A Novel Approach for Robust Dynamic Load Balancing of Scientific Applications with Parallel Independent Tasks
• [cs.IR]Abusive Language Detection in Online Conversations by Combining Content-and Graph-based Features
• [cs.IR]Learning Open Information Extraction of Implicit Relations from Reading Comprehension Datasets
• [cs.IR]Neural Graph Collaborative Filtering
• [cs.IT]Bidirectional Information Flow and the Roles of Privacy Masks in Cloud-Based Control
• [cs.IT]Cascaded Channel Estimation for Large Intelligent Metasurface Assisted Massive MIMO
• [cs.IT]Coding for Deletion Channels with Multiple Traces
• [cs.IT]Error Exponent Bounds for the Bee-Identification Problem
• [cs.IT]Indoor Signal Focusing with Deep Learning Designed Reconfigurable Intelligent Surfaces
• [cs.IT]Learning-Based Priority Pricing for Job Offloading in Mobile Edge Computing
• [cs.IT]On the Reliability of Wireless Virtual Reality at Terahertz (THz) Frequencies
• [cs.IT]Optimal Guessing under Nonextensive Framework and associated Moment Bounds
• [cs.IT]Power Inversion of the Massive MIMO Channel
• [cs.IT]Space-Time Signal Design for Multilevel Polar Coding in Slow Fading Broadcast Channels
• [cs.IT]Timing and Frequency Synchronization for 1-bit Massive MU-MIMO-OFDM Downlink
• [cs.LG]A Bayesian Approach to Robust Reinforcement Learning
• [cs.LG]A Case Study: Exploiting Neural Machine Translation to Translate CUDA to OpenCL
• [cs.LG]A Comparative Analysis of Feature Selection Methods for Biomarker Discovery in Study of Toxicant-treated Atlantic Cod (Gadus morhua) Liver
• [cs.LG]A comprehensive, application-oriented study of catastrophic forgetting in DNNs
• [cs.LG]A novel Multiplicative Polynomial Kernel for Volterra series identification
• [cs.LG]A type of generalization error induced by initialization in deep neural networks
• [cs.LG]Adaptive Attention Span in Transformers
• [cs.LG]Adversarially robust transfer learning
• [cs.LG]Alpha MAML: Adaptive Model-Agnostic Meta-Learning
• [cs.LG]An iterative scheme for feature based positioning using weighted dissimilarity measure
• [cs.LG]Automatic Posterior Transformation for Likelihood-Free Inference
• [cs.LG]Best Arm Identification in Generalized Linear Bandits
• [cs.LG]Butterfly: Robust One-step Approach towards Wildly-unsupervised Domain Adaptation
• [cs.LG]CERTIFAI: Counterfactual Explanations for Robustness, Transparency, Interpretability, and Fairness of Artificial Intelligence models
• [cs.LG]Catastrophic forgetting: still a problem for DNNs
• [cs.LG]Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
• [cs.LG]Combining Experience Replay with Exploration by Random Network Distillation
• [cs.LG]Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems
• [cs.LG]Continual Learning in Deep Neural Networks by Using a Kalman Optimiser
• [cs.LG]Convolutional Feature Extraction and Neural Arithmetic Logic Units for Stock Prediction
• [cs.LG]DARC: Differentiable ARchitecture Compression
• [cs.LG]Demand forecasting techniques for build-to-order lean manufacturing supply chains
• [cs.LG]Enforcing constraints for time series prediction in supervised, unsupervised and reinforcement learning
• [cs.LG]Evolving Rewards to Automate Reinforcement Learning
• [cs.LG]Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations
• [cs.LG]Formal derivation of Mesh Neural Networks with their Forward-Only gradient Propagation
• [cs.LG]Graph-based Semi-Supervised & Active Learning for Edge Flows
• [cs.LG]KGAT: Knowledge Graph Attention Network for Recommendation
• [cs.LG]Label Mapping Neural Networks with Response Consolidation for Class Incremental Learning
• [cs.LG]Learning Compact Neural Networks Using Ordinary Differential Equations as Activation Functions
• [cs.LG]Learning Ensembles of Anomaly Detectors on Synthetic Data
• [cs.LG]MaxEntropy Pursuit Variational Inference
• [cs.LG]Minimal Achievable Sufficient Statistic Learning
• [cs.LG]Multi-view Locality Low-rank Embedding for Dimension Reduction
• [cs.LG]Multinomial Distribution Learning for Effective Neural Architecture Search
• [cs.LG]Online Convex Optimization in Adversarial Markov Decision Processes
• [cs.LG]Optimisation of Overparametrized Sum-Product Networks
• [cs.LG]Perceptual Values from Observation
• [cs.LG]Predicting Model Failure using Saliency Maps in Autonomous Driving Systems
• [cs.LG]RaFM: Rank-Aware Factorization Machines
• [cs.LG]Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching
• [cs.LG]Sequential training algorithm for neural networks
• [cs.LG]Shaping the learning landscape in neural networks around wide flat minima
• [cs.LG]Sparse Transfer Learning via Winning Lottery Tickets
• [cs.LG]Spatio-Temporal Adversarial Learning for Detecting Unseen Falls
• [cs.LG]Stochastic Variance Reduction for Deep Q-learning
• [cs.LG]Things You May Not Know About Adversarial Example: A Black-box Adversarial Image Attack
• [cs.LG]Zero-Shot Knowledge Distillation in Deep Networks
• [cs.LO]Is Free Choice Permission Admissible in Classical Deontic Logic?
• [cs.MA]A Regularized Opponent Model with Maximum Entropy Objective
• [cs.MA]Arena: A General Evaluation Platform and Building Toolkit for Multi-Agent Intelligence
• [cs.NA]A Discrete Empirical Interpolation Method for Interpretable Immersion and Embedding of Nonlinear Manifolds
• [cs.NE]Can Bio-Inspired Swarm Algorithms Scale to Modern Societal Problems
• [cs.NE]Deep Reinforcement Learning Based Parameter Control in Differential Evolution
• [cs.NE]Water Distribution System Design Using Multi-Objective Genetic Algorithm with External Archive and Local Search
• [cs.NI]A Console GRID LA Console GRID Leveraged Authentication and Key Agreement Mechanism for LTE/SAE
• [cs.NI]Aeronautical Ad Hoc Networking for the Internet-Above-The-Clouds
• [cs.PL]Verification of Threshold-Based Distributed Algorithms by Decomposition to Decidable Logics
• [cs.RO]A Coordinated Search Strategy for Solitary Robots
• [cs.RO]A semantic-aided particle filter approach for AUV localization
• [cs.RO]Characterizing SLAM Benchmarks and Methods for the Robust Perception Age
• [cs.RO]Good Feature Selection for Least Squares Pose Optimization in VO/VSLAM
• [cs.RO]Learning while Competing — 3D Modeling & Design
• [cs.RO]Low-latency Visual SLAM with Appearance-Enhanced Local Map Building
• [cs.RO]Object Rearrangement with Nested Nonprehensile Manipulation Actions
• [cs.RO]Planning coordinated motions for tethered planar mobile robots
• [cs.RO]Positioning aiding using LiDAR in GPS signal loss scenarios
• [cs.RO]REPLAB: A Reproducible Low-Cost Arm Benchmark Platform for Robotic Learning
• [cs.RO]Reinforcement Learning without Ground-Truth State
• [cs.RO]SCALAR: Simultaneous Calibration of 2D Laser and Robot Kinematic Parameters Using Planarity and Distance Constraints
• [cs.SD]Dance Hit Song Prediction
• [cs.SE]Testing Deep Neural Network based Image Classifiers
• [cs.SI]Graph Mining Meets Crowdsourcing: Extracting Experts for Answer Aggregation
• [cs.SI]Online reactions to the 2017 ‘Unite the Right’ rally in Charlottesville: measuring polarization in Twitter networks using media followership
• [cs.SI]Understanding the Radical Mind: Identifying Signals to Detect Extremist Content on Twitter
• [cs.SY]Investigating Flight Envelope Variation Predictability of Impaired Aircraft using Least-Squares Regression Analysis
• [econ.EM]Conformal Prediction Interval Estimations with an Application to Day-Ahead and Intraday Power Markets
• [econ.EM]Nonparametric Instrumental Regressions with (Potentially Discrete) Instruments Independent of the Error Term
• [eess.IV]An Objective Evaluation Metric for image fusion based on Del Operator
• [eess.IV]Quantitative Error Prediction of Medical Image Registration using Regression Forests
• [eess.SP]Transmitter Classification With Supervised Deep Learning
• [math.FA]A note on variance bounds and location of eigenvalues
• [math.NA]Uniform bounds for invariant subspace perturbations
• [math.OC]A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization
• [math.OC]Trajectory Optimization on Manifolds: A Theoretically-Guaranteed Embedded Sequential Convex Programming Approach
• [math.PR]Mean-Field Langevin Dynamics and Energy Landscape of Neural Networks
• [math.PR]On a Tail Bound for Root-Finding in Randomly Growing Trees
• [math.ST]A residual-based bootstrap for functional autoregressions
• [math.ST]Integrated conditional moment test and beyond: when the number of covariates is divergent
• [math.ST]Method comparison with repeated measurements - Passing-Bablok regression for grouped data with errors in both variables
• [math.ST]On approximation of the distribution for Pearson statistic
• [math.ST]Second Order Expansions for Sample Median with Random Sample Size
• [math.ST]Teaching decision theory proof strategies using a crowdsourcing problem
• [physics.class-ph]Physics-informed transfer path analysis with parameter estimation using Gaussian processes
• [physics.comp-ph]Exploiting Parallelism on Shared Memory in the QED Particle-in-Cell Code PICADOR with Greedy Load Balancing
• [physics.comp-ph]Leveraging Bayesian Analysis To Improve Accuracy of Approximate Models
• [physics.geo-ph]Artificial Neural Network Surrogate Modeling of Oil Reservoir: a Case Study
• [physics.soc-ph]Diagnosing the performance of human mobility models at small spatial scales using volunteered geographic information
• [physics.soc-ph]The configuration model for Barabasi-Albert networks
• [q-bio.QM]Decoding the Rejuvenating Effects of Mechanical Loading on Skeletal Maturation using in Vivo Imaging and Deep Learning
• [stat.AP]ACE of Space: Estimating Genetic Components of High-Dimensional Imaging Data
• [stat.AP]On Changes of Global Wet-bulb Temperature and Snowfall Regimes
• [stat.AP]Optimizing Interim Analysis Timing for Bayesian Adaptive Commensurate Designs
• [stat.CO]LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations
• [stat.CO]Stratified sampling and resampling for approximate Bayesian computation
• [stat.ME]Causal Inference for Multiple Non-Randomized Treatments using Fractional Factorial Designs
• [stat.ME]Estimating variances in time series linear regression models using empirical BLUPs and convex optimization
• [stat.ME]Factor Models for High-Dimensional Tensor Time Series
• [stat.ME]Modeling of Missing Dynamical Systems: Deriving Parametric Models using a Nonparametric Framework
• [stat.ME]Non-Parametric Estimation of Spot Covariance Matrix with High-Frequency Data
• [stat.ME]On Selecting Stable Predictors in Time Series Models
• [stat.ME]Semiparametric estimation for space-time max-stable processes: F -madogram-based estimation approach
• [stat.ME]Study designs for extending causal inferences from a randomized trial to a target population
• [stat.ML]A Distributionally Robust Boosting Algorithm
• [stat.ML]An Online Stochastic Kernel Machine for Robust Signal Classification
• [stat.ML]Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees
• [stat.ML]Gradient Ascent for Active Exploration in Bandit Problems
• [stat.ML]Gradient tree boosting with random output projections for multi-label classification and multi-output regression
• [stat.ML]Leveraging Semantic Embeddings for Safety-Critical Applications
• [stat.ML]PAC-Bayes under potentially heavy tails
• [stat.ML]Practical Bayesian Optimization with Threshold-Guided Marginal Likelihood Maximization
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• [astro-ph.SR]Exploring helical dynamos with machine learning
Farrukh Nauman, Joonas Nättilä
http://arxiv.org/abs/1905.08193v1
• [cs.AI]Accelerated Discovery of Sustainable Building Materials
Xiou Ge, Richard T. Goodwin, Jeremy R. Gregory, Randolph E. Kirchain, Joana Maria, Lav R. Varshney
http://arxiv.org/abs/1905.08222v1
• [cs.AI]Guiding Theorem Proving by Recurrent Neural Networks
Bartosz Piotrowski, Josef Urban
http://arxiv.org/abs/1905.07961v1
• [cs.AI]Optimizing Sequential Medical Treatments with Auto-Encoding Heuristic Search in POMDPs
Luchen Li, Matthieu Komorowski, Aldo A. Faisal
http://arxiv.org/abs/1905.07465v1
• [cs.AI]The Twin-System Approach as One Generic Solution for XAI: An Overview of ANN-CBR Twins for Explaining Deep Learning
Mark T. Keane, Eoin M. Kenny
http://arxiv.org/abs/1905.08069v1
• [cs.AR]HALLS: An Energy-Efficient Highly Adaptable Last Level STT-RAM Cache for Multicore Systems
Kyle Kuan, Tosiron Adegbija
http://arxiv.org/abs/1905.07511v1
• [cs.CL]A Multi-Task Learning Framework for Extracting Drugs and Their Interactions from Drug Labels
Tung Tran, Ramakanth Kavuluru, Halil Kilicoglu
http://arxiv.org/abs/1905.07464v1
• [cs.CL]A Neural, Interactive-predictive System for Multimodal Sequence to Sequence Tasks
Álvaro Peris, Francisco Casacuberta
http://arxiv.org/abs/1905.08181v1
• [cs.CL]BERTSel: Answer Selection with Pre-trained Models
Dongfang Li, Yifei Yu, Qingcai Chen, Xinyu Li
http://arxiv.org/abs/1905.07588v1
• [cs.CL]Correlation Coefficients and Semantic Textual Similarity
Vitalii Zhelezniak, Aleksandar Savkov, April Shen, Nils Y. Hammerla
http://arxiv.org/abs/1905.07790v1
• [cs.CL]Cross-referencing using Fine-grained Topic Modeling
Jeffrey Lund, Piper Armstrong, Wilson Fearn, Stephen Cowley, Emily Hales, Kevin Seppi
http://arxiv.org/abs/1905.07508v1
• [cs.CL]DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrases
Zhiqing Sun, Jian Tang, Pan Du, Zhi-Hong Deng, Jian-Yun Nie
http://arxiv.org/abs/1905.07689v1
• [cs.CL]Earlier Attention? Aspect-Aware LSTM for Aspect Sentiment Analysis
Bowen Xing, Lejian Liao, Dandan Song, Jingang Wang, Fuzheng Zhang, Zhongyuan Wang, Heyan Huang
http://arxiv.org/abs/1905.07719v1
• [cs.CL]HellaSwag: Can a Machine Really Finish Your Sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, Yejin Choi
http://arxiv.org/abs/1905.07830v1
• [cs.CL]Human-like machine thinking: Language guided imagination
Feng Qi, Wenchuan Wu
http://arxiv.org/abs/1905.07562v1
• [cs.CL]Interpretable Neural Predictions with Differentiable Binary Variables
Joost Bastings, Wilker Aziz, Ivan Titov
http://arxiv.org/abs/1905.08160v1
• [cs.CL]Learning to Memorize in Neural Task-Oriented Dialogue Systems
Chien-Sheng Wu
http://arxiv.org/abs/1905.07687v1
• [cs.CL]Microblog Hashtag Generation via Encoding Conversation Contexts
Yue Wang, Jing Li, Irwin King, Michael R. Lyu, Shuming Shi
http://arxiv.org/abs/1905.07584v1
• [cs.CL]Montague Semantics for Lambek Pregroups
Giovanni de Felice, Konstantinos Meichanetzidis, Alexis Toumi
http://arxiv.org/abs/1905.07408v1
• [cs.CL]Neural Metric Learning for Fast End-to-End Relation Extraction
Tung Tran, Ramakanth Kavuluru
http://arxiv.org/abs/1905.07458v1
• [cs.CL]PaperRobot: Incremental Draft Generation of Scientific Ideas
Qingyun Wang, Lifu Huang, Zhiying Jiang, Kevin Knight, Heng Ji, Mohit Bansal, Yi Luan
http://arxiv.org/abs/1905.07870v1
• [cs.CL]Predicting Annotation Difficulty to Improve Task Routing and Model Performance for Biomedical Information Extraction
Yinfei Yang, Oshin Agarwal, Chris Tar, Byron C. Wallace, Ani Nenkova
http://arxiv.org/abs/1905.07791v1
• [cs.CL]Semantic flow in language networks
Edilson A. Corrêa Jr., Vanessa Q. Marinho, Diego R. Amancio
http://arxiv.org/abs/1905.07595v1
• [cs.CL]Story Ending Prediction by Transferable BERT
Zhongyang Li, Xiao Ding, Ting Liu
http://arxiv.org/abs/1905.07504v1
• [cs.CL]Structured Summarization of Academic Publications
Alexios Gidiotis, Grigorios Tsoumakas
http://arxiv.org/abs/1905.07695v1
• [cs.CL]Target Based Speech Act Classification in Political Campaign Text
Shivashankar Subramanian, Trevor Cohn, Timothy Baldwin
http://arxiv.org/abs/1905.07856v1
• [cs.CL]Target Conditioned Sampling: Optimizing Data Selection for Multilingual Neural Machine Translation
Xinyi Wang, Graham Neubig
http://arxiv.org/abs/1905.08212v1
• [cs.CL]Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation
Jiaqi Guo, Zecheng Zhan, Yan Gao, Yan Xiao, Jian-Guang Lou, Ting Liu, Dongmei Zhang
http://arxiv.org/abs/1905.08205v1
• [cs.CR]Discrete Logarithmic Fuzzy Vault Scheme
Khaled Ahmed Nagaty
http://arxiv.org/abs/1905.07561v1
• [cs.CR]Privacy-Preserving P2P Energy Market on the Blockchain
Alain Brenzikofer, Noa Melchior
http://arxiv.org/abs/1905.07940v1
• [cs.CR]The Curious Case of Machine Learning In Malware Detection
Sherif Saad, William Briguglio, Haytham Elmiligi
http://arxiv.org/abs/1905.07573v1
• [cs.CV]3DViewGraph: Learning Global Features for 3D Shapes from A Graph of Unordered Views with Attention
Zhizhong Han, Xiyang Wang, Chi-Man Vong, Yu-Shen Liu, Matthias Zwicker, C. L. Philip Chen
http://arxiv.org/abs/1905.07503v1
• [cs.CV]A 2D dilated residual U-Net for multi-organ segmentation in thoracic CT
Sulaiman Vesal, Nishant Ravikumar, Andreas Maier
http://arxiv.org/abs/1905.07710v1
• [cs.CV]AutoDispNet: Improving Disparity Estimation with AutoML
Tonmoy Saikia, Yassine Marrakchi, Arber Zela, Frank Hutter, Thomas Brox
http://arxiv.org/abs/1905.07443v1
• [cs.CV]Boundary Loss for Remote Sensing Imagery Semantic Segmentation
Alexey Bokhovkin, Evgeny Burnaev
http://arxiv.org/abs/1905.07852v1
• [cs.CV]Deep Transfer Learning Methods for Colon Cancer Classification in Confocal Laser Microscopy Images
Nils Gessert, Marcel Bengs, Lukas Wittig, Daniel Drömann, Tobias Keck, Alexander Schlaefer, David B. Ellebrecht
http://arxiv.org/abs/1905.07991v1
• [cs.CV]Disparity-based HDR imaging
Jennifer Bonnard, Gilles Valette, Céline Loscos
http://arxiv.org/abs/1905.07918v1
• [cs.CV]Drone Shadow Tracking
Xiaoyan Zou, Ruofan Zhou, Majed El Helou, Sabine Süsstrunk
http://arxiv.org/abs/1905.08214v1
• [cs.CV]Enabling Computer Vision Driven Assistive Devices for the Visually Impaired via Micro-architecture Design Exploration
Linda Wang, Alexander Wong
http://arxiv.org/abs/1905.07836v1
• [cs.CV]FORECAST-CLSTM: A New Convolutional LSTM Network for Cloudage Nowcasting
Chao Tan, Xin Feng, Jianwu Long, Li Geng
http://arxiv.org/abs/1905.07700v1
• [cs.CV]Fast Regularity-Constrained Plane Reconstruction
Yangbin Lin, Jialian Li, Cheng Wang, Zhonggui Chen, Zongyue Wang, Jonathan Li
http://arxiv.org/abs/1905.07922v1
• [cs.CV]Few-Shot Adversarial Learning of Realistic Neural Talking Head Models
Egor Zakharov, Aliaksandra Shysheya, Egor Burkov, Victor Lempitsky
http://arxiv.org/abs/1905.08233v1
• [cs.CV]Geometric Pose Affordance: 3D Human Pose with Scene Constraints
Zhe Wang, Liyan Chen, Shaurya Rathore, Daeyun Shin, Charless Fowlkes
http://arxiv.org/abs/1905.07718v1
• [cs.CV]Image Captioning based on Deep Learning Methods: A Survey
Yiyu Wang, Jungang Xu, Yingfei Sun, Ben He
http://arxiv.org/abs/1905.08110v1
• [cs.CV]Implications of Computer Vision Driven Assistive Technologies Towards Individuals with Visual Impairment
Linda Wang, Alexander Wong
http://arxiv.org/abs/1905.07844v1
• [cs.CV]Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation
Xiaofeng Xu, Ivor W. Tsang, Xiaofeng Cao, Ruiheng Zhang, Chuancai Liu
http://arxiv.org/abs/1905.07933v1
• [cs.CV]Learning Perspective Undistortion of Portraits
Yajie Zhao, Zeng Huang, Tianye Li, Weikai Chen, Chloe LeGendre, Xinglei Ren, Jun Xing, Ari Shapiro, Hao Li
http://arxiv.org/abs/1905.07515v1
• [cs.CV]Learning Video Representations from Correspondence Proposals
Xingyu Liu, Joon-Young Lee, Hailin Jin
http://arxiv.org/abs/1905.07853v1
• [cs.CV]Learning to Count Objects with Few Exemplar Annotations
Jianfeng Wang, Rong Xiao, Yandong Guo, Lei Zhang
http://arxiv.org/abs/1905.07898v1
• [cs.CV]Less Memory, Faster Speed: Refining Self-Attention Module for Image Reconstruction
Zheng Wang, Jianwu Li, Ge Song, Tieling Li
http://arxiv.org/abs/1905.08008v1
• [cs.CV]Limitations and Biases in Facial Landmark Detection — An Empirical Study on Older Adults with Dementia
Azin Asgarian, Shun Zhao, Ahmed B. Ashraf, M. Erin Browne, Kenneth M. Prkachin, Alex Mihailidis, Thomas Hadjistavropoulos, Babak Taati
http://arxiv.org/abs/1905.07446v1
• [cs.CV]Multimodal 3D Object Detection from Simulated Pretraining
Åsmund Brekke, Fredrik Vatsendvik, Frank Lindseth
http://arxiv.org/abs/1905.07754v1
• [cs.CV]Multimodal Transformer with Multi-View Visual Representation for Image Captioning
Jun Yu, Jing Li, Zhou Yu, Qingming Huang
http://arxiv.org/abs/1905.07841v1
• [cs.CV]Not All Parts Are Created Equal: 3D Pose Estimation by Modelling Bi-directional Dependencies of Body Parts
Jue Wang, Shaoli Huang, Xinchao Wang, Dacheng Tao
http://arxiv.org/abs/1905.07862v1
• [cs.CV]Parts4Feature: Learning 3D Global Features from Generally Semantic Parts in Multiple Views
Zhizhong Han, Xinhai Liu, Yu-Shen Liu, Matthias Zwicker
http://arxiv.org/abs/1905.07506v1
• [cs.CV]Patch-based 3D Human Pose Refinement
Qingfu Wan, Weichao Qiu, Alan L. Yuille
http://arxiv.org/abs/1905.08231v1
• [cs.CV]Procedural Synthesis of Remote Sensing Images for Robust Change Detection with Neural Networks
Maria Kolos, Anton Marin, Alexey Artemov, Evgeny Burnaev
http://arxiv.org/abs/1905.07877v1
• [cs.CV]SAWNet: A Spatially Aware Deep Neural Network for 3D Point Cloud Processing
Chaitanya Kaul, Nick Pears, Suresh Manandhar
http://arxiv.org/abs/1905.07650v1
• [cs.CV]Self-Supervised Similarity Learning for Digital Pathology
Jacob Gildenblat, Eldad Klaiman
http://arxiv.org/abs/1905.08139v1
• [cs.CV]Semi-Supervised Learning by Augmented Distribution Alignment
Qin Wang, Wen Li, Luc Van Gool
http://arxiv.org/abs/1905.08171v1
• [cs.CV]Semi-Supervised Monocular Depth Estimation with Left-Right Consistency Using Deep Neural Network
Ali Jahani Amiri, Shing Yan Loo, Hong Zhang
http://arxiv.org/abs/1905.07542v1
• [cs.CV]Skeleton-Based Hand Gesture Recognition by Learning SPD Matrices with Neural Networks
Xuan Nguyen, Luc Brun, Olivier Lezoray, Sébastien Bougleux
http://arxiv.org/abs/1905.07917v1
• [cs.CV]Spin Detection in Robotic Table Tennis
Jonas Tebbe, Lukas Klamt, Andreas Zell
http://arxiv.org/abs/1905.07967v1
• [cs.CV]SplitNet: Sim2Sim and Task2Task Transfer for Embodied Visual Navigation
Daniel Gordon, Abhishek Kadian, Devi Parikh, Judy Hoffman, Dhruv Batra
http://arxiv.org/abs/1905.07512v1
• [cs.CV]U-Net Based Multi-instance Video Object Segmentation
Heguang Liu, Jingle Jiang
http://arxiv.org/abs/1905.07826v1
• [cs.CV]What Do Adversarially Robust Models Look At?
Takahiro Itazuri, Yoshihiro Fukuhara, Hirokatsu Kataoka, Shigeo Morishima
http://arxiv.org/abs/1905.07666v1
• [cs.CV]Which Tasks Should Be Learned Together in Multi-task Learning?
Trevor Standley, Amir R. Zamir, Dawn Chen, Leonidas Guibas, Jitendra Malik, Silvio Savarese
http://arxiv.org/abs/1905.07553v1
• [cs.DC]Broadcast Congested Clique: Planted Cliques and Pseudorandom Generators
Lijie Chen, Ofer Grossman
http://arxiv.org/abs/1905.07780v1
• [cs.DC]Custom Execution Environments with Containers in Pegasus-enabled Scientific Workflows
Karan Vahi, Mats Rynge, George Papadimitriou, Duncan A. Brown, Rajiv Mayani, Rafael Ferreira da Silva, Ewa Deelman, Anirban Mandal, Eric Lyons, Michael Zink
http://arxiv.org/abs/1905.08204v1
• [cs.DC]Distributed Algorithms for Subgraph-Centric Graph Platforms
Diptanshu Kakwani, Yogesh Simmhan
http://arxiv.org/abs/1905.08051v1
• [cs.DC]Hyaline: Fast and Transparent Lock-Free Memory Reclamation
Ruslan Nikolaev, Binoy Ravindran
http://arxiv.org/abs/1905.07903v1
• [cs.DC]Locally Self-Adjusting Hypercubic Networks
Sikder Huq, Sukumar Ghosh
http://arxiv.org/abs/1905.07699v1
• [cs.DC]Massively Parallel Computation via Remote Memory Access
Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Łącki, Warren Schudy, Vahab Mirrokni
http://arxiv.org/abs/1905.07533v1
• [cs.DC]Online Research Report: rDLB: A Novel Approach for Robust Dynamic Load Balancing of Scientific Applications with Parallel Independent Tasks
Ali Mohammed, Aurelien Cavelan, Florina M. Ciorba
http://arxiv.org/abs/1905.08073v1
• [cs.IR]Abusive Language Detection in Online Conversations by Combining Content-and Graph-based Features
Noé Cecillon, Vincent Labatut, Richard Dufour, Georges Linarès
http://arxiv.org/abs/1905.07894v1
• [cs.IR]Learning Open Information Extraction of Implicit Relations from Reading Comprehension Datasets
Jacob Beckerman, Theodore Christakis
http://arxiv.org/abs/1905.07471v1
• [cs.IR]Neural Graph Collaborative Filtering
Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng, Tat-Seng Chua
http://arxiv.org/abs/1905.08108v1
• [cs.IT]Bidirectional Information Flow and the Roles of Privacy Masks in Cloud-Based Control
Ali Reza Pedram, Takashi Tanaka, Matthew Hale
http://arxiv.org/abs/1905.07459v1
• [cs.IT]Cascaded Channel Estimation for Large Intelligent Metasurface Assisted Massive MIMO
Zhen-Qing He, Xiaojun Yuan
http://arxiv.org/abs/1905.07948v1
• [cs.IT]Coding for Deletion Channels with Multiple Traces
Mahed Abroshan, Ramji Venkataramanan, Lara Dolecek, Albert Guillén i Fàbregas
http://arxiv.org/abs/1905.08197v1
• [cs.IT]Error Exponent Bounds for the Bee-Identification Problem
Anshoo Tandon, Vincent Y. F. Tan, Lav R. Varshney
http://arxiv.org/abs/1905.07868v1
• [cs.IT]Indoor Signal Focusing with Deep Learning Designed Reconfigurable Intelligent Surfaces
Chongwen Huang, George C. Alexandropoulos, Chau Yuen, Mérouane Debbah
http://arxiv.org/abs/1905.07726v1
• [cs.IT]Learning-Based Priority Pricing for Job Offloading in Mobile Edge Computing
Lingxiang Li, Marie Siew, Tony Q. S. Quek, Ju Ren, Zhi Chen, Yaoxue Zhang
http://arxiv.org/abs/1905.07749v1
• [cs.IT]On the Reliability of Wireless Virtual Reality at Terahertz (THz) Frequencies
Christina Chaccour, Ramy Amer, Bo Zhou, Walid Saad
http://arxiv.org/abs/1905.07656v1
• [cs.IT]Optimal Guessing under Nonextensive Framework and associated Moment Bounds
Abhik Ghosh
http://arxiv.org/abs/1905.07729v1
• [cs.IT]Power Inversion of the Massive MIMO Channel
Jens Abraham, Torbjörn Ekman
http://arxiv.org/abs/1905.07555v1
• [cs.IT]Space-Time Signal Design for Multilevel Polar Coding in Slow Fading Broadcast Channels
Hossein Khoshnevis, Ian Marsland, Hamid Jafarkhani, Halim Yanikomeroglu
http://arxiv.org/abs/1905.07876v1
• [cs.IT]Timing and Frequency Synchronization for 1-bit Massive MU-MIMO-OFDM Downlink
Sven Jacobsson, Carl Lindquist, Giuseppe Durisi, Thomas Eriksson, Christoph Studer
http://arxiv.org/abs/1905.07792v1
• [cs.LG]A Bayesian Approach to Robust Reinforcement Learning
Esther Derman, Daniel Mankowitz, Timothy Mann, Shie Mannor
http://arxiv.org/abs/1905.08188v1
• [cs.LG]A Case Study: Exploiting Neural Machine Translation to Translate CUDA to OpenCL
Yonghae Kim, Hyesoon Kim
http://arxiv.org/abs/1905.07653v1
• [cs.LG]A Comparative Analysis of Feature Selection Methods for Biomarker Discovery in Study of Toxicant-treated Atlantic Cod (Gadus morhua) Liver
Xiaokang Zhang, Inge Jonassen
http://arxiv.org/abs/1905.08048v1
• [cs.LG]A comprehensive, application-oriented study of catastrophic forgetting in DNNs
B. Pfülb, A. Gepperth
http://arxiv.org/abs/1905.08101v1
• [cs.LG]A novel Multiplicative Polynomial Kernel for Volterra series identification
Alberto Dalla Libera, Ruggero Carli, Gianluigi Pillonetto
http://arxiv.org/abs/1905.07960v1
• [cs.LG]A type of generalization error induced by initialization in deep neural networks
Yaoyu Zhang, Zhi-Qin John Xu, Tao Luo, Zheng Ma
http://arxiv.org/abs/1905.07777v1
• [cs.LG]Adaptive Attention Span in Transformers
Sainbayar Sukhbaatar, Edouard Grave, Piotr Bojanowski, Armand Joulin
http://arxiv.org/abs/1905.07799v1
• [cs.LG]Adversarially robust transfer learning
Ali Shafahi, Parsa Saadatpanah, Chen Zhu, Amin Ghiasi, Christoph Studer, David Jacobs, Tom Goldstein
http://arxiv.org/abs/1905.08232v1
• [cs.LG]Alpha MAML: Adaptive Model-Agnostic Meta-Learning
Harkirat Singh Behl, Atılım Güneş Baydin, Philip H. S. Torr
http://arxiv.org/abs/1905.07435v1
• [cs.LG]An iterative scheme for feature based positioning using weighted dissimilarity measure
Caifa Zhou, Andreas Wieser
http://arxiv.org/abs/1905.08022v1
• [cs.LG]Automatic Posterior Transformation for Likelihood-Free Inference
David S. Greenberg, Marcel Nonnenmacher, Jakob H. Macke
http://arxiv.org/abs/1905.07488v1
• [cs.LG]Best Arm Identification in Generalized Linear Bandits
Abbas Kazerouni, Lawrence M. Wein
http://arxiv.org/abs/1905.08224v1
• [cs.LG]Butterfly: Robust One-step Approach towards Wildly-unsupervised Domain Adaptation
Feng Liu, Jie Lu, Bo Han, Gang Niu, Guangquan Zhang, Masashi Sugiyama
http://arxiv.org/abs/1905.07720v1
• [cs.LG]CERTIFAI: Counterfactual Explanations for Robustness, Transparency, Interpretability, and Fairness of Artificial Intelligence models
Shubham Sharma, Jette Henderson, Joydeep Ghosh
http://arxiv.org/abs/1905.07857v1
• [cs.LG]Catastrophic forgetting: still a problem for DNNs
B. Pfülb, A. Gepperth, S. Abdullah, A. Kilian
http://arxiv.org/abs/1905.08077v1
• [cs.LG]Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, Cho-Jui Hsieh
http://arxiv.org/abs/1905.07953v1
• [cs.LG]Combining Experience Replay with Exploration by Random Network Distillation
Francesco Sovrano
http://arxiv.org/abs/1905.07579v1
• [cs.LG]Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems
Sangkyun Lee, Jeonghyun Lee
http://arxiv.org/abs/1905.07931v1
• [cs.LG]Continual Learning in Deep Neural Networks by Using a Kalman Optimiser
Honglin Li, Shirin Enshaeifar, Frieder Ganz, Payam Barnaghi
http://arxiv.org/abs/1905.08119v1
• [cs.LG]Convolutional Feature Extraction and Neural Arithmetic Logic Units for Stock Prediction
Shangeth Rajaa, Jajati Keshari Sahoo
http://arxiv.org/abs/1905.07581v1
• [cs.LG]DARC: Differentiable ARchitecture Compression
Shashank Singh, Ashish Khetan, Zohar Karnin
http://arxiv.org/abs/1905.08170v1
• [cs.LG]Demand forecasting techniques for build-to-order lean manufacturing supply chains
Rodrigo Rivera-Castro, Ivan Nazarov, Yuke Xiang, Alexander Pletneev, Ivan Maksimov, Evgeny Burnaev
http://arxiv.org/abs/1905.07902v1
• [cs.LG]Enforcing constraints for time series prediction in supervised, unsupervised and reinforcement learning
Panos Stinis
http://arxiv.org/abs/1905.07501v1
• [cs.LG]Evolving Rewards to Automate Reinforcement Learning
Aleksandra Faust, Anthony Francis, Dar Mehta
http://arxiv.org/abs/1905.07628v1
• [cs.LG]Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations
Ramaravind Kommiya Mothilal, Amit Sharma, Chenhao Tan
http://arxiv.org/abs/1905.07697v1
• [cs.LG]Formal derivation of Mesh Neural Networks with their Forward-Only gradient Propagation
Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini
http://arxiv.org/abs/1905.06684v2
• [cs.LG]Graph-based Semi-Supervised & Active Learning for Edge Flows
Junteng Jia, Michael T. Schaub, Santiago Segarra, Austin R. Benson
http://arxiv.org/abs/1905.07451v1
• [cs.LG]KGAT: Knowledge Graph Attention Network for Recommendation
Xiang Wang, Xiangnan He, Yixin Cao, Meng Liu, Tat-Seng Chua
http://arxiv.org/abs/1905.07854v1
• [cs.LG]Label Mapping Neural Networks with Response Consolidation for Class Incremental Learning
Xu Zhang, Yang Yao, Baile Xu, Lekun Mao, Furao Shen, Jian Zhao, Qingwei Lin
http://arxiv.org/abs/1905.07835v1
• [cs.LG]Learning Compact Neural Networks Using Ordinary Differential Equations as Activation Functions
MohamadAli Torkamani, Phillip Wallis, Shiv Shankar, Amirmohammad Rooshenas
http://arxiv.org/abs/1905.07685v1
• [cs.LG]Learning Ensembles of Anomaly Detectors on Synthetic Data
D. Smolyakov, N. Sviridenko, V. Ishimtsev, E. Burikov, E. Burnaev
http://arxiv.org/abs/1905.07892v1
• [cs.LG]MaxEntropy Pursuit Variational Inference
Evgenii Egorov, Kirill Neklydov, Ruslan Kostoev, Evgeny Burnaev
http://arxiv.org/abs/1905.07855v1
• [cs.LG]Minimal Achievable Sufficient Statistic Learning
Milan Cvitkovic, Günther Koliander
http://arxiv.org/abs/1905.07822v1
• [cs.LG]Multi-view Locality Low-rank Embedding for Dimension Reduction
Lin Feng, Xiangzhu Meng, Huibing Wang
http://arxiv.org/abs/1905.08138v1
• [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/1905.07529v1
• [cs.LG]Online Convex Optimization in Adversarial Markov Decision Processes
Aviv Rosenberg, Yishay Mansour
http://arxiv.org/abs/1905.07773v1
• [cs.LG]Optimisation of Overparametrized Sum-Product Networks
Martin Trapp, Robert Peharz, Franz Pernkopf
http://arxiv.org/abs/1905.08196v1
• [cs.LG]Perceptual Values from Observation
Ashley D. Edwards, Charles L. Isbell
http://arxiv.org/abs/1905.07861v1
• [cs.LG]Predicting Model Failure using Saliency Maps in Autonomous Driving Systems
Sina Mohseni, Akshay Jagadeesh, Zhangyang Wang
http://arxiv.org/abs/1905.07679v1
• [cs.LG]RaFM: Rank-Aware Factorization Machines
Xiaoshuang Chen, Yin Zheng, Jiaxing Wang, Wenye Ma, Junzhou Huang
http://arxiv.org/abs/1905.07570v1
• [cs.LG]Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching
Hongteng Xu, Dixin Luo, Lawrence Carin
http://arxiv.org/abs/1905.07645v1
• [cs.LG]Sequential training algorithm for neural networks
Jongrae Kim
http://arxiv.org/abs/1905.07490v1
• [cs.LG]Shaping the learning landscape in neural networks around wide flat minima
Carlo Baldassi, Fabrizio Pittorino, Riccardo Zecchina
http://arxiv.org/abs/1905.07833v1
• [cs.LG]Sparse Transfer Learning via Winning Lottery Tickets
Rahul Mehta
http://arxiv.org/abs/1905.07785v1
• [cs.LG]Spatio-Temporal Adversarial Learning for Detecting Unseen Falls
Shehroz S. Khan, Jacob Nogas, Alex Mihailidis
http://arxiv.org/abs/1905.07817v1
• [cs.LG]Stochastic Variance Reduction for Deep Q-learning
Wei-Ye Zhao, Xi-Ya Guan, Yang Liu, Xiaoming Zhao, Jian Peng
http://arxiv.org/abs/1905.08152v1
• [cs.LG]Things You May Not Know About Adversarial Example: A Black-box Adversarial Image Attack
Yuchao Duan, Zhe Zhao, Lei Bu, Fu Song
http://arxiv.org/abs/1905.07672v1
• [cs.LG]Zero-Shot Knowledge Distillation in Deep Networks
Gaurav Kumar Nayak, Konda Reddy Mopuri, Vaisakh Shaj, R. Venkatesh Babu, Anirban Chakraborty
http://arxiv.org/abs/1905.08114v1
• [cs.LO]Is Free Choice Permission Admissible in Classical Deontic Logic?
Guido Governatori, Antonino Rotolo
http://arxiv.org/abs/1905.07696v1
• [cs.MA]A Regularized Opponent Model with Maximum Entropy Objective
Zheng Tian, Ying Wen, Zhichen Gong, Faiz Punakkath, Shihao Zou, Jun Wang
http://arxiv.org/abs/1905.08087v1
• [cs.MA]Arena: A General Evaluation Platform and Building Toolkit for Multi-Agent Intelligence
Yuhang Song, Jianyi Wang, Thomas Lukasiewicz, Zhenghua Xu, Mai Xu, Zihan Ding, Lianlong Wu
http://arxiv.org/abs/1905.08085v1
• [cs.NA]A Discrete Empirical Interpolation Method for Interpretable Immersion and Embedding of Nonlinear Manifolds
Samuel E. Otto, Clarence W. Rowley
http://arxiv.org/abs/1905.07619v1
• [cs.NE]Can Bio-Inspired Swarm Algorithms Scale to Modern Societal Problems
Darren M. Chitty, Elizabeth Wanner, Rakhi Parmar, Peter R. Lewis
http://arxiv.org/abs/1905.08126v1
• [cs.NE]Deep Reinforcement Learning Based Parameter Control in Differential Evolution
Mudita Sharma, Alexandros Komninos, Manuel Lopez Ibanez, Dimitar Kazakov
http://arxiv.org/abs/1905.08006v1
• [cs.NE]Water Distribution System Design Using Multi-Objective Genetic Algorithm with External Archive and Local Search
Mahesh Patil, M. Naveen Naidu, A. Vasan, Murari R. R. Varma
http://arxiv.org/abs/1905.08105v1
• [cs.NI]A Console GRID LA Console GRID Leveraged Authentication and Key Agreement Mechanism for LTE/SAE
Rajakumar Arul, Gunasekaran Raja, Ali Kashif Bashir, Junaid Chaudry, Amjad Ali
http://arxiv.org/abs/1905.07607v1
• [cs.NI]Aeronautical Ad Hoc Networking for the Internet-Above-The-Clouds
Jiankang Zhang, Taihai Chen, Shida Zhong, Jingjing Wang, Wenbo Zhang, Xin Zuo, Robert G. Maunder, Lajos Hanzo
http://arxiv.org/abs/1905.07486v1
• [cs.PL]Verification of Threshold-Based Distributed Algorithms by Decomposition to Decidable Logics
Idan Berkovits, Marijana Lazic, Giuliano Losa, Oded Padon, Sharon Shoham
http://arxiv.org/abs/1905.07805v1
• [cs.RO]A Coordinated Search Strategy for Solitary Robots
Jordan F. Masakuna, Simukai W. Utete, Steve Kroon
http://arxiv.org/abs/1905.07434v1
• [cs.RO]A semantic-aided particle filter approach for AUV localization
Francesco Maurelli, Szymon Krupinski
http://arxiv.org/abs/1905.07470v1
• [cs.RO]Characterizing SLAM Benchmarks and Methods for the Robust Perception Age
Wenkai Ye, Yipu Zhao, Patricio A. Vela
http://arxiv.org/abs/1905.07808v1
• [cs.RO]Good Feature Selection for Least Squares Pose Optimization in VO/VSLAM
Yipu Zhao, Patricio A. Vela
http://arxiv.org/abs/1905.07807v1
• [cs.RO]Learning while Competing — 3D Modeling & Design
Kalind Karia, Rucmenya Bessariya, Krishna Lala, Kavi Arya
http://arxiv.org/abs/1905.07644v1
• [cs.RO]Low-latency Visual SLAM with Appearance-Enhanced Local Map Building
Yipu Zhao, Wenkai Ye, Patricio A. Vela
http://arxiv.org/abs/1905.07797v1
• [cs.RO]Object Rearrangement with Nested Nonprehensile Manipulation Actions
Changkyu Song, Abdeslam Boularias
http://arxiv.org/abs/1905.07505v1
• [cs.RO]Planning coordinated motions for tethered planar mobile robots
Xu Zhang, Quang-Cuong Pham
http://arxiv.org/abs/1905.07873v1
• [cs.RO]Positioning aiding using LiDAR in GPS signal loss scenarios
Szymon Krupinski, Francesco Maurelli
http://arxiv.org/abs/1905.07491v1
• [cs.RO]REPLAB: A Reproducible Low-Cost Arm Benchmark Platform for Robotic Learning
Brian Yang, Jesse Zhang, Vitchyr Pong, Sergey Levine, Dinesh Jayaraman
http://arxiv.org/abs/1905.07447v1
• [cs.RO]Reinforcement Learning without Ground-Truth State
Xingyu Lin, Harjatin Singh Baweja, David Held
http://arxiv.org/abs/1905.07866v1
• [cs.RO]SCALAR: Simultaneous Calibration of 2D Laser and Robot Kinematic Parameters Using Planarity and Distance Constraints
Teguh Santoso Lembono, Francisco Suárez-Ruiz, Quang-Cuong Pham
http://arxiv.org/abs/1905.07625v1
• [cs.SD]Dance Hit Song Prediction
Dorien herremans, David Martens, Kenneth Sörensen
http://arxiv.org/abs/1905.08076v1
• [cs.SE]Testing Deep Neural Network based Image Classifiers
Yuchi Tian, Ziyuan Zhong, Vicente Ordonez, Baishakhi Ray
http://arxiv.org/abs/1905.07831v1
• [cs.SI]Graph Mining Meets Crowdsourcing: Extracting Experts for Answer Aggregation
Yasushi Kawase, Yuko Kuroki, Atsushi Miyauchi
http://arxiv.org/abs/1905.08088v1
• [cs.SI]Online reactions to the 2017 ‘Unite the Right’ rally in Charlottesville: measuring polarization in Twitter networks using media followership
Joseph H. Tien, Marisa C. Eisenberg, Sarah T. Cherng, Mason A. Porter
http://arxiv.org/abs/1905.07755v1
• [cs.SI]Understanding the Radical Mind: Identifying Signals to Detect Extremist Content on Twitter
Mariam Nouh, Jason R. C. Nurse, Michael Goldsmith
http://arxiv.org/abs/1905.08067v1
• [cs.SY]Investigating Flight Envelope Variation Predictability of Impaired Aircraft using Least-Squares Regression Analysis
Ramin Norouzi, Amirreza Kosari, Mohammad Hossein Sabour
http://arxiv.org/abs/1905.07875v1
• [econ.EM]Conformal Prediction Interval Estimations with an Application to Day-Ahead and Intraday Power Markets
Christopher Kath, Florian Ziel
http://arxiv.org/abs/1905.07886v1
• [econ.EM]Nonparametric Instrumental Regressions with (Potentially Discrete) Instruments Independent of the Error Term
Samuele Centorrino, Frédérique Fève, Jean-Pierre Florens
http://arxiv.org/abs/1905.07812v1
• [eess.IV]An Objective Evaluation Metric for image fusion based on Del Operator
Ali A. Kiaei, Hassan Khotanlou, Paniz Kiaei, Yasin Bhrouzi, Mahdi Abbasi
http://arxiv.org/abs/1905.07709v1
• [eess.IV]Quantitative Error Prediction of Medical Image Registration using Regression Forests
Hessam Sokooti, Gorkem Saygili, Ben Glocker, Boudewijn P. F. Lelieveldt, Marius Staring
http://arxiv.org/abs/1905.07624v1
• [eess.SP]Transmitter Classification With Supervised Deep Learning
Cyrille Morin, Leonardo Cardoso, Jakob Hoydis, Jean-Marie Gorce, Thibaud Vial
http://arxiv.org/abs/1905.07923v1
• [math.FA]A note on variance bounds and location of eigenvalues
R. Sharma, A. Sharma, R. Saini
http://arxiv.org/abs/1905.07568v1
• [math.NA]Uniform bounds for invariant subspace perturbations
Anil Damle, Yuekai Sun
http://arxiv.org/abs/1905.07865v1
• [math.OC]A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization
Sulaiman A. Alghunaim, Kun Yuan, Ali H. Sayed
http://arxiv.org/abs/1905.07996v1
• [math.OC]Trajectory Optimization on Manifolds: A Theoretically-Guaranteed Embedded Sequential Convex Programming Approach
Riccardo Bonalli, Andrew Bylard, Abhishek Cauligi, Thomas Lew, Marco Pavone
http://arxiv.org/abs/1905.07654v1
• [math.PR]Mean-Field Langevin Dynamics and Energy Landscape of Neural Networks
Kaitong Hu, Zhenjie Ren, David Siska, Lukasz Szpruch
http://arxiv.org/abs/1905.07769v1
• [math.PR]On a Tail Bound for Root-Finding in Randomly Growing Trees
Sam Justice, N. D. Shyamalkumar
http://arxiv.org/abs/1905.07652v1
• [math.ST]A residual-based bootstrap for functional autoregressions
Jürgen Franke, Euna Gesare Nyarige
http://arxiv.org/abs/1905.07635v1
• [math.ST]Integrated conditional moment test and beyond: when the number of covariates is divergent
Falong Tan, Lixing Zhu
http://arxiv.org/abs/1905.08011v1
• [math.ST]Method comparison with repeated measurements - Passing-Bablok regression for grouped data with errors in both variables
Franz Baumdicker, Ulrich Hölker
http://arxiv.org/abs/1905.07649v1
• [math.ST]On approximation of the distribution for Pearson statistic
Nikolai Dokuchaev
http://arxiv.org/abs/1905.07881v1
• [math.ST]Second Order Expansions for Sample Median with Random Sample Size
Gerd Christoph, Vladimir V. Ulyanov, Vladimir E. Bening
http://arxiv.org/abs/1905.07765v1
• [math.ST]Teaching decision theory proof strategies using a crowdsourcing problem
Luis G. Esteves, Rafael Izbicki, Rafael B. Stern
http://arxiv.org/abs/1905.07670v1
• [physics.class-ph]Physics-informed transfer path analysis with parameter estimation using Gaussian processes
Christopher Albert
http://arxiv.org/abs/1905.07907v1
• [physics.comp-ph]Exploiting Parallelism on Shared Memory in the QED Particle-in-Cell Code PICADOR with Greedy Load Balancing
Iosif Meyerov, Sergei Bastrakov, Aleksei Bashinov, Evgeny Efimenko, Alexander Panov, Elena Panova, Igor Surmin, Valentin Volokitin, Arkady Gonoskov
http://arxiv.org/abs/1905.08217v1
• [physics.comp-ph]Leveraging Bayesian Analysis To Improve Accuracy of Approximate Models
Balasubramanya T. Nadiga, Chiyu Jiang, Daniel Livescu
http://arxiv.org/abs/1905.08227v1
• [physics.geo-ph]Artificial Neural Network Surrogate Modeling of Oil Reservoir: a Case Study
Oleg Sudakov, Dmitri Koroteev, Boris Belozerov, Evgeny Burnaev
http://arxiv.org/abs/1905.07859v1
• [physics.soc-ph]Diagnosing the performance of human mobility models at small spatial scales using volunteered geographic information
Chico Q. Camargo, Jonathan Bright, Scott A. Hale
http://arxiv.org/abs/1905.07964v1
• [physics.soc-ph]The configuration model for Barabasi-Albert networks
M. L. Bertotti, G. Modanese
http://arxiv.org/abs/1905.08093v1
• [q-bio.QM]Decoding the Rejuvenating Effects of Mechanical Loading on Skeletal Maturation using in Vivo Imaging and Deep Learning
Pouyan Asgharzadeh, Oliver Röhrle, Bettina M. Willie, Annette I. Birkhold
http://arxiv.org/abs/1905.08099v1
• [stat.AP]ACE of Space: Estimating Genetic Components of High-Dimensional Imaging Data
Benjamin B. Risk, Hongtu Zhu
http://arxiv.org/abs/1905.07502v1
• [stat.AP]On Changes of Global Wet-bulb Temperature and Snowfall Regimes
Sagar K. Tamang, Ardeshir M. Ebtehaj, Andreas F. Prein, Andrew J. Heymsfield
http://arxiv.org/abs/1905.07776v1
• [stat.AP]Optimizing Interim Analysis Timing for Bayesian Adaptive Commensurate Designs
Xiao Wu, Yi Xu, Bradley P. Carlin
http://arxiv.org/abs/1905.07456v1
• [stat.CO]LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations
Brian L. Trippe, Jonathan H. Huggins, Raj Agrawal, Tamara Broderick
http://arxiv.org/abs/1905.07499v1
• [stat.CO]Stratified sampling and resampling for approximate Bayesian computation
Umberto Picchini, Richard G. Everitt
http://arxiv.org/abs/1905.07976v1
• [stat.ME]Causal Inference for Multiple Non-Randomized Treatments using Fractional Factorial Designs
Nicole E. Pashley, Marie-Abele C. Bind
http://arxiv.org/abs/1905.07596v1
• [stat.ME]Estimating variances in time series linear regression models using empirical BLUPs and convex optimization
Martina Hančová, Gabriela Vozáriková, Andrej Gajdoš, Jozef Hanč
http://arxiv.org/abs/1905.07771v1
• [stat.ME]Factor Models for High-Dimensional Tensor Time Series
Rong Chen, Dan Yang, Cun-hui Zhang
http://arxiv.org/abs/1905.07530v1
• [stat.ME]Modeling of Missing Dynamical Systems: Deriving Parametric Models using a Nonparametric Framework
Shixiao W. Jiang, John Harlim
http://arxiv.org/abs/1905.08082v1
• [stat.ME]Non-Parametric Estimation of Spot Covariance Matrix with High-Frequency Data
Konul Mustafayeva, Weining Wang
http://arxiv.org/abs/1905.08122v1
• [stat.ME]On Selecting Stable Predictors in Time Series Models
Avleen S. Bijral
http://arxiv.org/abs/1905.07659v1
• [stat.ME]Semiparametric estimation for space-time max-stable processes: F -madogram-based estimation approach
Abdul-Fattah Abu-Awwad, Véronique Maume-Deschamps, Pierre Ribereau
http://arxiv.org/abs/1905.07912v1
• [stat.ME]Study designs for extending causal inferences from a randomized trial to a target population
Issa J. Dahabreh, Sebastien J-P. A. Haneuse, James M. Robins, Sarah E. Robertson, Ashley L. Buchanan, Elisabeth A. Stuart, Miguel A. Hernán
http://arxiv.org/abs/1905.07764v1
• [stat.ML]A Distributionally Robust Boosting Algorithm
Jose Blanchet, Yang Kang, Fan Zhang, Zhangyi Hu
http://arxiv.org/abs/1905.07845v1
• [stat.ML]An Online Stochastic Kernel Machine for Robust Signal Classification
Raghu G. Raj
http://arxiv.org/abs/1905.07686v1
• [stat.ML]Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees
Summer Devlin, Chandan Singh, W. James Murdoch, Bin Yu
http://arxiv.org/abs/1905.07631v1
• [stat.ML]Gradient Ascent for Active Exploration in Bandit Problems
Pierre Ménard
http://arxiv.org/abs/1905.08165v1
• [stat.ML]Gradient tree boosting with random output projections for multi-label classification and multi-output regression
Arnaud Joly, Louis Wehenkel, Pierre Geurts
http://arxiv.org/abs/1905.07558v1
• [stat.ML]Leveraging Semantic Embeddings for Safety-Critical Applications
Thomas Brunner, Frederik Diehl, Michael Truong Le, Alois Knoll
http://arxiv.org/abs/1905.07733v1
• [stat.ML]PAC-Bayes under potentially heavy tails
Matthew J. Holland
http://arxiv.org/abs/1905.07900v1
• [stat.ML]Practical Bayesian Optimization with Threshold-Guided Marginal Likelihood Maximization
Jungtaek Kim, Seungjin Choi
http://arxiv.org/abs/1905.07540v1
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