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.DC - 分布式、并行与集群计算 cs.DM - 离散数学 cs.DS - 数据结构与算法 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.MM - 多媒体 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.OC - 优化与控制 math.SP - 谱理论 math.ST - 统计理论 physics.bio-ph - 生物物理 q-bio.GN - 基因组学 q-bio.PE - 人口与发展 q-fin.PR - 证券定价 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cs.AI]Empowering Quality Diversity in Dungeon Design with Interactive Constrained MAP-Elites
• [cs.AI]General Video Game Rule Generation
• [cs.AI]Online Learning and Planning in Partially Observable Domains without Prior Knowledge
• [cs.AI]Polynomial-time Updates of Epistemic States in a Fragment of Probabilistic Epistemic Argumentation (Technical Report)
• [cs.AI]Search on the Replay Buffer: Bridging Planning and Reinforcement Learning
• [cs.CL]A Structured Learning Approach to Temporal Relation Extraction
• [cs.CL]A Systematic Comparison of English Noun Compound Representations
• [cs.CL]Adversarial Learning of Privacy-Preserving Text Representations for De-Identification of Medical Records
• [cs.CL]BiSET: Bi-directional Selective Encoding with Template for Abstractive Summarization
• [cs.CL]CogCompTime: A Tool for Understanding Time in Natural Language Text
• [cs.CL]Concept Discovery through Information Extraction in Restaurant Domain
• [cs.CL]Continual and Multi-Task Architecture Search
• [cs.CL]Explore, Propose, and Assemble: An Interpretable Model for Multi-Hop Reading Comprehension
• [cs.CL]Incremental Learning from Scratch for Task-Oriented Dialogue Systems
• [cs.CL]Joint Reasoning for Temporal and Causal Relations
• [cs.CL]Keeping Notes: Conditional Natural Language Generation with a Scratchpad Mechanism
• [cs.CL]Monotonic Infinite Lookback Attention for Simultaneous Machine Translation
• [cs.CL]PerspectroScope: A Window to the World of Diverse Perspectives
• [cs.CL]Probing Multilingual Sentence Representations With X-Probe
• [cs.CL]Putting words in context: LSTM language models and lexical ambiguity
• [cs.CL]Towards Geocoding Spatial Expressions
• [cs.CL]Unified Semantic Parsing with Weak Supervision
• [cs.CL]Unmasking Bias in News
• [cs.CL]Unsupervised Discovery of Gendered Language through Latent-Variable Modeling
• [cs.CL]Unsupervised Question Answering by Cloze Translation
• [cs.CR]Differential Imaging Forensics
• [cs.CR]Secure Federated Matrix Factorization
• [cs.CV]All-Weather Deep Outdoor Lighting Estimation
• [cs.CV]Boosting Few-Shot Visual Learning with Self-Supervision
• [cs.CV]CDPM: Convolutional Deformable Part Models for Person Re-identification
• [cs.CV]Compressed Sensing MRI via a Multi-scale Dilated Residual Convolution Network
• [cs.CV]Compressive Hyperspherical Energy Minimization
• [cs.CV]DeepSquare: Boosting the Learning Power of Deep Convolutional Neural Networks with Elementwise Square Operators
• [cs.CV]Different Approaches for Human Activity Recognition: A Survey
• [cs.CV]Edge-Direct Visual Odometry
• [cs.CV]Evaluation of Dataflow through layers of Deep Neural Networks in Classification and Regression Problems
• [cs.CV]Hand Orientation Estimation in Probability Density Form
• [cs.CV]Handwritten Text Segmentation via End-to-End Learning of Convolutional Neural Network
• [cs.CV]High Accuracy Classification of White Blood Cells using TSLDA Classifier and Covariance Features
• [cs.CV]Indoor image representation by high-level semantic features
• [cs.CV]Inferring 3D Shapes from Image Collections using Adversarial Networks
• [cs.CV]LAEO-Net: revisiting people Looking At Each Other in videos
• [cs.CV]LED2Net: Deep Illumination-aware Dehazing with Low-light and Detail Enhancement
• [cs.CV]NAS-FCOS: Fast Neural Architecture Search for Object Detection
• [cs.CV]Pay Attention to Convolution Filters: Towards Fast and Accurate Fine-Grained Transfer Learning
• [cs.CV]Pose from Shape: Deep Pose Estimation for Arbitrary 3D Objects
• [cs.CV]Presence-Only Geographical Priors for Fine-Grained Image Classification
• [cs.CV]Recognizing Manipulation Actions from State-Transformations
• [cs.CV]Recurrent U-Net for Resource-Constrained Segmentation
• [cs.CV]Semi-Supervised Exploration in Image Retrieval
• [cs.CV]Suppressing Model Overfitting for Image Super-Resolution Networks
• [cs.CV]Synthesizing Diverse Lung Nodules Wherever Massively: 3D Multi-Conditional GAN-based CT Image Augmentation for Object Detection
• [cs.CV]Tackling Partial Domain Adaptation with Self-Supervision
• [cs.CV]Task-Aware Deep Sampling for Feature Generation
• [cs.CV]Towards Real-Time Head Pose Estimation: Exploring Parameter-Reduced Residual Networks on In-the-wild Datasets
• [cs.CV]Vispi: Automatic Visual Perception and Interpretation of Chest X-rays
• [cs.CV]Visual Relationships as Functions: Enabling Few-Shot Scene Graph Prediction
• [cs.CV]Weakly-supervised Compositional FeatureAggregation for Few-shot Recognition
• [cs.DC]Application-Level Differential Checkpointing for HPC Applications with Dynamic Datasets
• [cs.DC]Checkpoint/restart approaches for a thread-based MPI runtime
• [cs.DC]Handel: Practical Multi-Signature Aggregation for Large Byzantine Committees
• [cs.DM]Relative Hausdorff Distance for Network Analysis
• [cs.DS]Sorted Top-k in Rounds
• [cs.HC]Toward Best Practices for Explainable B2B Machine Learning
• [cs.IR]A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications
• [cs.IR]From Fully Supervised to Zero Shot Settings for Twitter Hashtag Recommendation
• [cs.IR]Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification
• [cs.IR]Innovating HR Using an Expert System for Recruiting IT Specialists — ESRIT
• [cs.IR]Modeling the Past and Future Contexts for Session-based Recommendation
• [cs.IR]Real-time Attention Based Look-alike Model for Recommender System
• [cs.IR]Reinforcement Knowledge Graph Reasoning for Explainable Recommendation
• [cs.IT]Collaborative Broadcast in O(log log n) Rounds
• [cs.IT]Good Stabilizer Codes from Quasi-Cyclic Codes over $\mathbb{F}_4$ and $\mathbb{F}_9$
• [cs.IT]On Universal Codes for Integers: Wallace Tree, Elias Omega and Variations
• [cs.IT]Second-best Beam-Alignment via Bayesian Multi-Armed Bandits
• [cs.IT]Spectral Bounds for Quasi-Twisted Codes
• [cs.LG]A Closer Look at the Optimization Landscapes of Generative Adversarial Networks
• [cs.LG]A Model to Search for Synthesizable Molecules
• [cs.LG]A Stratified Approach to Robustness for Randomly Smoothed Classifiers
• [cs.LG]Adaptively Preconditioned Stochastic Gradient Langevin Dynamics
• [cs.LG]Artificial Intelligence Enabled Material Behavior Prediction
• [cs.LG]Associative Convolutional Layers
• [cs.LG]Coresets for Gaussian Mixture Models of Any Shape
• [cs.LG]DCEF: Deep Collaborative Encoder Framework for Unsupervised Clustering
• [cs.LG]Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning
• [cs.LG]Decoupling Gating from Linearity
• [cs.LG]Deep 2FBSDEs for Systems with Control Multiplicative Noise
• [cs.LG]Deep Learning for Spatio-Temporal Data Mining: A Survey
• [cs.LG]Deep Reinforcement Learning for Unmanned Aerial Vehicle-Assisted Vehicular Networks
• [cs.LG]Discrepancy, Coresets, and Sketches in Machine Learning
• [cs.LG]Does Learning Require Memorization? A Short Tale about a Long Tail
• [cs.LG]DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections
• [cs.LG]Dynamical Anatomy of NARMA10 Benchmark Task
• [cs.LG]Efficient Exploration via State Marginal Matching
• [cs.LG]Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks
• [cs.LG]Fast Task Inference with Variational Intrinsic Successor Features
• [cs.LG]GluonTS: Probabilistic Time Series Models in Python
• [cs.LG]Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations
• [cs.LG]Higher-Order Ranking and Link Prediction: From Closing Triangles to Closing Higher-Order Motifs
• [cs.LG]Improving Reproducible Deep Learning Workflows with DeepDIVA
• [cs.LG]Incremental Classifier Learning Based on PEDCC-Loss and Cosine Distance
• [cs.LG]Is Deep Learning an RG Flow?
• [cs.LG]Issues with post-hoc counterfactual explanations: a discussion
• [cs.LG]Macro-action Multi-timescale Dynamic Programming for Energy Management with Phase Change Materials
• [cs.LG]Manifold Graph with Learned Prototypes for Semi-Supervised Image Classification
• [cs.LG]Multiple instance learning with graph neural networks
• [cs.LG]Multitask Learning for Network Traffic Classification
• [cs.LG]Neural Variational Inference For Estimating Uncertainty in Knowledge Graph Embeddings
• [cs.LG]Non-Parametric Calibration for Classification
• [cs.LG]On regularization for a convolutional kernel in neural networks
• [cs.LG]Optimizing Pipelined Computation and Communication for Latency-Constrained Edge Learning
• [cs.LG]Parameterized Structured Pruning for Deep Neural Networks
• [cs.LG]Partial Or Complete, That’s The Question
• [cs.LG]Position-aware Graph Neural Networks
• [cs.LG]Power Gradient Descent
• [cs.LG]Regret Minimization for Reinforcement Learning by Evaluating the Optimal Bias Function
• [cs.LG]Reinforcement Learning for Integer Programming: Learning to Cut
• [cs.LG]Run-Time Efficient RNN Compression for Inference on Edge Devices
• [cs.LG]SPoC: Search-based Pseudocode to Code
• [cs.LG]Semi-flat minima and saddle points by embedding neural networks to overparameterization
• [cs.LG]Stability of Graph Scattering Transforms
• [cs.LG]Statistical guarantees for local graph clustering
• [cs.LG]Table-Based Neural Units: Fully Quantizing Networks for Multiply-Free Inference
• [cs.LG]Towards Inverse Reinforcement Learning for Limit Order Book Dynamics
• [cs.LG]Using Small Proxy Datasets to Accelerate Hyperparameter Search
• [cs.LG]Warping Resilient Time Series Embeddings
• [cs.LG]When to use parametric models in reinforcement learning?
• [cs.LG]Who Will Win It? An In-game Win Probability Model for Football
• [cs.MM]Stereoscopic Omnidirectional Image Quality Assessment Based on Predictive Coding Theory
• [cs.NI]Towards Big data processing in IoT: Path Planning and Resource Management of UAV Base Stations in Mobile-Edge Computing System
• [cs.RO]A Survey of Autonomous Driving: Common Practices and Emerging Technologies
• [cs.RO]Active Learning of Dynamics for Data-Driven Control Using Koopman Operators
• [cs.RO]Adaptive Navigation Scheme for Optimal Deep-Sea Localization Using Multimodal Perception Cues
• [cs.RO]Co-modelling of Agricultural Robotic Systems
• [cs.RO]DensePhysNet: Learning Dense Physical Object Representations via Multi-step Dynamic Interactions
• [cs.RO]Enhancing the Vertical Mobility of a Robot Hexapod Using Microspines
• [cs.RO]Identification of Motor Parameters on Coupled Joints
• [cs.RO]Kinematics of Spherical Robots Rolling Over 3D Terrains
• [cs.RO]Snake-Like Robots for Minimally Invasive, Single Port, and Intraluminal Surgeries
• [cs.RO]Transferrable Operative Difficulty Assessment in Robot-assisted Teleoperation: A Domain Adaptation Approach
• [cs.SE]Does BLEU Score Work for Code Migration?
• [cs.SI]A decentralized trust-aware collaborative filtering recommender system based on weighted items for social tagging systems
• [cs.SI]Optimizing city-scale traffic flows through modeling isolated observations of vehicle movements
• [cs.SI]Power-law Verification for Event Detection at Multi-spatial Scales from Geo-tagged Tweet Streams
• [cs.SI]Understanding Vulnerability of Communities in Complex Networks
• [cs.SI]Weighted, Bipartite, or Directed Stream Graphs for the Modeling of Temporal Networks
• [eess.IV]Joint 3D Localization and Classification of Space Debris using a Multispectral Rotating Point Spread Function
• [eess.IV]`Project & Excite’ Modules for Segmentation of Volumetric Medical Scans
• [eess.SP]Trip Table Estimation and Prediction for Dynamic Traffic Assignment Applications
• [eess.SY]Reinforcement-Learning-based Adaptive Optimal Control for Arbitrary Reference Tracking
• [math.OC]Critical Point Finding with Newton-MR by Analogy to Computing Square Roots
• [math.OC]Deep Forward-Backward SDEs for Min-max Control
• [math.OC]Global optimization using Sobol indices
• [math.SP]Spectral Ratio for Positive Matrices
• [math.ST]Knowledge Gradient for Selection with Covariates: Consistency and Computation
• [math.ST]Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification
• [math.ST]Robust subgaussian estimation of a mean vector in nearly linear time
• [math.ST]Stein’s method and the distribution of the product of zero mean correlated normal random variables
• [math.ST]Structure-adaptive manifold estimation
• [physics.bio-ph]High-resolution Markov state models for the dynamics of Trp-cage miniprotein constructed over slow folding modes identified by state-free reversible VAMPnets
• [q-bio.GN]Exploring Bayesian approaches to eQTL mapping through probabilistic programming
• [q-bio.PE]Markov-modulated continuous-time Markov chains to identify site- and branch-specific evolutionary variation
• [q-bio.PE]Relaxed random walks at scale
• [q-fin.PR]Deep Smoothing of the Implied Volatility Surface
• [stat.AP]A Bayesian Hierarchical Model for Evaluating Forensic Footwear Evidence
• [stat.AP]Applying economic measures to lapse risk management with machine learning approaches
• [stat.AP]Assessing the effects of exposure to sulfuric acid aerosol on respiratory function in adults
• [stat.AP]Estimating the Number of Fatal Victims of the Peruvian Internal Armed Conflict, 1980-2000: an application of modern multi-list Capture-Recapture techniques
• [stat.AP]Technical Preprint: Rationale and Design of a Planned Observational Study to Evaluate the Impact of Hydrocodone Rescheduling on Opioid Prescribing After Surgery
• [stat.ME]A mnotone data augmentation algorithm for longitudinal data analysis via multivariate skew-t, skew-normal or t distributions
• [stat.ME]Distribution-Free Multisample Test Based on Optimal Matching with Applications to Single Cell Genomics
• [stat.ME]Functional Singular Spectrum Analysis
• [stat.ME]Learning High-Dimensional Gaussian Graphical Models under Total Positivity without Tuning Parameters
• [stat.ME]Model Testing for Generalized Scalar-on-Function Linear Models
• [stat.ME]Structure learning of Bayesian networks involving cyclic structures
• [stat.ME]The EAS approach for graphical selection consistency in vector autoregression models
• [stat.ML]ADASS: Adaptive Sample Selection for Training Acceleration
• [stat.ML]Attention-based Multi-Input Deep Learning Architecture for Biological Activity Prediction: An Application in EGFR Inhibitors
• [stat.ML]Bootstrapping Upper Confidence Bound
• [stat.ML]Communication-Efficient Accurate Statistical Estimation
• [stat.ML]Improving Importance Weighted Auto-Encoders with Annealed Importance Sampling
• [stat.ML]Medium-Term Load Forecasting Using Support Vector Regression, Feature Selection, and Symbiotic Organism Search Optimization
• [stat.ML]On the Universality of Noiseless Linear Estimation with Respect to the Measurement Matrix
• [stat.ML]Stable Rank Normalization for Improved Generalization in Neural Networks and GANs
• [stat.ML]Task Agnostic Continual Learning via Meta Learning
• [stat.ML]The Impact of Regularization on High-dimensional Logistic Regression
·····································
• [cs.AI]Empowering Quality Diversity in Dungeon Design with Interactive Constrained MAP-Elites
Alberto Alvarez, Steve Dahlskog, Jose Font, Julian Togelius
http://arxiv.org/abs/1906.05175v1
• [cs.AI]General Video Game Rule Generation
Ahmed Khalifa, Michael Cerny Green, Diego Perez-Liebana, Julian Togelius
http://arxiv.org/abs/1906.05160v1
• [cs.AI]Online Learning and Planning in Partially Observable Domains without Prior Knowledge
Yunlong Liu, Jianyang Zheng
http://arxiv.org/abs/1906.05130v1
• [cs.AI]Polynomial-time Updates of Epistemic States in a Fragment of Probabilistic Epistemic Argumentation (Technical Report)
Nico Potyka, Sylwia Polberg, Anthony Hunter
http://arxiv.org/abs/1906.05066v1
• [cs.AI]Search on the Replay Buffer: Bridging Planning and Reinforcement Learning
Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
http://arxiv.org/abs/1906.05253v1
• [cs.CL]A Structured Learning Approach to Temporal Relation Extraction
Qiang Ning, Zhili Feng, Dan Roth
http://arxiv.org/abs/1906.04943v1
• [cs.CL]A Systematic Comparison of English Noun Compound Representations
Vered Shwartz
http://arxiv.org/abs/1906.04772v1
• [cs.CL]Adversarial Learning of Privacy-Preserving Text Representations for De-Identification of Medical Records
Max Friedrich, Arne Köhn, Gregor Wiedemann, Chris Biemann
http://arxiv.org/abs/1906.05000v1
• [cs.CL]BiSET: Bi-directional Selective Encoding with Template for Abstractive Summarization
Kai Wang, Xiaojun Quan, Rui Wang
http://arxiv.org/abs/1906.05012v1
• [cs.CL]CogCompTime: A Tool for Understanding Time in Natural Language Text
Qiang Ning, Ben Zhou, Zhili Feng, Haoruo Peng, Dan Roth
http://arxiv.org/abs/1906.04940v1
• [cs.CL]Concept Discovery through Information Extraction in Restaurant Domain
Nadeesha Pathirana, Sandaru Seneviratne, Rangika Samarawickrama, Shane Wolff, Charith Chitraranjan, Uthayasanker Thayasivam, Tharindu Ranasinghe
http://arxiv.org/abs/1906.05039v1
• [cs.CL]Continual and Multi-Task Architecture Search
Ramakanth Pasunuru, Mohit Bansal
http://arxiv.org/abs/1906.05226v1
• [cs.CL]Explore, Propose, and Assemble: An Interpretable Model for Multi-Hop Reading Comprehension
Yichen Jiang, Nitish Joshi, Yen-Chun Chen, Mohit Bansal
http://arxiv.org/abs/1906.05210v1
• [cs.CL]Incremental Learning from Scratch for Task-Oriented Dialogue Systems
Weikang Wang, Jiajun Zhang, Qian Li, Mei-Yuh Hwang, Chengqing Zong, Zhifei Li
http://arxiv.org/abs/1906.04991v1
• [cs.CL]Joint Reasoning for Temporal and Causal Relations
Qiang Ning, Zhili Feng, Hao Wu, Dan Roth
http://arxiv.org/abs/1906.04941v1
• [cs.CL]Keeping Notes: Conditional Natural Language Generation with a Scratchpad Mechanism
Ryan Y. Benmalek, Madian Khabsa, Suma Desu, Claire Cardie, Michele Banko
http://arxiv.org/abs/1906.05275v1
• [cs.CL]Monotonic Infinite Lookback Attention for Simultaneous Machine Translation
Naveen Arivazhagan, Colin Cherry, Wolfgang Macherey, Chung-Cheng Chiu, Semih Yavuz, Ruoming Pang, Wei Li, Colin Raffel
http://arxiv.org/abs/1906.05218v1
• [cs.CL]PerspectroScope: A Window to the World of Diverse Perspectives
Sihao Chen, Daniel Khashabi, Chris Callison-Burch, Dan Roth
http://arxiv.org/abs/1906.04761v1
• [cs.CL]Probing Multilingual Sentence Representations With X-Probe
Vinit Ravishankar, Lilja Øvrelid, Erik Velldal
http://arxiv.org/abs/1906.05061v1
• [cs.CL]Putting words in context: LSTM language models and lexical ambiguity
Laura Aina, Kristina Gulordava, Gemma Boleda
http://arxiv.org/abs/1906.05149v1
• [cs.CL]Towards Geocoding Spatial Expressions
Hussein S. Al-Olimat, Valerie L. Shalin, Krishnaprasad Thirunarayan, Joy Prakash Sain
http://arxiv.org/abs/1906.04960v1
• [cs.CL]Unified Semantic Parsing with Weak Supervision
Priyanka Agrawal, Parag Jain, Ayushi Dalmia, Abhishek Bansal, Ashish Mittal, Karthik Sankaranarayanan
http://arxiv.org/abs/1906.05062v1
• [cs.CL]Unmasking Bias in News
Javier Sánchez-Junquera, Paolo Rosso, Manuel Montes-y-Gómez, Simone Paolo Ponzetto
http://arxiv.org/abs/1906.04836v1
• [cs.CL]Unsupervised Discovery of Gendered Language through Latent-Variable Modeling
Alexander Hoyle, Wolf-Sonkin, Hanna Wallach, Isabelle Augenstein, Ryan Cotterell
http://arxiv.org/abs/1906.04760v1
• [cs.CL]Unsupervised Question Answering by Cloze Translation
Patrick Lewis, Ludovic Denoyer, Sebastian Riedel
http://arxiv.org/abs/1906.04980v1
• [cs.CR]Differential Imaging Forensics
Aurélien Bourquard, Jeff Yan
http://arxiv.org/abs/1906.05268v1
• [cs.CR]Secure Federated Matrix Factorization
Di Chai, Leye Wang, Kai Chen, Qiang Yang
http://arxiv.org/abs/1906.05108v1
• [cs.CV]All-Weather Deep Outdoor Lighting Estimation
Jinsong Zhang, Kalyan Sunkavalli, Yannick Hold-Geoffroy, Sunil Hadap, Jonathan Eisenmann, Jean-François Lalonde
http://arxiv.org/abs/1906.04909v1
• [cs.CV]Boosting Few-Shot Visual Learning with Self-Supervision
Spyros Gidaris, Andrei Bursuc, Nikos Komodakis, Patrick Pérez, Matthieu Cord
http://arxiv.org/abs/1906.05186v1
• [cs.CV]CDPM: Convolutional Deformable Part Models for Person Re-identification
Kan Wang, Changxing Ding, Stephen J. Maybank, Dacheng Tao
http://arxiv.org/abs/1906.04976v1
• [cs.CV]Compressed Sensing MRI via a Multi-scale Dilated Residual Convolution Network
Yuxiang Dai, Peixian Zhuang
http://arxiv.org/abs/1906.05251v1
• [cs.CV]Compressive Hyperspherical Energy Minimization
Rongmei Lin, Weiyang Liu, Zhen Liu, Chen Feng, Zhiding Yu, James M. Rehg, Li Xiong, Le Song
http://arxiv.org/abs/1906.04892v1
• [cs.CV]DeepSquare: Boosting the Learning Power of Deep Convolutional Neural Networks with Elementwise Square Operators
Sheng Chen, Xu Wang, Chao Chen, Yifan Lu, Xijin Zhang, Linfu Wen
http://arxiv.org/abs/1906.04979v1
• [cs.CV]Different Approaches for Human Activity Recognition: A Survey
Zawar Hussain, Michael Sheng, Wei Emma Zhang
http://arxiv.org/abs/1906.05074v1
• [cs.CV]Edge-Direct Visual Odometry
Kevin Christensen, Martial Hebert
http://arxiv.org/abs/1906.04838v1
• [cs.CV]Evaluation of Dataflow through layers of Deep Neural Networks in Classification and Regression Problems
Ahmad Kalhor, Mohsen Saffar, Melika Kheirieh, Somayyeh Hoseinipoor, Babak N. Araabi
http://arxiv.org/abs/1906.05156v1
• [cs.CV]Hand Orientation Estimation in Probability Density Form
Kazuaki Kondo, Daisuke Deguchi, Atsushi Shimada
http://arxiv.org/abs/1906.04952v1
• [cs.CV]Handwritten Text Segmentation via End-to-End Learning of Convolutional Neural Network
Junho Jo, Hyung Il Koo, Jae Woong Soh, Nam Ik Cho
http://arxiv.org/abs/1906.05229v1
• [cs.CV]High Accuracy Classification of White Blood Cells using TSLDA Classifier and Covariance Features
Hamed Talebi, Amin Ranjbar, Alireza Davoudi, Hamed Gholami, Mohammad Bagher Menhaj
http://arxiv.org/abs/1906.05131v1
• [cs.CV]Indoor image representation by high-level semantic features
Chiranjibi Sitaula, Yong Xiang, Yushu Zhang, Xuequan Lu, Sunil Aryal
http://arxiv.org/abs/1906.04987v1
• [cs.CV]Inferring 3D Shapes from Image Collections using Adversarial Networks
Matheus Gadelha, Aartika Rai, Subhransu Maji, Rui Wang
http://arxiv.org/abs/1906.04910v1
• [cs.CV]LAEO-Net: revisiting people Looking At Each Other in videos
Manuel J. Marin-Jimenez, Vicky Kalogeiton, Pablo Medina-Suarez, Andrew Zisserman
http://arxiv.org/abs/1906.05261v1
• [cs.CV]LED2Net: Deep Illumination-aware Dehazing with Low-light and Detail Enhancement
Guisik Kim, Junseok Kwon
http://arxiv.org/abs/1906.05119v1
• [cs.CV]NAS-FCOS: Fast Neural Architecture Search for Object Detection
Ning Wang, Yang Gao, Hao Chen, Peng Wang, Zhi Tian, Chunhua Shen
http://arxiv.org/abs/1906.04423v2
• [cs.CV]Pay Attention to Convolution Filters: Towards Fast and Accurate Fine-Grained Transfer Learning
Xiangxi Mo, Ruizhe Cheng, Tianyi Fang
http://arxiv.org/abs/1906.04950v1
• [cs.CV]Pose from Shape: Deep Pose Estimation for Arbitrary 3D Objects
Yang Xiao, Xuchong Qiu, Pierre-Alain Langlois, Mathieu Aubry, Renaud Marlet
http://arxiv.org/abs/1906.05105v1
• [cs.CV]Presence-Only Geographical Priors for Fine-Grained Image Classification
Oisin Mac Aodha, Elijah Cole, Pietro Perona
http://arxiv.org/abs/1906.05272v1
• [cs.CV]Recognizing Manipulation Actions from State-Transformations
Nachwa Aboubakr, James L. Crowley, Remi Ronfard
http://arxiv.org/abs/1906.05147v1
• [cs.CV]Recurrent U-Net for Resource-Constrained Segmentation
Wei Wang, Kaicheng Yu, Joachim Hugonot, Pascal Fua, Mathieu Salzmann
http://arxiv.org/abs/1906.04913v1
• [cs.CV]Semi-Supervised Exploration in Image Retrieval
Cheng Chang, Himanshu Rai, Satya Krishna Gorti, Junwei Ma, Chundi Liu, Guangwei Yu, Maksims Volkovs
http://arxiv.org/abs/1906.04944v1
• [cs.CV]Suppressing Model Overfitting for Image Super-Resolution Networks
Ruicheng Feng, Jinjin Gu, Yu Qiao, Chao Dong
http://arxiv.org/abs/1906.04809v1
• [cs.CV]Synthesizing Diverse Lung Nodules Wherever Massively: 3D Multi-Conditional GAN-based CT Image Augmentation for Object Detection
Changhee Han, Yoshiro Kitamura, Akira Kudo, Akimichi Ichinose, Leonardo Rundo, Yujiro Furukawa, Kazuki Umemoto, Hideki Nakayama, Yuanzhong Li
http://arxiv.org/abs/1906.04962v1
• [cs.CV]Tackling Partial Domain Adaptation with Self-Supervision
Silvia Bucci, Antonio D’Innocente, Tatiana Tommasi
http://arxiv.org/abs/1906.05199v1
• [cs.CV]Task-Aware Deep Sampling for Feature Generation
Xin Wang, Fisher Yu, Trevor Darrell, Joseph E. Gonzalez
http://arxiv.org/abs/1906.04854v1
• [cs.CV]Towards Real-Time Head Pose Estimation: Exploring Parameter-Reduced Residual Networks on In-the-wild Datasets
Ines Rieger, Thomas Hauenstein, Sebastian Hettenkofer, Jens-Uwe Garbas
http://arxiv.org/abs/1906.05203v1
• [cs.CV]Vispi: Automatic Visual Perception and Interpretation of Chest X-rays
Xin Li, Rui Cao, Dongxiao Zhu
http://arxiv.org/abs/1906.05190v1
• [cs.CV]Visual Relationships as Functions: Enabling Few-Shot Scene Graph Prediction
Apoorva Dornadula, Austin Narcomey, Ranjay Krishna, Michael Bernstein, Li Fei-Fei
http://arxiv.org/abs/1906.04876v1
• [cs.CV]Weakly-supervised Compositional FeatureAggregation for Few-shot Recognition
Ping Hu, Ximeng Sun, Kate Saenko, Stan Sclaroff
http://arxiv.org/abs/1906.04833v1
• [cs.DC]Application-Level Differential Checkpointing for HPC Applications with Dynamic Datasets
Kai Keller, Leonardo Bautista Gomez
http://arxiv.org/abs/1906.05038v1
• [cs.DC]Checkpoint/restart approaches for a thread-based MPI runtime
Julien Adam, Maxime Kermarquer, Jean-Baptiste Besnard, Leonardo Bautista-Gomez, Marc Perache, Patrick Carribault, Julien Jaeger, Allen D. Malony, Sameer Shende
http://arxiv.org/abs/1906.05020v1
• [cs.DC]Handel: Practical Multi-Signature Aggregation for Large Byzantine Committees
Olivier Bégassat, Blazej Kolad, Nicolas Gailly, Nicolas Liochon
http://arxiv.org/abs/1906.05132v1
• [cs.DM]Relative Hausdorff Distance for Network Analysis
Sinan G. Aksoy, Kathleen E. Nowak, Emilie Purvine, Stephen J. Young
http://arxiv.org/abs/1906.04936v1
• [cs.DS]Sorted Top-k in Rounds
Mark Braverman, Jieming Mao, Yuval Peres
http://arxiv.org/abs/1906.05208v1
• [cs.HC]Toward Best Practices for Explainable B2B Machine Learning
Kit Kuksenok
http://arxiv.org/abs/1906.04837v1
• [cs.IR]A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications
Finn Kuusisto, John Steill, Zhaobin Kuang, James Thomson, David Page, Ron Stewart
http://arxiv.org/abs/1906.05255v1
• [cs.IR]From Fully Supervised to Zero Shot Settings for Twitter Hashtag Recommendation
Abhay Kumar, Nishant Jain, Suraj Tripathi, Chirag Singh
http://arxiv.org/abs/1906.04914v1
• [cs.IR]Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification
Hao Peng, Jianxin Li, Qiran Gong, Senzhang Wang, Lifang He, Bo Li, Lihong Wang, Philip S. Yu
http://arxiv.org/abs/1906.04898v1
• [cs.IR]Innovating HR Using an Expert System for Recruiting IT Specialists — ESRIT
Ciprian-Octavian Truică, Adriana Barnoschi
http://arxiv.org/abs/1906.04915v1
• [cs.IR]Modeling the Past and Future Contexts for Session-based Recommendation
Yuan Fajie, He Xiangnan, Guo Guibing, Xu Zhezhao, Xiong Jian, He Xiuqiang
http://arxiv.org/abs/1906.04473v2
• [cs.IR]Real-time Attention Based Look-alike Model for Recommender System
Yudan Liu, Kaikai Ge, Xu Zhang, Leyu Lin
http://arxiv.org/abs/1906.05022v1
• [cs.IR]Reinforcement Knowledge Graph Reasoning for Explainable Recommendation
Yikun Xian, Zuohui Fu, S. Muthukrishnan, Gerard de Melo, Yongfeng Zhang
http://arxiv.org/abs/1906.05237v1
• [cs.IT]Collaborative Broadcast in O(log log n) Rounds
Christian Schindelhauer, Aditya Oak, Thomas Janson
http://arxiv.org/abs/1906.05153v1
• [cs.IT]Good Stabilizer Codes from Quasi-Cyclic Codes over $\mathbb{F}_4$ and $\mathbb{F}_9$
Martianus Frederic Ezerman, San Ling, Buket Özkaya, Patrick Solé
http://arxiv.org/abs/1906.04964v1
• [cs.IT]On Universal Codes for Integers: Wallace Tree, Elias Omega and Variations
Lloyd Allison, Arun Konagurthu, Daniel Schmidt
http://arxiv.org/abs/1906.05004v1
• [cs.IT]Second-best Beam-Alignment via Bayesian Multi-Armed Bandits
Muddassar Hussain, Nicolo Michelusi
http://arxiv.org/abs/1906.04782v1
• [cs.IT]Spectral Bounds for Quasi-Twisted Codes
Martianus Frederic Ezerman, San Ling, Buket Özkaya, Jareena Tharnnukhroh
http://arxiv.org/abs/1906.04967v1
• [cs.LG]A Closer Look at the Optimization Landscapes of Generative Adversarial Networks
Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien
http://arxiv.org/abs/1906.04848v1
• [cs.LG]A Model to Search for Synthesizable Molecules
John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato
http://arxiv.org/abs/1906.05221v1
• [cs.LG]A Stratified Approach to Robustness for Randomly Smoothed Classifiers
Guang-He Lee, Yang Yuan, Shiyu Chang, Tommi S. Jaakkola
http://arxiv.org/abs/1906.04948v1
• [cs.LG]Adaptively Preconditioned Stochastic Gradient Langevin Dynamics
Chandrasekaran Anirudh Bhardwaj
http://arxiv.org/abs/1906.04324v2
• [cs.LG]Artificial Intelligence Enabled Material Behavior Prediction
Timothy Hanlon, Johan Reimann, Monica A. Soare, Anjali Singhal, James Grande, Marc Edgar, Kareem S. Aggour, Joseph Vinciquerra
http://arxiv.org/abs/1906.05270v1
• [cs.LG]Associative Convolutional Layers
Hamed Omidvar, Vahideh Akhlaghi, Massimo Franceschetti, Rajesh K. Gupta
http://arxiv.org/abs/1906.04309v2
• [cs.LG]Coresets for Gaussian Mixture Models of Any Shape
Dan Feldman, Zahi Kfir, Xuan Wu
http://arxiv.org/abs/1906.04895v1
• [cs.LG]DCEF: Deep Collaborative Encoder Framework for Unsupervised Clustering
Jielei Chu, Hongjun Wang, Jing Liu, Zeng Yu, Tianrui Li
http://arxiv.org/abs/1906.05173v1
• [cs.LG]Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning
Georgios Papoudakis, Filippos Christianos, Arrasy Rahman, Stefano V. Albrecht
http://arxiv.org/abs/1906.04737v1
• [cs.LG]Decoupling Gating from Linearity
Jonathan Fiat, Eran Malach, Shai Shalev-Shwartz
http://arxiv.org/abs/1906.05032v1
• [cs.LG]Deep 2FBSDEs for Systems with Control Multiplicative Noise
Ziyi Wang, Marcus A. Pereira, Evangelos A. Theodorou
http://arxiv.org/abs/1906.04762v1
• [cs.LG]Deep Learning for Spatio-Temporal Data Mining: A Survey
Senzhang Wang, Jiannong Cao, Philip S. Yu
http://arxiv.org/abs/1906.04928v1
• [cs.LG]Deep Reinforcement Learning for Unmanned Aerial Vehicle-Assisted Vehicular Networks
Ming Zhu, Xiao-Yang Liu, Xiaodong Wang
http://arxiv.org/abs/1906.05015v1
• [cs.LG]Discrepancy, Coresets, and Sketches in Machine Learning
Zohar Karnin, Edo Liberty
http://arxiv.org/abs/1906.04845v1
• [cs.LG]Does Learning Require Memorization? A Short Tale about a Long Tail
Vitaly Feldman
http://arxiv.org/abs/1906.05271v1
• [cs.LG]DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections
Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li
http://arxiv.org/abs/1906.04733v1
• [cs.LG]Dynamical Anatomy of NARMA10 Benchmark Task
Tomoyuki Kubota, Kohei Nakajima, Hirokazu Takahashi
http://arxiv.org/abs/1906.04608v2
• [cs.LG]Efficient Exploration via State Marginal Matching
Lisa Lee, Benjamin Eysenbach, Emilio Parisotto, Eric Xing, Sergey Levine, Ruslan Salakhutdinov
http://arxiv.org/abs/1906.05274v1
• [cs.LG]Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks
Mahyar Fazlyab, Alexander Robey, Hamed Hassani, Manfred Morari, George J. Pappas
http://arxiv.org/abs/1906.04893v1
• [cs.LG]Fast Task Inference with Variational Intrinsic Successor Features
Steven Hansen, Will Dabney, Andre Barreto, Tom Van de Wiele, David Warde-Farley, Volodymyr Mnih
http://arxiv.org/abs/1906.05030v1
• [cs.LG]GluonTS: Probabilistic Time Series Models in Python
Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Danielle C. Maddix, Syama Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner Türkmen, Yuyang Wang
http://arxiv.org/abs/1906.05264v1
• [cs.LG]Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations
Xiang Yue, Zhen Wang, Jingong Huang, Srinivasan Parthasarathy, Soheil Moosavinasab, Yungui Huang, Simon M. Lin, Wen Zhang, Ping Zhang, Huan Sun
http://arxiv.org/abs/1906.05017v1
• [cs.LG]Higher-Order Ranking and Link Prediction: From Closing Triangles to Closing Higher-Order Motifs
Ryan A. Rossi, Anup Rao, Sungchul Kim, Eunyee Koh, Nesreen K. Ahmed, Gang Wu
http://arxiv.org/abs/1906.05059v1
• [cs.LG]Improving Reproducible Deep Learning Workflows with DeepDIVA
Michele Alberti, Vinaychandran Pondenkandath, Lars Vögtlin, Marcel Würsch, Rolf Ingold, Marcus Liwicki
http://arxiv.org/abs/1906.04736v1
• [cs.LG]Incremental Classifier Learning Based on PEDCC-Loss and Cosine Distance
Qiuyu Zhu, Zikuang He, Xin Ye
http://arxiv.org/abs/1906.04734v1
• [cs.LG]Is Deep Learning an RG Flow?
Ellen de Mello Koch, Robert de Mello Koch, Ling Cheng
http://arxiv.org/abs/1906.05212v1
• [cs.LG]Issues with post-hoc counterfactual explanations: a discussion
Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Marcin Detyniecki
http://arxiv.org/abs/1906.04774v1
• [cs.LG]Macro-action Multi-timescale Dynamic Programming for Energy Management with Phase Change Materials
Zahra Rahimpour, Gregor Verbic, Archie C. Chapman
http://arxiv.org/abs/1906.05200v1
• [cs.LG]Manifold Graph with Learned Prototypes for Semi-Supervised Image Classification
Chia-Wen Kuo, Chih-Yao Ma, Jia-Bin Huang, Zsolt Kira
http://arxiv.org/abs/1906.05202v1
• [cs.LG]Multiple instance learning with graph neural networks
Ming Tu, Jing Huang, Xiaodong He, Bowen Zhou
http://arxiv.org/abs/1906.04881v1
• [cs.LG]Multitask Learning for Network Traffic Classification
Shahbaz Rezaei, Xin Liu
http://arxiv.org/abs/1906.05248v1
• [cs.LG]Neural Variational Inference For Estimating Uncertainty in Knowledge Graph Embeddings
Alexander I. Cowen-Rivers, Pasquale Minervini, Tim Rocktaschel, Matko Bovsnjak, Sebastian Riedel, Jun Wang
http://arxiv.org/abs/1906.04985v1
• [cs.LG]Non-Parametric Calibration for Classification
Jonathan Wenger, Hedvig Kjellström, Rudolph Triebel
http://arxiv.org/abs/1906.04933v1
• [cs.LG]On regularization for a convolutional kernel in neural networks
Peichang Guo, Qiang Ye
http://arxiv.org/abs/1906.04866v1
• [cs.LG]Optimizing Pipelined Computation and Communication for Latency-Constrained Edge Learning
Nicolas Skatchkovsky, Osvaldo Simeone
http://arxiv.org/abs/1906.04488v2
• [cs.LG]Parameterized Structured Pruning for Deep Neural Networks
Guenther Schindler, Wolfgang Roth, Franz Pernkopf, Holger Froening
http://arxiv.org/abs/1906.05180v1
• [cs.LG]Partial Or Complete, That’s The Question
Qiang Ning, Hangfeng He, Chuchu Fan, Dan Roth
http://arxiv.org/abs/1906.04937v1
• [cs.LG]Position-aware Graph Neural Networks
Jiaxuan You, Rex Ying, Jure Leskovec
http://arxiv.org/abs/1906.04817v1
• [cs.LG]Power Gradient Descent
Marco Baiesi
http://arxiv.org/abs/1906.04787v1
• [cs.LG]Regret Minimization for Reinforcement Learning by Evaluating the Optimal Bias Function
Zihan Zhang, Xiangyang Ji
http://arxiv.org/abs/1906.05110v1
• [cs.LG]Reinforcement Learning for Integer Programming: Learning to Cut
Yunhao Tang, Shipra Agrawal, Yuri Faenza
http://arxiv.org/abs/1906.04859v1
• [cs.LG]Run-Time Efficient RNN Compression for Inference on Edge Devices
Urmish Thakker, Jesse Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina
http://arxiv.org/abs/1906.04886v1
• [cs.LG]SPoC: Search-based Pseudocode to Code
Sumith Kulal, Panupong Pasupat, Kartik Chandra, Mina Lee, Oded Padon, Alex Aiken, Percy Liang
http://arxiv.org/abs/1906.04908v1
• [cs.LG]Semi-flat minima and saddle points by embedding neural networks to overparameterization
Kenji Fukumizu, Shoichiro Yamaguch, Yoh-ichi Mototake, Mirai Tanaka
http://arxiv.org/abs/1906.04868v1
• [cs.LG]Stability of Graph Scattering Transforms
Fernando Gama, Joan Bruna, Alejandro Ribeiro
http://arxiv.org/abs/1906.04784v1
• [cs.LG]Statistical guarantees for local graph clustering
Wooseok Ha, Kimon Fountoulakis, Michael W. Mahoney
http://arxiv.org/abs/1906.04863v1
• [cs.LG]Table-Based Neural Units: Fully Quantizing Networks for Multiply-Free Inference
Michele Covell, David Marwood, Shumeet Baluja, Nick Johnston
http://arxiv.org/abs/1906.04798v1
• [cs.LG]Towards Inverse Reinforcement Learning for Limit Order Book Dynamics
Jacobo Roa-Vicens, Cyrine Chtourou, Angelos Filos, Francisco Rullan, Yarin Gal, Ricardo Silva
http://arxiv.org/abs/1906.04813v1
• [cs.LG]Using Small Proxy Datasets to Accelerate Hyperparameter Search
Sam Shleifer, Eric Prokop
http://arxiv.org/abs/1906.04887v1
• [cs.LG]Warping Resilient Time Series Embeddings
Anish Mathew, Deepak P, Sahely Bhadra
http://arxiv.org/abs/1906.05205v1
• [cs.LG]When to use parametric models in reinforcement learning?
Hado van Hasselt, Matteo Hessel, John Aslanides
http://arxiv.org/abs/1906.05243v1
• [cs.LG]Who Will Win It? An In-game Win Probability Model for Football
Pieter Robberechts, Jan Van Haaren, Jesse Davis
http://arxiv.org/abs/1906.05029v1
• [cs.MM]Stereoscopic Omnidirectional Image Quality Assessment Based on Predictive Coding Theory
Zhibo Chen, Jiahua Xu, Chaoyi Lin, Wei Zhou
http://arxiv.org/abs/1906.05165v1
• [cs.NI]Towards Big data processing in IoT: Path Planning and Resource Management of UAV Base Stations in Mobile-Edge Computing System
Shuo Wan, Jiaxun Lu, Pingyi Fan, Khaled B. Letaief
http://arxiv.org/abs/1906.05023v1
• [cs.RO]A Survey of Autonomous Driving: Common Practices and Emerging Technologies
Ekim Yurtsever, Jacob Lambert, Alexander Carballo, Kazuya Takeda
http://arxiv.org/abs/1906.05113v1
• [cs.RO]Active Learning of Dynamics for Data-Driven Control Using Koopman Operators
Ian Abraham, Todd D. Murphey
http://arxiv.org/abs/1906.05194v1
• [cs.RO]Adaptive Navigation Scheme for Optimal Deep-Sea Localization Using Multimodal Perception Cues
Arturo Gomez Chavez, Qingwen Xu, Christian A. Mueller, Sören Schwertfeger, Andreas Birk
http://arxiv.org/abs/1906.04888v1
• [cs.RO]Co-modelling of Agricultural Robotic Systems
Martin Peter Christiansen
http://arxiv.org/abs/1906.05111v1
• [cs.RO]DensePhysNet: Learning Dense Physical Object Representations via Multi-step Dynamic Interactions
Zhenjia Xu, Jiajun Wu, Andy Zeng, Joshua B. Tenenbaum, Shuran Song
http://arxiv.org/abs/1906.03853v2
• [cs.RO]Enhancing the Vertical Mobility of a Robot Hexapod Using Microspines
Matt Martone, Catherine Pavlov, Adam Zeloof, Vivaan Bahl
http://arxiv.org/abs/1906.04811v1
• [cs.RO]Identification of Motor Parameters on Coupled Joints
Nuno Guedelha, Silvio Traversaro, Daniele Pucci
http://arxiv.org/abs/1906.05070v1
• [cs.RO]Kinematics of Spherical Robots Rolling Over 3D Terrains
Saeed Moazami, Hassan Zargarzadeh, Srinivas Palanki
http://arxiv.org/abs/1906.05228v1
• [cs.RO]Snake-Like Robots for Minimally Invasive, Single Port, and Intraluminal Surgeries
Andrew L. Orekhov, Colette Abah, Nabil Simaan
http://arxiv.org/abs/1906.04852v1
• [cs.RO]Transferrable Operative Difficulty Assessment in Robot-assisted Teleoperation: A Domain Adaptation Approach
Ziheng Wang, Cong Feng, Jie Zhang, Ann Majewicz Fey
http://arxiv.org/abs/1906.04934v1
• [cs.SE]Does BLEU Score Work for Code Migration?
Ngoc Tran, Hieu Tran, Son Nguyen, Hoan Nguyen, Tien N. Nguyen
http://arxiv.org/abs/1906.04903v1
• [cs.SI]A decentralized trust-aware collaborative filtering recommender system based on weighted items for social tagging systems
Hossein Monshizadeh Naeen, Mehrdad Jalali
http://arxiv.org/abs/1906.05143v1
• [cs.SI]Optimizing city-scale traffic flows through modeling isolated observations of vehicle movements
Fan Yang, Alina Vereshchaka, Bruno Lepri, Wen Dong
http://arxiv.org/abs/1906.05093v1
• [cs.SI]Power-law Verification for Event Detection at Multi-spatial Scales from Geo-tagged Tweet Streams
Yi Han, Shanika Karunasekera, Christopher Leckie, Aaron Harwood
http://arxiv.org/abs/1906.05063v1
• [cs.SI]Understanding Vulnerability of Communities in Complex Networks
V. Parimi, A. Pal, S. Ruj, P. Kumaraguru, T. Chakraborty
http://arxiv.org/abs/1906.05238v1
• [cs.SI]Weighted, Bipartite, or Directed Stream Graphs for the Modeling of Temporal Networks
Matthieu Latapy, Clémence Magnien, Tiphaine Viard
http://arxiv.org/abs/1906.04840v1
• [eess.IV]Joint 3D Localization and Classification of Space Debris using a Multispectral Rotating Point Spread Function
Chao Wang, Grey Ballard, Robert Plemmons, Sudhakar Prasad
http://arxiv.org/abs/1906.04749v1
• [eess.IV]`Project & Excite’ Modules for Segmentation of Volumetric Medical Scans
Anne-Marie Rickmann, Abhijit Guha Roy, Ignacio Sarasua, Nassir Navab, Christian Wachinger
http://arxiv.org/abs/1906.04649v2
• [eess.SP]Trip Table Estimation and Prediction for Dynamic Traffic Assignment Applications
Sajjad Shafiei, Adriana-Simona Mihaita, Chen Cai
http://arxiv.org/abs/1906.04739v1
• [eess.SY]Reinforcement-Learning-based Adaptive Optimal Control for Arbitrary Reference Tracking
Florian Köpf, Johannes Westermann, Michael Flad, Sören Hohmann
http://arxiv.org/abs/1906.05085v1
• [math.OC]Critical Point Finding with Newton-MR by Analogy to Computing Square Roots
Charles G Frye
http://arxiv.org/abs/1906.05273v1
• [math.OC]Deep Forward-Backward SDEs for Min-max Control
Ziyi Wang, Keuntaek Lee, Marcus A. Pereira, Ioannis Exarchos, Evangelos A. Theodorou
http://arxiv.org/abs/1906.04771v1
• [math.OC]Global optimization using Sobol indices
Alexandre Janon
http://arxiv.org/abs/1906.05189v1
• [math.SP]Spectral Ratio for Positive Matrices
Wendi Han, Guangyue Han
http://arxiv.org/abs/1906.04875v1
• [math.ST]Knowledge Gradient for Selection with Covariates: Consistency and Computation
Xiaowei Zhang, Haihui Shen, L. Jeff Hong, Liang Ding
http://arxiv.org/abs/1906.05098v1
• [math.ST]Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification
Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Luca Oneto, Massimiliano Pontil
http://arxiv.org/abs/1906.05082v1
• [math.ST]Robust subgaussian estimation of a mean vector in nearly linear time
Jules Depersin, Guillaume Lecué
http://arxiv.org/abs/1906.03058v2
• [math.ST]Stein’s method and the distribution of the product of zero mean correlated normal random variables
Robert E. Gaunt
http://arxiv.org/abs/1906.04785v1
• [math.ST]Structure-adaptive manifold estimation
Nikita Puchkin, Vladimir Spokoiny
http://arxiv.org/abs/1906.05014v1
• [physics.bio-ph]High-resolution Markov state models for the dynamics of Trp-cage miniprotein constructed over slow folding modes identified by state-free reversible VAMPnets
Hythem Sidky, Wei Chen, Andrew L. Ferguson
http://arxiv.org/abs/1906.04890v1
• [q-bio.GN]Exploring Bayesian approaches to eQTL mapping through probabilistic programming
Dimitrios V Vavoulis
http://arxiv.org/abs/1906.05150v1
• [q-bio.PE]Markov-modulated continuous-time Markov chains to identify site- and branch-specific evolutionary variation
Guy Baele, Mandev S. Gill, Philippe Lemey, Marc A. Suchard
http://arxiv.org/abs/1906.05136v1
• [q-bio.PE]Relaxed random walks at scale
Alexander A. Fisher, Xiang Ji, Philippe Lemey, Marc A. Suchard
http://arxiv.org/abs/1906.04834v1
• [q-fin.PR]Deep Smoothing of the Implied Volatility Surface
Damien Ackerer, Natasa Tagasovska, Thibault Vatter
http://arxiv.org/abs/1906.05065v1
• [stat.AP]A Bayesian Hierarchical Model for Evaluating Forensic Footwear Evidence
Neil A. Spencer, Jared S. Murray
http://arxiv.org/abs/1906.05244v1
• [stat.AP]Applying economic measures to lapse risk management with machine learning approaches
Stéphane Loisel, Pierrick Piette, Jason Tsai
http://arxiv.org/abs/1906.05087v1
• [stat.AP]Assessing the effects of exposure to sulfuric acid aerosol on respiratory function in adults
Lamin Juwara, Jennifer Boateng
http://arxiv.org/abs/1906.04296v2
• [stat.AP]Estimating the Number of Fatal Victims of the Peruvian Internal Armed Conflict, 1980-2000: an application of modern multi-list Capture-Recapture techniques
Daniel Manrique-Vallier, Patrick Ball, David Sulmont
http://arxiv.org/abs/1906.04763v1
• [stat.AP]Technical Preprint: Rationale and Design of a Planned Observational Study to Evaluate the Impact of Hydrocodone Rescheduling on Opioid Prescribing After Surgery
Mark D. Neuman, Sean Hennessy, Dylan Small, Colleen Brensinger, Craig Newcomb, Lakisha Gaskins, Duminda Wijeysundera, Brian T. Bateman, Hannah Wunsch
http://arxiv.org/abs/1906.04246v2
• [stat.ME]A mnotone data augmentation algorithm for longitudinal data analysis via multivariate skew-t, skew-normal or t distributions
Yongqiang Tang
http://arxiv.org/abs/1906.04844v1
• [stat.ME]Distribution-Free Multisample Test Based on Optimal Matching with Applications to Single Cell Genomics
Divyansh Agarwal, Somabha Mukherjee, Bhaswar Bikram Bhattacharya, Nancy Ruonan Zhang
http://arxiv.org/abs/1906.04776v1
• [stat.ME]Functional Singular Spectrum Analysis
Hossein Haghbin, Seyed Morteza Najibi, Rahim Mahmoudvand, Mehdi Maadooliat
http://arxiv.org/abs/1906.05232v1
• [stat.ME]Learning High-Dimensional Gaussian Graphical Models under Total Positivity without Tuning Parameters
Yuhao Wang, Uma Roy, Caroline Uhler
http://arxiv.org/abs/1906.05159v1
• [stat.ME]Model Testing for Generalized Scalar-on-Function Linear Models
Stephanie T. Chen, Luo Xiao, Ana-Maria Staicu
http://arxiv.org/abs/1906.04889v1
• [stat.ME]Structure learning of Bayesian networks involving cyclic structures
Witold Wiecek, Frederic Y. Bois, Ghislaine Gayraud
http://arxiv.org/abs/1906.04992v1
• [stat.ME]The EAS approach for graphical selection consistency in vector autoregression models
Jonathan P Williams, Yuying Xie, Jan Hannig
http://arxiv.org/abs/1906.04812v1
• [stat.ML]ADASS: Adaptive Sample Selection for Training Acceleration
Shen-Yi Zhao, Hao Gao, Wu-Jun Li
http://arxiv.org/abs/1906.04819v1
• [stat.ML]Attention-based Multi-Input Deep Learning Architecture for Biological Activity Prediction: An Application in EGFR Inhibitors
Huy Ngoc Pham, Trung Hoang Le
http://arxiv.org/abs/1906.05168v1
• [stat.ML]Bootstrapping Upper Confidence Bound
Botao Hao, Yasin Abbasi-Yadkori, Zheng Wen, Guang Cheng
http://arxiv.org/abs/1906.05247v1
• [stat.ML]Communication-Efficient Accurate Statistical Estimation
Jianqing Fan, Yongyi Guo, Kaizheng Wang
http://arxiv.org/abs/1906.04870v1
• [stat.ML]Improving Importance Weighted Auto-Encoders with Annealed Importance Sampling
Xinqiang Ding, David J. Freedman
http://arxiv.org/abs/1906.04904v1
• [stat.ML]Medium-Term Load Forecasting Using Support Vector Regression, Feature Selection, and Symbiotic Organism Search Optimization
Arghavan Zare-Noghabi, Morteza Shabanzadeh, Hossein Sangrody
http://arxiv.org/abs/1906.04818v1
• [stat.ML]On the Universality of Noiseless Linear Estimation with Respect to the Measurement Matrix
Alia Abbara, Antoine Baker, Florent Krzakala, Lenka Zdeborová
http://arxiv.org/abs/1906.04735v1
• [stat.ML]Stable Rank Normalization for Improved Generalization in Neural Networks and GANs
Amartya Sanyal, Philip H. S. Torr, Puneet K. Dokania
http://arxiv.org/abs/1906.04659v2
• [stat.ML]Task Agnostic Continual Learning via Meta Learning
Xu He, Jakub Sygnowski, Alexandre Galashov, Andrei A. Rusu, Yee Whye Teh, Razvan Pascanu
http://arxiv.org/abs/1906.05201v1
• [stat.ML]The Impact of Regularization on High-dimensional Logistic Regression
Fariborz Salehi, Ehsan Abbasi, Babak Hassibi
http://arxiv.org/abs/1906.03761v2