cond-mat.mtrl-sci - 材料科学

    cond-mat.soft - 软凝聚物质 cs.AI - 人工智能 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DC - 分布式、并行与集群计算 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.NE - 神经与进化计算 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 econ.GN - 一般经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 physics.ao-ph - 大气和海洋物理 physics.ins-det - 仪器和探测器 q-bio.NC - 神经元与认知 q-bio.PE - 人口与发展 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cond-mat.mtrl-sci]Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide
    • [cond-mat.soft]Using Bayesian model selection to advise neutron reflectometry analysis from Langmuir-Blodgett monolayers
    • [cs.AI]AnnaParser: Semantic Parsing for Tabular Data Analysis
    • [cs.AI]Knowledge Map: Toward a New Approach Supporting the Knowledge Management in Distributed Data Mining
    • [cs.AI]RTOP: A Conceptual and Computational Framework for General Intelligence
    • [cs.CL]A Search-based Neural Model for Biomedical Nested and Overlapping Event Detection
    • [cs.CL]A practical two-stage training strategy for multi-stream end-to-end speech recognition
    • [cs.CL]Capturing Greater Context for Question Generation
    • [cs.CL]Controlling the Output Length of Neural Machine Translation
    • [cs.CL]Correction of Automatic Speech Recognition with Transformer Sequence-to-sequence Model
    • [cs.CL]Deja-vu: Double Feature Presentation in Deep Transformer Networks
    • [cs.CL]Efficient Dynamic WFST Decoding for Personalized Language Models
    • [cs.CL]IPOD: Corpus of 190,000 Industrial Occupations
    • [cs.CL]Incremental Online Spoken Language Understanding
    • [cs.CL]Instance-Based Model Adaptation For Direct Speech Translation
    • [cs.CL]Kernel Graph Attention Network for Fact Verification
    • [cs.CL]Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis
    • [cs.CL]Opinion aspect extraction in Dutch childrens diary entries
    • [cs.CL]Robust Neural Machine Translation for Clean and Noisy Speech Transcripts
    • [cs.CL]Speaker Adaptive Training using Model Agnostic Meta-Learning
    • [cs.CL]Speech-XLNet: Unsupervised Acoustic Model Pretraining For Self-Attention Networks
    • [cs.CR]ASNM Datasets: A Collection of Network Traffic Features for Testing of Adversarial Classifiers and Network Intrusion Detectors
    • [cs.CR]Deep learning guided Android malware and anomaly detection
    • [cs.CV]Accurate 6D Object Pose Estimation by Pose Conditioned Mesh Reconstruction
    • [cs.CV]Breast Anatomy Enriched Tumor Saliency Estimation
    • [cs.CV]Deep Classification Network for Monocular Depth Estimation
    • [cs.CV]Domain Bridge for Unpaired Image-to-Image Translation and Unsupervised Domain Adaptation
    • [cs.CV]Facial Expression Restoration Based on Improved Graph Convolutional Networks
    • [cs.CV]Fast and Automatic Periacetabular Osteotomy Fragment Pose Estimation Using Intraoperatively Implanted Fiducials and Single-View Fluoroscopy
    • [cs.CV]Identification of primary angle-closure on AS-OCT images with Convolutional Neural Networks
    • [cs.CV]Iterative Matching Point
    • [cs.CV]Occlusions for Effective Data Augmentation in Image Classification
    • [cs.CV]Random 2.5D U-net for Fully 3D Segmentation
    • [cs.CV]Region Based Adversarial Synthesis of Facial Action Units
    • [cs.CV]Relation Modeling with Graph Convolutional Networks for Facial Action Unit Detection
    • [cs.CV]SalGaze: Personalizing Gaze Estimation Using Visual Saliency
    • [cs.CV]Semi-supervised Multi-domain Multi-task Training for Metastatic Colon Lymph Node Diagnosis From Abdominal CT
    • [cs.CV]Unsupervised Robust Disentangling of Latent Characteristics for Image Synthesis
    • [cs.CV]Using Segmentation Masks in the ICCV 2019 Learning to Drive Challenge
    • [cs.CV]Winning the ICCV 2019 Learning to Drive Challenge
    • [cs.CY]Achieving Ethical Algorithmic Behaviour in the Internet-of-Things: a Review
    • [cs.CY]An Empirical Study on Learning Fairness Metrics for COMPAS Data with Human Supervision
    • [cs.CY]Robot-Friendly Cities
    • [cs.CY]Towards Robotic Things in Society
    • [cs.DC]An Optimized, Parallel Computation of the Ghost Layer for Adaptive Hybrid Forest Meshes
    • [cs.DC]Blockchain Methods for Trusted Avionics Systems
    • [cs.DC]Divide and Scale: Formalization of Distributed Ledger Sharding Protocols
    • [cs.DC]Train Where the Data is: A Case for Bandwidth Efficient Coded Training
    • [cs.HC]On Automating Conversations
    • [cs.HC]The Task Analysis Cell Assembly Perspective
    • [cs.IR]BanditRank: Learning to Rank Using Contextual Bandits
    • [cs.IR]Context-Aware Sentence/Passage Term Importance Estimation For First Stage Retrieval
    • [cs.IR]Lucene for Approximate Nearest-Neighbors Search on Arbitrary Dense Vectors
    • [cs.IR]Self-Attentive Document Interaction Networks for Permutation Equivariant Ranking
    • [cs.IT]A New Method to Construct Gloay Complementary Set by Paraunitary Matrices and Hadamard Matrices
    • [cs.IT]CNN-based Analog CSI Feedback in FDD MIMO-OFDM Systems
    • [cs.IT]Circularly Pulse Shaped Orthogonal Time Frequency Space Modulation
    • [cs.IT]Coded Caching with Linear Subpacketization is Possible in Multi-Antenna Communications
    • [cs.IT]Distribution of the Sum of Fisher-Snedecor $\mathcal{F}$ Random Variables and Its Applications
    • [cs.IT]Management and Orchestration of Virtual Network Functions via Deep Reinforcement Learning
    • [cs.IT]New Construction of Complementary Sequence (or Array) Sets and Complete Complementary Codes (I)
    • [cs.IT]New Construction of Complementary Sequence (or Array) Sets and Complete Complementary Codes (II)
    • [cs.IT]On the Bee-Identification Error Exponent with Absentee Bees
    • [cs.IT]Trainable Projected Gradient Detector for Sparsely Spread Code Division Multiple Access
    • [cs.LG]A Unifying Framework of Bilinear LSTMs
    • [cs.LG]A Useful Taxonomy for Adversarial Robustness of Neural Networks
    • [cs.LG]Better Approximate Inference for Partial Likelihood Models with a Latent Structure
    • [cs.LG]Bottom-Up Meta-Policy Search
    • [cs.LG]Complex Transformer: A Framework for Modeling Complex-Valued Sequence
    • [cs.LG]Contrastive Representation Distillation
    • [cs.LG]Deep Learning at the Edge
    • [cs.LG]Detecting Out-of-Distribution Inputs in Deep Neural Networks Using an Early-Layer Output
    • [cs.LG]EdgeAI: A Vision for Deep Learning in IoT Era
    • [cs.LG]Efficient Decoupled Neural Architecture Search by Structure and Operation Sampling
    • [cs.LG]Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
    • [cs.LG]Feature Selection and Extraction for Graph Neural Networks
    • [cs.LG]Federated Evaluation of On-device Personalization
    • [cs.LG]Federated Learning with Unbiased Gradient Aggregation and Controllable Meta Updating
    • [cs.LG]Generalized Domain Adaptation with Covariate and Label Shift CO-ALignment
    • [cs.LG]Interpreting Basis Path Set in Neural Networks
    • [cs.LG]Learning Partial Differential Equations from Data Using Neural Networks
    • [cs.LG]MLAT: Metric Learning for kNN in Streaming Time Series
    • [cs.LG]Online Meta-Learning on Non-convex Setting
    • [cs.LG]Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation
    • [cs.LG]Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning
    • [cs.LG]Recurrent Attention Walk for Semi-supervised Classification
    • [cs.LG]Restless Hidden Markov Bandits with Linear Rewards
    • [cs.LG]Robust Domain Randomization for Reinforcement Learning
    • [cs.LG]Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles
    • [cs.LG]Self-Attention for Raw Optical Satellite Time Series Classification
    • [cs.LG]Stabilising priors for robust Bayesian deep learning
    • [cs.LG]State2vec: Off-Policy Successor Features Approximators
    • [cs.LG]Strategic Adaptation to Classifiers: A Causal Perspective
    • [cs.LG]USTAR: Online Multimodal Embedding for Modeling User-Guided Spatiotemporal Activity
    • [cs.LG]Weighted Distributed Differential Privacy ERM: Convex and Non-convex
    • [cs.LO]Knowledge of Uncertain Worlds: Programming with Logical Constraints
    • [cs.NE]A Novel Generalized Artificial Neural Network for Mining Two-Class Datasets
    • [cs.NE]Autoencoding with XCSF
    • [cs.NE]Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis
    • [cs.RO]An Analytical Lidar Sensor Model Based on Ray Path Information
    • [cs.RO]Closed-Form Full Map Posteriors for Robot Localization with Lidar Sensors
    • [cs.RO]Impact-Aware Online Motion Planning for Fully-Actuated Bipedal Robot Walking
    • [cs.RO]Learning Deep Parameterized Skills from Demonstration for Re-targetable Visuomotor Control
    • [cs.RO]Learning Humanoid Robot Running Skills through Proximal Policy Optimization
    • [cs.RO]Long-Term Urban Vehicle Localization Using Pole Landmarks Extracted from 3-D Lidar Scans
    • [cs.RO]Teach Biped Robots to Walk via Gait Principles and Reinforcement Learning with Adversarial Critics
    • [cs.RO]gradSLAM: Dense SLAM meets Automatic Differentiation
    • [cs.SD]Filterbank design for end-to-end speech separation
    • [cs.SD]Learning the helix topology of musical pitch
    • [cs.SE]Kuksa: A Cloud-Native Architecture for Enabling Continuous Delivery in the Automotive Domain
    • [cs.SI]Network2Vec Learning Node Representation Based on Space Mapping in Networks
    • [econ.GN]Beating the House: Identifying Inefficiencies in Sports Betting Markets
    • [eess.AS]A Transformer with Interleaved Self-attention and Convolution for Hybrid Acoustic Models
    • [eess.IV]A Deep Learning based Pipeline for Efficient Oral Cancer Screening on Whole Slide Images
    • [eess.IV]Deep Clustering of Compressed Variational Embeddings
    • [eess.IV]Deep Learning Supersampled Scanning Transmission Electron Microscopy
    • [eess.IV]Deep generative model-driven multimodal prostate segmentation in radiotherapy
    • [eess.IV]Divide-and-Conquer Adversarial Learning for High-Resolution Image and Video Enhancement
    • [eess.IV]INTEL-TAU: A Color Constancy Dataset
    • [eess.IV]Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands
    • [eess.IV]Photoshopping Colonoscopy Video Frames
    • [eess.IV]Semantic Segmentation of Skin Lesions using a Small Data Set
    • [eess.IV]Stain Style Transfer using Transitive Adversarial Networks
    • [eess.IV]Towards an Intelligent Microscope: adaptively learned illumination for optimal sample classification
    • [eess.SP]New RLL Code with Improved Error Performance for Visible Light Communication
    • [eess.SY]Decentralized Runtime Synthesis of Shields for Multi-Agent Systems
    • [eess.SY]Prioritized Inverse Kinematics: Desired Task Trajectories in Nonsingular Task Spaces
    • [math.NA]Kernel Methods for Bayesian Elliptic Inverse Problems on Manifolds
    • [math.OC]Accelerated Primal-Dual Algorithms for Distributed Smooth Convex Optimization over Networks
    • [math.ST]How well can we learn large factor models without assuming strong factors?
    • [math.ST]Minimax Rate Optimal Adaptive Nearest Neighbor Classification and Regression
    • [math.ST]Multiple outlier detection tests for parametric models
    • [math.ST]Objective Bayesian Analysis of a Cokriging Model for Hierarchical Multifidelity Codes
    • [math.ST]On the behavior of the DFA and DCCA in trend-stationary processes
    • [physics.ao-ph]Tropical Cyclone Track Forecasting using Fused Deep Learning from Aligned Reanalysis Data
    • [physics.ins-det]Towards Fast Displaced Vertex Finding
    • [q-bio.NC]Working memory facilitates reward-modulated Hebbian learning in recurrent neural networks
    • [q-bio.PE]Inference with selection, varying population size and evolving population structure: Application of ABC to a forward-backward coalescent process with interactions
    • [stat.AP]An inverse problem approach to the probabilistic reconstruction of particle tracks on a censored and closed surface
    • [stat.AP]Double-Counting Problem of the Bonus-Malus System
    • [stat.AP]Statistical Modeling for Spatio-Temporal Data from Physical Convection-Diffusion Processes
    • [stat.CO]Event-scheduling algorithms with Kalikow decomposition for simulating potentially infinite neuronal networks
    • [stat.ME]A Stochastic Block Model for Multilevel Networks: Application to the Sociology of Organisations
    • [stat.ME]Bayesian nonparametric temporal dynamic clustering via autoregressive Dirichlet priors
    • [stat.ME]Doubly robust treatment effect estimation with missing attributes
    • [stat.ME]Flexible Bayesian modelling in dichotomous item response theory using mixtures of skewed item curves
    • [stat.ME]Nested Conformal Prediction and the Generalized Jackknife+
    • [stat.ML]Deterministic tensor completion with hypergraph expanders
    • [stat.ML]Global Capacity Measures for Deep ReLU Networks via Path Sampling
    • [stat.ML]Leveraging directed causal discovery to detect latent common causes
    • [stat.ML]Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small Molecules
    • [stat.ML]Neural Execution of Graph Algorithms
    • [stat.ML]Sparse Orthogonal Variational Inference for Gaussian Processes
    • [stat.ML]Unifying Variational Inference and PAC-Bayes for Supervised Learning that Scales

    ·····································

    • [cond-mat.mtrl-sci]Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide
    Ganesh Sivaraman, Anand Narayanan Krishnamoorthy, Matthias Baur, Christian Holm, Marius Stan, Gabor Csányi, Chris Benmore, Álvaro Vázquez-Mayagoitia
    http://arxiv.org/abs/1910.10254v1

    • [cond-mat.soft]Using Bayesian model selection to advise neutron reflectometry analysis from Langmuir-Blodgett monolayers
    Andrew R. McCluskey, Thomas Arnold, Joshaniel F. K. Cooper, Tim Snow
    http://arxiv.org/abs/1910.10581v1

    • [cs.AI]AnnaParser: Semantic Parsing for Tabular Data Analysis
    Yan Gao, Jian-Guang Lou, Dongmei Zhang
    http://arxiv.org/abs/1910.10363v1

    • [cs.AI]Knowledge Map: Toward a New Approach Supporting the Knowledge Management in Distributed Data Mining
    Nhien-An Le-Khac, Lamine M. Aouad, M-Tahar Kechadi
    http://arxiv.org/abs/1910.10547v1

    • [cs.AI]RTOP: A Conceptual and Computational Framework for General Intelligence
    Shilpesh Garg
    http://arxiv.org/abs/1910.10393v1

    • [cs.CL]A Search-based Neural Model for Biomedical Nested and Overlapping Event Detection
    Kurt Espinosa, Makoto Miwa, Sophia Ananiadou
    http://arxiv.org/abs/1910.10281v1

    • [cs.CL]A practical two-stage training strategy for multi-stream end-to-end speech recognition
    Ruizhi Li, Gregory Sell, Xiaofei Wang, Shinji Watanabe, Hynek Hermansky
    http://arxiv.org/abs/1910.10671v1

    • [cs.CL]Capturing Greater Context for Question Generation
    Luu Anh Tuan, Darsh J Shah, Regina Barzilay
    http://arxiv.org/abs/1910.10274v1

    • [cs.CL]Controlling the Output Length of Neural Machine Translation
    Surafel Melaku Lakew, Mattia Di Gangi, Marcello Federico
    http://arxiv.org/abs/1910.10408v1

    • [cs.CL]Correction of Automatic Speech Recognition with Transformer Sequence-to-sequence Model
    Oleksii Hrinchuk, Mariya Popova, Boris Ginsburg
    http://arxiv.org/abs/1910.10697v1

    • [cs.CL]Deja-vu: Double Feature Presentation in Deep Transformer Networks
    Andros Tjandra, Chunxi Liu, Frank Zhang, Xiaohui Zhang, Yongqiang Wang, Gabriel Synnaeve, Satoshi Nakamura, Geoffrey Zweig
    http://arxiv.org/abs/1910.10324v1

    • [cs.CL]Efficient Dynamic WFST Decoding for Personalized Language Models
    Jun Liu, Jiedan Zhu, Vishal Kathuria, Fuchun Peng
    http://arxiv.org/abs/1910.10670v1

    • [cs.CL]IPOD: Corpus of 190,000 Industrial Occupations
    Junhua Liu, Chu Guo, Yung Chuen Ng, Kristin L. Wood, Kwan Hui Lim
    http://arxiv.org/abs/1910.10495v1

    • [cs.CL]Incremental Online Spoken Language Understanding
    Prashanth Gurunath Shivakumar, Naveen Kumar, Panayiotis Georgiou, Shrikanth Narayanan
    http://arxiv.org/abs/1910.10287v1

    • [cs.CL]Instance-Based Model Adaptation For Direct Speech Translation
    Mattia Antonino Di Gangi, Viet-Nhat Nguyen, Matteo Negri, Marco Turchi
    http://arxiv.org/abs/1910.10663v1

    • [cs.CL]Kernel Graph Attention Network for Fact Verification
    Zhenghao Liu, Chenyan Xiong, Maosong Sun
    http://arxiv.org/abs/1910.09796v2

    • [cs.CL]Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis
    Eric Battenberg, RJ Skerry-Ryan, Soroosh Mariooryad, Daisy Stanton, David Kao, Matt Shannon, Tom Bagby
    http://arxiv.org/abs/1910.10288v1

    • [cs.CL]Opinion aspect extraction in Dutch childrens diary entries
    Hella Haanstra, Maaike H. T. de Boer
    http://arxiv.org/abs/1910.10502v1

    • [cs.CL]Robust Neural Machine Translation for Clean and Noisy Speech Transcripts
    Mattia Antonino Di Gangi, Robert Enyedi, Alessandra Brusadin, Marcello Federico
    http://arxiv.org/abs/1910.10238v1

    • [cs.CL]Speaker Adaptive Training using Model Agnostic Meta-Learning
    Ondřej Klejch, Joachim Fainberg, Peter Bell, Steve Renals
    http://arxiv.org/abs/1910.10605v1

    • [cs.CL]Speech-XLNet: Unsupervised Acoustic Model Pretraining For Self-Attention Networks
    Xingchen Song, Guangsen Wang, Zhiyong Wu, Yiheng Huang, Dan Su, Dong Yu, Helen Meng
    http://arxiv.org/abs/1910.10387v1

    • [cs.CR]ASNM Datasets: A Collection of Network Traffic Features for Testing of Adversarial Classifiers and Network Intrusion Detectors
    Ivan Homoliak, Petr Hanacek
    http://arxiv.org/abs/1910.10528v1

    • [cs.CR]Deep learning guided Android malware and anomaly detection
    Nikola Milosevic, Junfan Huang
    http://arxiv.org/abs/1910.10660v1

    • [cs.CV]Accurate 6D Object Pose Estimation by Pose Conditioned Mesh Reconstruction
    Pedro Castro, Anil Armagan, Tae-Kyun Kim
    http://arxiv.org/abs/1910.10653v1

    • [cs.CV]Breast Anatomy Enriched Tumor Saliency Estimation
    Fei Xu, Yingtao Zhang, Min Xian, H. D. Cheng, Boyu Zhang, Jianrui Ding, Chunping Ning, Ying Wang
    http://arxiv.org/abs/1910.10652v1

    • [cs.CV]Deep Classification Network for Monocular Depth Estimation
    Azeez Oluwafemi, Yang Zou, B. V. K. Vijaya Kumar
    http://arxiv.org/abs/1910.10369v1

    • [cs.CV]Domain Bridge for Unpaired Image-to-Image Translation and Unsupervised Domain Adaptation
    Fabio Pizzati, Raoul de Charette, Michela Zaccaria, Pietro Cerri
    http://arxiv.org/abs/1910.10563v1

    • [cs.CV]Facial Expression Restoration Based on Improved Graph Convolutional Networks
    Zhilei Liu, Le Li, Yunpeng Wu, Cuicui Zhang
    http://arxiv.org/abs/1910.10344v1

    • [cs.CV]Fast and Automatic Periacetabular Osteotomy Fragment Pose Estimation Using Intraoperatively Implanted Fiducials and Single-View Fluoroscopy
    Robert Grupp, Ryan Murphy, Rachel Hegeman, Clayton Alexander, Mathias Unberath, Yoshito Otake, Benjamin McArthur, Mehran Armand, Russell Taylor
    http://arxiv.org/abs/1910.10187v1

    • [cs.CV]Identification of primary angle-closure on AS-OCT images with Convolutional Neural Networks
    Chenglang Yuan, Cheng Bian, Hongjian Kang, Shu Liang, Kai Ma, Yefeng Zheng
    http://arxiv.org/abs/1910.10414v1

    • [cs.CV]Iterative Matching Point
    Jiahao Li, Changhao Zhang
    http://arxiv.org/abs/1910.10328v1

    • [cs.CV]Occlusions for Effective Data Augmentation in Image Classification
    Ruth Fong, Andrea Vedaldi
    http://arxiv.org/abs/1910.10651v1

    • [cs.CV]Random 2.5D U-net for Fully 3D Segmentation
    Christoph Angermann, Markus Haltmeier
    http://arxiv.org/abs/1910.10398v1

    • [cs.CV]Region Based Adversarial Synthesis of Facial Action Units
    Zhilei Liu, Diyi Liu, Yunpeng Wu
    http://arxiv.org/abs/1910.10323v1

    • [cs.CV]Relation Modeling with Graph Convolutional Networks for Facial Action Unit Detection
    Zhilei Liu, Jiahui Dong, Cuicui Zhang, Longbiao Wang, Jianwu Dang
    http://arxiv.org/abs/1910.10334v1

    • [cs.CV]SalGaze: Personalizing Gaze Estimation Using Visual Saliency
    Zhuoqing Chang, Matias Di Martino, Qiang Qiu, Steven Espinosa, Guillermo Sapiro
    http://arxiv.org/abs/1910.10603v1

    • [cs.CV]Semi-supervised Multi-domain Multi-task Training for Metastatic Colon Lymph Node Diagnosis From Abdominal CT
    Saskia Glaser, Gabriel Maicas, Sergei Bedrikovetski, Tarik Sammour, Gustavo Carneiro
    http://arxiv.org/abs/1910.10371v1

    • [cs.CV]Unsupervised Robust Disentangling of Latent Characteristics for Image Synthesis
    Patrick Esser, Johannes Haux, Björn Ommer
    http://arxiv.org/abs/1910.10223v1

    • [cs.CV]Using Segmentation Masks in the ICCV 2019 Learning to Drive Challenge
    Antonia Lovjer, Minsu Yeom, Benedikt D. Schifferer, Iddo Drori
    http://arxiv.org/abs/1910.10317v1

    • [cs.CV]Winning the ICCV 2019 Learning to Drive Challenge
    Michael Diodato, Yu Li, Manik Goyal, Iddo Drori
    http://arxiv.org/abs/1910.10318v1

    • [cs.CY]Achieving Ethical Algorithmic Behaviour in the Internet-of-Things: a Review
    Seng W. Loke
    http://arxiv.org/abs/1910.10241v1

    • [cs.CY]An Empirical Study on Learning Fairness Metrics for COMPAS Data with Human Supervision
    Hanchen Wang, Nina Grgic-Hlaca, Preethi Lahoti, Krishna P. Gummadi, Adrian Weller
    http://arxiv.org/abs/1910.10255v1

    • [cs.CY]Robot-Friendly Cities
    Seng W. Loke
    http://arxiv.org/abs/1910.10258v1

    • [cs.CY]Towards Robotic Things in Society
    Seng W. Loke
    http://arxiv.org/abs/1910.10253v1

    • [cs.DC]An Optimized, Parallel Computation of the Ghost Layer for Adaptive Hybrid Forest Meshes
    Johannes Holke, David Knapp, Carsten Burstedde
    http://arxiv.org/abs/1910.10641v1

    • [cs.DC]Blockchain Methods for Trusted Avionics Systems
    Erik Blasch, Ronghua Xu, Yu Chen, Genshe Chen, Dan Shen
    http://arxiv.org/abs/1910.10638v1

    • [cs.DC]Divide and Scale: Formalization of Distributed Ledger Sharding Protocols
    Georgia Avarikioti, Eleftherios Kokoris-Kogias, Roger Wattenhofer
    http://arxiv.org/abs/1910.10434v1

    • [cs.DC]Train Where the Data is: A Case for Bandwidth Efficient Coded Training
    Zhifeng Lin, Krishna Giri Narra, Mingchao Yu, Salman Avestimehr, Murali Annavaram
    http://arxiv.org/abs/1910.10283v1

    • [cs.HC]On Automating Conversations
    Ting-Hao ‘Kenneth’ Huang
    http://arxiv.org/abs/1910.09621v2

    • [cs.HC]The Task Analysis Cell Assembly Perspective
    Dan Diaper, Chris Huyck
    http://arxiv.org/abs/1910.10481v1

    • [cs.IR]BanditRank: Learning to Rank Using Contextual Bandits
    Phanideep Gampa, Sumio Fujita
    http://arxiv.org/abs/1910.10410v1

    • [cs.IR]Context-Aware Sentence/Passage Term Importance Estimation For First Stage Retrieval
    Zhuyun Dai, Jamie Callan
    http://arxiv.org/abs/1910.10687v1

    • [cs.IR]Lucene for Approximate Nearest-Neighbors Search on Arbitrary Dense Vectors
    Tommaso Teofili, Jimmy Lin
    http://arxiv.org/abs/1910.10208v1

    • [cs.IR]Self-Attentive Document Interaction Networks for Permutation Equivariant Ranking
    Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork
    http://arxiv.org/abs/1910.09676v2

    • [cs.IT]A New Method to Construct Gloay Complementary Set by Paraunitary Matrices and Hadamard Matrices
    Zilong Wang, Gaofei Wu, Dongxu Ma
    http://arxiv.org/abs/1910.10302v1

    • [cs.IT]CNN-based Analog CSI Feedback in FDD MIMO-OFDM Systems
    Mahdi Boloursaz Mashhadi, Qianqian Yang, Deniz Gunduz
    http://arxiv.org/abs/1910.10428v1

    • [cs.IT]Circularly Pulse Shaped Orthogonal Time Frequency Space Modulation
    Shashank Tiwari, Suvra Sekhar Das
    http://arxiv.org/abs/1910.10457v1

    • [cs.IT]Coded Caching with Linear Subpacketization is Possible in Multi-Antenna Communications
    MohammadJavad Salehi, Antti Tölli, Seyed Pooya Shariatpanahi
    http://arxiv.org/abs/1910.10384v1

    • [cs.IT]Distribution of the Sum of Fisher-Snedecor $\mathcal{F}$ Random Variables and Its Applications
    Hongyang Du, Jiayi Zhang, Julian Cheng, Bo Ai
    http://arxiv.org/abs/1910.10565v1

    • [cs.IT]Management and Orchestration of Virtual Network Functions via Deep Reinforcement Learning
    Joan S Pujol Roig, David M. Gutierrez-Estevez, Deniz Gündüz
    http://arxiv.org/abs/1910.10695v1

    • [cs.IT]New Construction of Complementary Sequence (or Array) Sets and Complete Complementary Codes (I)
    Zilong Wang, Dongxu Ma, Guang Gong
    http://arxiv.org/abs/1910.10304v1

    • [cs.IT]New Construction of Complementary Sequence (or Array) Sets and Complete Complementary Codes (II)
    Zilong Wang, Dongxu Ma, Erzhong Xue, Guang Gong, Srdjan Budisin
    http://arxiv.org/abs/1910.10310v1

    • [cs.IT]On the Bee-Identification Error Exponent with Absentee Bees
    Anshoo Tandon, Vincent Y. F. Tan, Lav R. Varshney
    http://arxiv.org/abs/1910.10333v1

    • [cs.IT]Trainable Projected Gradient Detector for Sparsely Spread Code Division Multiple Access
    Satoshi Takabe, Yuki Yamauchi, Tadashi Wadayama
    http://arxiv.org/abs/1910.10336v1

    • [cs.LG]A Unifying Framework of Bilinear LSTMs
    Mohit Rajpal, Bryan Kian Hsiang Low
    http://arxiv.org/abs/1910.10294v1

    • [cs.LG]A Useful Taxonomy for Adversarial Robustness of Neural Networks
    Leslie N. Smith
    http://arxiv.org/abs/1910.10679v1

    • [cs.LG]Better Approximate Inference for Partial Likelihood Models with a Latent Structure
    Amrith Setlur, Barnabás Póczós
    http://arxiv.org/abs/1910.10211v1

    • [cs.LG]Bottom-Up Meta-Policy Search
    Luckeciano C. Melo, Marcos R. O. A. Maximo, Adilson Marques da Cunha
    http://arxiv.org/abs/1910.10232v1

    • [cs.LG]Complex Transformer: A Framework for Modeling Complex-Valued Sequence
    Muqiao Yang, Martin Q. Ma, Dongyu Li, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov
    http://arxiv.org/abs/1910.10202v1

    • [cs.LG]Contrastive Representation Distillation
    Yonglong Tian, Dilip Krishnan, Phillip Isola
    http://arxiv.org/abs/1910.10699v1

    • [cs.LG]Deep Learning at the Edge
    Sahar Voghoei, Navid Hashemi Tonekaboni, Jason G. Wallace, Hamid R. Arabnia
    http://arxiv.org/abs/1910.10231v1

    • [cs.LG]Detecting Out-of-Distribution Inputs in Deep Neural Networks Using an Early-Layer Output
    Vahdat Abdelzad, Krzysztof Czarnecki, Rick Salay, Taylor Denounden, Sachin Vernekar, Buu Phan
    http://arxiv.org/abs/1910.10307v1

    • [cs.LG]EdgeAI: A Vision for Deep Learning in IoT Era
    Kartikeya Bhardwaj, Naveen Suda, Radu Marculescu
    http://arxiv.org/abs/1910.10356v1

    • [cs.LG]Efficient Decoupled Neural Architecture Search by Structure and Operation Sampling
    Heung-Chang Lee, Do-Guk Kim, Bohyung Han
    http://arxiv.org/abs/1910.10397v1

    • [cs.LG]Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
    Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu
    http://arxiv.org/abs/1910.10683v1

    • [cs.LG]Feature Selection and Extraction for Graph Neural Networks
    Deepak Bhaskar Acharya, Dr. Huaming Zhang
    http://arxiv.org/abs/1910.10682v1

    • [cs.LG]Federated Evaluation of On-device Personalization
    Kangkang Wang, Rajiv Mathews, Chloé Kiddon, Hubert Eichner, Françoise Beaufays, Daniel Ramage
    http://arxiv.org/abs/1910.10252v1

    • [cs.LG]Federated Learning with Unbiased Gradient Aggregation and Controllable Meta Updating
    Xin Yao, Tianchi Huang, Rui-Xiao Zhang, Ruiyu Li, Lifeng Sun
    http://arxiv.org/abs/1910.08234v2

    • [cs.LG]Generalized Domain Adaptation with Covariate and Label Shift CO-ALignment
    Shuhan Tan, Xingchao Peng, Kate Saenko
    http://arxiv.org/abs/1910.10320v1

    • [cs.LG]Interpreting Basis Path Set in Neural Networks
    Juanping Zhu, Qi Meng, Wei Chen, Zhi-ming Ma
    http://arxiv.org/abs/1910.09402v1

    • [cs.LG]Learning Partial Differential Equations from Data Using Neural Networks
    Ali Hasan, João M. Pereira, Robert Ravier, Sina Farsiu, Vahid Tarokh
    http://arxiv.org/abs/1910.10262v1

    • [cs.LG]MLAT: Metric Learning for kNN in Streaming Time Series
    Dongmin Park, Susik Yoon, Hwanjun Song, Jae-Gil Lee
    http://arxiv.org/abs/1910.10368v1

    • [cs.LG]Online Meta-Learning on Non-convex Setting
    Zhenxun Zhuang, Yunlong Wang, Kezi Yu, Songtao Lu
    http://arxiv.org/abs/1910.10196v1

    • [cs.LG]Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation
    Viet Anh Nguyen, Soroosh Shafieezadeh-Abadeh, Man-Chung Yue, Daniel Kuhn, Wolfram Wiesemann
    http://arxiv.org/abs/1910.10583v1

    • [cs.LG]Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning
    Anis Elgabli, Jihong Park, Amrit S. Bedi, Mehdi Bennis, Vaneet Aggarwal
    http://arxiv.org/abs/1910.10453v1

    • [cs.LG]Recurrent Attention Walk for Semi-supervised Classification
    Uchenna Akujuobi, Qiannan Zhang, Han Yufei, Xiangliang Zhang
    http://arxiv.org/abs/1910.10266v1

    • [cs.LG]Restless Hidden Markov Bandits with Linear Rewards
    Michal Yemini, Amir Leshem, Anelia Somekh-Baruch
    http://arxiv.org/abs/1910.10271v1

    • [cs.LG]Robust Domain Randomization for Reinforcement Learning
    Reda Bahi Slaoui, William R. Clements, Jakob N. Foerster, Sébastien Toth
    http://arxiv.org/abs/1910.10537v1

    • [cs.LG]Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles
    Aditya Modi, Nan Jiang, Ambuj Tewari, Satinder Singh
    http://arxiv.org/abs/1910.10597v1

    • [cs.LG]Self-Attention for Raw Optical Satellite Time Series Classification
    Marc Rußwurm, Marco Körner
    http://arxiv.org/abs/1910.10536v1

    • [cs.LG]Stabilising priors for robust Bayesian deep learning
    Felix McGregor, Arnu Pretorius, Johan du Preez, Steve Kroon
    http://arxiv.org/abs/1910.10386v1

    • [cs.LG]State2vec: Off-Policy Successor Features Approximators
    Sephora Madjiheurem, Laura Toni
    http://arxiv.org/abs/1910.10277v1

    • [cs.LG]Strategic Adaptation to Classifiers: A Causal Perspective
    John Miller, Smitha Milli, Moritz Hardt
    http://arxiv.org/abs/1910.10362v1

    • [cs.LG]USTAR: Online Multimodal Embedding for Modeling User-Guided Spatiotemporal Activity
    Amila Silva, Shanika Karunasekera, Christopher Leckie, Ling Luo
    http://arxiv.org/abs/1910.10335v1

    • [cs.LG]Weighted Distributed Differential Privacy ERM: Convex and Non-convex
    Yilin Kang, Yong Liu, Weiping Wang
    http://arxiv.org/abs/1910.10308v1

    • [cs.LO]Knowledge of Uncertain Worlds: Programming with Logical Constraints
    Yanhong A. Liu, Scott D. Stoller
    http://arxiv.org/abs/1910.10346v1

    • [cs.NE]A Novel Generalized Artificial Neural Network for Mining Two-Class Datasets
    Wei-Chang Yeh
    http://arxiv.org/abs/1910.10461v1

    • [cs.NE]Autoencoding with XCSF
    Richard J. Preen, Stewart W. Wilson, Larry Bull
    http://arxiv.org/abs/1910.10579v1

    • [cs.NE]Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis
    Andrew Lensen, Bing Xue, Mengjie Zhang
    http://arxiv.org/abs/1910.10264v1

    • [cs.RO]An Analytical Lidar Sensor Model Based on Ray Path Information
    Alexander Schaefer, Lukas Luft, Wolfram Burgard
    http://arxiv.org/abs/1910.10469v1

    • [cs.RO]Closed-Form Full Map Posteriors for Robot Localization with Lidar Sensors
    Lukas Luft, Alexander Schaefer, Tobias Schubert, Wolfram Burgard
    http://arxiv.org/abs/1910.10493v1

    • [cs.RO]Impact-Aware Online Motion Planning for Fully-Actuated Bipedal Robot Walking
    Yuan Gao, Xingye Da, Yan Gu
    http://arxiv.org/abs/1910.10633v1

    • [cs.RO]Learning Deep Parameterized Skills from Demonstration for Re-targetable Visuomotor Control
    Jonathan Chang, Nishanth Kumar, Sean Hastings, Aaron Gokaslan, Diego Romeres, Devesh Jha, Daniel Nikovski, George Konidaris, Stefanie Tellex
    http://arxiv.org/abs/1910.10628v1

    • [cs.RO]Learning Humanoid Robot Running Skills through Proximal Policy Optimization
    Luckeciano C. Melo, Marcos R. O. A. Maximo
    http://arxiv.org/abs/1910.10620v1

    • [cs.RO]Long-Term Urban Vehicle Localization Using Pole Landmarks Extracted from 3-D Lidar Scans
    Alexander Schaefer, Daniel Büscher, Johan Vertens, Lukas Luft, Wolfram Burgard
    http://arxiv.org/abs/1910.10550v1

    • [cs.RO]Teach Biped Robots to Walk via Gait Principles and Reinforcement Learning with Adversarial Critics
    Kuangen Zhang, Zhimin Hou, Clarence W. de Silva, Haoyong Yu, Chenglong Fu
    http://arxiv.org/abs/1910.10194v1

    • [cs.RO]gradSLAM: Dense SLAM meets Automatic Differentiation
    Krishna Murthy Jatavallabhula, Ganesh Iyer, Liam Paull
    http://arxiv.org/abs/1910.10672v1

    • [cs.SD]Filterbank design for end-to-end speech separation
    Manuel Pariente, Samuele Cornell, Antoine Deleforge, Emmanuel Vincent
    http://arxiv.org/abs/1910.10400v1

    • [cs.SD]Learning the helix topology of musical pitch
    Vincent Lostanlen, Sripathi Sridhar, Brian McFee, Andrew Farnsworth, Juan Pablo Bello
    http://arxiv.org/abs/1910.10246v1

    • [cs.SE]Kuksa: A Cloud-Native Architecture for Enabling Continuous Delivery in the Automotive Domain
    Ahmad Banijamali, Pooyan Jamshidi, Pasi Kuvaja, Markku Oivo
    http://arxiv.org/abs/1910.10190v1

    • [cs.SI]Network2Vec Learning Node Representation Based on Space Mapping in Networks
    Huang Zhenhua, Wang Zhenyu, Zhang Rui, Zhao Yangyang, Xie Xiaohui, Sharad Mehrotra
    http://arxiv.org/abs/1910.10379v1

    • [econ.GN]Beating the House: Identifying Inefficiencies in Sports Betting Markets
    Sathya Ramesh, Ragib Mostofa, Marco Bornstein, John Dobelman
    http://arxiv.org/abs/1910.08858v2

    • [eess.AS]A Transformer with Interleaved Self-attention and Convolution for Hybrid Acoustic Models
    Liang Lu
    http://arxiv.org/abs/1910.10352v1

    • [eess.IV]A Deep Learning based Pipeline for Efficient Oral Cancer Screening on Whole Slide Images
    Jiahao Lu, Nataša Sladoje, Christina Runow Stark, Eva Darai Ramqvist, Jan-Michaél Hirsch, Joakim Lindblad
    http://arxiv.org/abs/1910.10549v1

    • [eess.IV]Deep Clustering of Compressed Variational Embeddings
    Suya Wu, Enmao Diao, Jie Ding, Vahid Tarokh
    http://arxiv.org/abs/1910.10341v1

    • [eess.IV]Deep Learning Supersampled Scanning Transmission Electron Microscopy
    Jeffrey M. Ede
    http://arxiv.org/abs/1910.10467v1

    • [eess.IV]Deep generative model-driven multimodal prostate segmentation in radiotherapy
    Kibrom Berihu Girum, Gilles Créhange, Raabid Hussain, Paul Michael Walker, Alain Lalande
    http://arxiv.org/abs/1910.10542v1

    • [eess.IV]Divide-and-Conquer Adversarial Learning for High-Resolution Image and Video Enhancement
    Zhiwu Huang, Danda Pani Paudel, Guanju Li, Jiqing Wu, Radu Timofte, Luc Van Gool
    http://arxiv.org/abs/1910.10455v1

    • [eess.IV]INTEL-TAU: A Color Constancy Dataset
    Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Jarno Nikkanen, Moncef Gabbouj
    http://arxiv.org/abs/1910.10404v1

    • [eess.IV]Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands
    Hans Pinckaers, Geert Litjens
    http://arxiv.org/abs/1910.10470v1

    • [eess.IV]Photoshopping Colonoscopy Video Frames
    Yuyuan Liu, Yu Tian, Gabriel Maicas, Leonardo Z. C. T. Pu, Rajvinder Singh, Johan W. Verjans, Gustavo Carneiro
    http://arxiv.org/abs/1910.10345v1

    • [eess.IV]Semantic Segmentation of Skin Lesions using a Small Data Set
    Beril Sirmacek, Max Kivits
    http://arxiv.org/abs/1910.10534v1

    • [eess.IV]Stain Style Transfer using Transitive Adversarial Networks
    Shaojin Cai, Yuyang Xue3 Qinquan Gao, Min Du, Gang Chen, Hejun Zhang, Tong Tong
    http://arxiv.org/abs/1910.10330v1

    • [eess.IV]Towards an Intelligent Microscope: adaptively learned illumination for optimal sample classification
    Amey Chaware, Colin L. Cooke, Kanghyun Kim, Roarke Horstmeyer
    http://arxiv.org/abs/1910.10209v1

    • [eess.SP]New RLL Code with Improved Error Performance for Visible Light Communication
    Vitalio Alfonso Reguera
    http://arxiv.org/abs/1910.10079v2

    • [eess.SY]Decentralized Runtime Synthesis of Shields for Multi-Agent Systems
    Dhananjay Raju, Suda Bharadwaj, Ufuk Topcu
    http://arxiv.org/abs/1910.10380v1

    • [eess.SY]Prioritized Inverse Kinematics: Desired Task Trajectories in Nonsingular Task Spaces
    Sang-ik An, Dongheui Lee
    http://arxiv.org/abs/1910.10300v1

    • [math.NA]Kernel Methods for Bayesian Elliptic Inverse Problems on Manifolds
    John Harlim, Daniel Sanz-Alonso, Ruiyi Yang
    http://arxiv.org/abs/1910.10669v1

    • [math.OC]Accelerated Primal-Dual Algorithms for Distributed Smooth Convex Optimization over Networks
    Jinming Xu, Ye Tian, Ying Sun, Gesualdo Scutari
    http://arxiv.org/abs/1910.10666v1

    • [math.ST]How well can we learn large factor models without assuming strong factors?
    Yinchu Zhu
    http://arxiv.org/abs/1910.10382v1

    • [math.ST]Minimax Rate Optimal Adaptive Nearest Neighbor Classification and Regression
    Puning Zhao, Lifeng Lai
    http://arxiv.org/abs/1910.10513v1

    • [math.ST]Multiple outlier detection tests for parametric models
    Vilijandas Bagdonavicius, Linas Petkevicius
    http://arxiv.org/abs/1910.10426v1

    • [math.ST]Objective Bayesian Analysis of a Cokriging Model for Hierarchical Multifidelity Codes
    Pulong Ma
    http://arxiv.org/abs/1910.10225v1

    • [math.ST]On the behavior of the DFA and DCCA in trend-stationary processes
    Taiane Schaedler Prass, Guilherme Pumi
    http://arxiv.org/abs/1910.10589v1

    • [physics.ao-ph]Tropical Cyclone Track Forecasting using Fused Deep Learning from Aligned Reanalysis Data
    Sophie Giffard-Roisin, Mo Yang, Guillaume Charpiat, Christina Kumler-Bonfanti, Balázs Kégl, Claire Monteleoni
    http://arxiv.org/abs/1910.10566v1

    • [physics.ins-det]Towards Fast Displaced Vertex Finding
    Kim Albertsson, Federico Meloni
    http://arxiv.org/abs/1910.10508v1

    • [q-bio.NC]Working memory facilitates reward-modulated Hebbian learning in recurrent neural networks
    Roman Pogodin, Dane Corneil, Alexander Seeholzer, Joseph Heng, Wulfram Gerstner
    http://arxiv.org/abs/1910.10559v1

    • [q-bio.PE]Inference with selection, varying population size and evolving population structure: Application of ABC to a forward-backward coalescent process with interactions
    Clotilde Lepers, Sylvain Billiard, Matthieu Porte, Sylvie Méléard, Viet Chi Tran
    http://arxiv.org/abs/1910.10201v1

    • [stat.AP]An inverse problem approach to the probabilistic reconstruction of particle tracks on a censored and closed surface
    Yunjiao Lu, Pierre Hodara, Charles Kervrann, Alain Trubuil
    http://arxiv.org/abs/1910.10432v1

    • [stat.AP]Double-Counting Problem of the Bonus-Malus System
    Rosy Oh, Kyung Suk Lee, Sojung C. Park, Jae Youn Ahn
    http://arxiv.org/abs/1910.10313v1

    • [stat.AP]Statistical Modeling for Spatio-Temporal Data from Physical Convection-Diffusion Processes
    Xiao Liu, Kyongmin Yeo, Siyuan Lu
    http://arxiv.org/abs/1910.10375v1

    • [stat.CO]Event-scheduling algorithms with Kalikow decomposition for simulating potentially infinite neuronal networks
    Tien Cuong Phi, Alexandre Muzy, Patricia Reynaud-Bouret
    http://arxiv.org/abs/1910.10576v1

    • [stat.ME]A Stochastic Block Model for Multilevel Networks: Application to the Sociology of Organisations
    Saint-Clair Chabert-Liddell, Pierre Barbillon, Sophie Donnet, Emmanuel Lazega
    http://arxiv.org/abs/1910.10512v1

    • [stat.ME]Bayesian nonparametric temporal dynamic clustering via autoregressive Dirichlet priors
    Maria De Iorio, Stefano Favaro, Alessandra Guglielmi, Lifeng Ye
    http://arxiv.org/abs/1910.10443v1

    • [stat.ME]Doubly robust treatment effect estimation with missing attributes
    Imke Mayer, Stefan Wager, Tobias Gauss, Jean-Denis Moyer, Julie Josse
    http://arxiv.org/abs/1910.10624v1

    • [stat.ME]Flexible Bayesian modelling in dichotomous item response theory using mixtures of skewed item curves
    Flávio B. Gonçalves, Juliane Venturelli, Rosangela H. Loschi
    http://arxiv.org/abs/1910.10233v1

    • [stat.ME]Nested Conformal Prediction and the Generalized Jackknife+
    Arun K. Kuchibhotla, Aaditya K. Ramdas
    http://arxiv.org/abs/1910.10562v1

    • [stat.ML]Deterministic tensor completion with hypergraph expanders
    Kameron Decker Harris, Yizhe Zhu
    http://arxiv.org/abs/1910.10692v1

    • [stat.ML]Global Capacity Measures for Deep ReLU Networks via Path Sampling
    Ryan Theisen, Jason M. Klusowski, Huan Wang, Nitish Shirish Keskar, Caiming Xiong, Richard Socher
    http://arxiv.org/abs/1910.10245v1

    • [stat.ML]Leveraging directed causal discovery to detect latent common causes
    Ciarán M. Lee, Christopher Hart, Jonathan G. Richens, Saurabh Johri
    http://arxiv.org/abs/1910.10174v1

    • [stat.ML]Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small Molecules
    Benjamin Sanchez-Lengeling, Jennifer N. Wei, Brian K. Lee, Richard C. Gerkin, Alán Aspuru-Guzik, Alexander B. Wiltschko
    http://arxiv.org/abs/1910.10685v1

    • [stat.ML]Neural Execution of Graph Algorithms
    Petar Veličković, Rex Ying, Matilde Padovano, Raia Hadsell, Charles Blundell
    http://arxiv.org/abs/1910.10593v1

    • [stat.ML]Sparse Orthogonal Variational Inference for Gaussian Processes
    Jiaxin Shi, Michalis K. Titsias, Andriy Mnih
    http://arxiv.org/abs/1910.10596v1

    • [stat.ML]Unifying Variational Inference and PAC-Bayes for Supervised Learning that Scales
    Sanjay Thakur, Herke Van Hoof, Gunshi Gupta, David Meger
    http://arxiv.org/abs/1910.10367v1