cs.AI - 人工智能

    cs.CC - 计算复杂度 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.MA - 多代理系统 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 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.ST - 统计理论 physics.comp-ph - 计算物理学 physics.soc-ph - 物理学与社会 q-bio.QM - 定量方法 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]Decision Automation for Electric Power Network Recovery
    • [cs.AI]The Choice Function Framework for Online Policy Improvement
    • [cs.CC]TE-ETH: Lower Bounds for QBFs of Bounded Treewidth
    • [cs.CL]A CCG-based Compositional Semantics and Inference System for Comparatives
    • [cs.CL]Abstractive Dialog Summarization with Semantic Scaffolds
    • [cs.CL]BookQA: Stories of Challenges and Opportunities
    • [cs.CL]Clinical Text Generation through Leveraging Medical Concept and Relations
    • [cs.CL]DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
    • [cs.CL]DyKgChat: Benchmarking Dialogue Generation Grounding on Dynamic Knowledge Graphs
    • [cs.CL]Essentia: Mining Domain-specific Paraphrases with Word-Alignment Graphs
    • [cs.CL]Exploiting BERT for End-to-End Aspect-based Sentiment Analysis
    • [cs.CL]Global Voices: Crossing Borders in Automatic News Summarization
    • [cs.CL]Grammatical Error Correction in Low-Resource Scenarios
    • [cs.CL]Hierarchical Multi-Task Natural Language Understanding for Cross-domain Conversational AI: HERMIT NLU
    • [cs.CL]Learning to estimate label uncertainty for automatic radiology report parsing
    • [cs.CL]Neural Word Decomposition Models for Abusive Language Detection
    • [cs.CL]Speech-to-speech Translation between Untranscribed Unknown Languages
    • [cs.CL]State-of-the-Art Speech Recognition Using Multi-Stream Self-Attention With Dilated 1D Convolutions
    • [cs.CL]SummAE: Zero-Shot Abstractive Text Summarization using Length-Agnostic Auto-Encoders
    • [cs.CR]ChainSplitter: Towards Blockchain-based Industrial IoT Architecture for Supporting Hierarchical Storage
    • [cs.CR]Detecting and Characterizing Lateral Phishing at Scale
    • [cs.CR]Teaching Hardware Reverse Engineering: Educational Guidelines and Practical Insights
    • [cs.CV]A Computationally Efficient Pipeline Approach to Full Page Offline Handwritten Text Recognition
    • [cs.CV]A Pre-defined Sparse Kernel Based Convolutionfor Deep CNNs
    • [cs.CV]Animating Face using Disentangled Audio Representations
    • [cs.CV]Automated Crabgrass Detection in Aerial Imagery with Context
    • [cs.CV]Bio-Inspired Foveated Technique for Augmented-Range Vehicle Detection Using Deep Neural Networks
    • [cs.CV]Boosting Image Recognition with Non-differentiable Constraints
    • [cs.CV]CNN-based Semantic Segmentation using Level Set Loss
    • [cs.CV]Joint Learning of Semantic Alignment and Object Landmark Detection
    • [cs.CV]Object Parsing in Sequences Using CoordConv Gated Recurrent Networks
    • [cs.CV]Privacy-preserving Federated Brain Tumour Segmentation
    • [cs.CV]RITnet: Real-time Semantic Segmentation of the Eye for Gaze Tracking
    • [cs.CV]Temporal Multimodal Fusion for Driver Behavior Prediction Tasks using Gated Recurrent Fusion Units
    • [cs.CV]Training Kinetics in 15 Minutes: Large-scale Distributed Training on Videos
    • [cs.CV]Unsupervised Doodling and Painting with Improved SPIRAL
    • [cs.CV]Unsupervised Projection Networks for Generative Adversarial Networks
    • [cs.CY]Race and Religion in Online Abuse towards UK Politicians: Working Paper
    • [cs.CY]Reviewing National Cybersecurity Awareness for Users and Executives in Africa
    • [cs.DB]A Blueprint For Interoperable Blockhains
    • [cs.DB]SharPer: Sharding Permissioned Blockchains Over Network Clusters
    • [cs.DC]Research Intelligence (CRIS) and the Cloud: A Review
    • [cs.DC]Scheduling Stochastic Real-Time Coflows in Unreliable Computing Machines
    • [cs.DC]Thread Homeostasis: Real-Time Anomalous Behavior Detection for Safety-Critical Software
    • [cs.DS]Streaming Balanced Clustering
    • [cs.IR]The merits of Universal Language Model Fine-tuning for Small Datasets — a case with Dutch book reviews
    • [cs.IT]A Self-contained Analysis of the Lempel-Ziv Compression Algorithm
    • [cs.IT]Age of Information with Finite Horizon and Partial Updates
    • [cs.IT]Beamspace Channel Estimation for Massive MIMO mmWave Systems: Algorithm and VLSI Design
    • [cs.IT]Deep Learning for Communication over Dispersive Nonlinear Channels: Performance and Comparison with Classical Digital Signal Processing
    • [cs.IT]MIMO Assisted Networks Relying on Large Intelligent Surfaces: A Stochastic Geometry Model
    • [cs.IT]On the Optimality of Reconfigurable Intelligent Surfaces (RISs): Passive Beamforming, Modulation, and Resource Allocation
    • [cs.IT]Optimizing the Transition Waste in Coded Elastic Computing
    • [cs.IT]Performance Analysis and Design of Non-orthogonal Multiple Access for Wireless Communications
    • [cs.IT]Potential Key Technologies for 6G Mobile Communications
    • [cs.IT]Probabilistic MIMO Symbol Detection with Expectation Consistency Approximate Inference
    • [cs.LG]A Deep Factorization of Style and Structure in Fonts
    • [cs.LG]Accelerating Deep Learning by Focusing on the Biggest Losers
    • [cs.LG]Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning
    • [cs.LG]An Introduction to Probabilistic Spiking Neural Networks
    • [cs.LG]Benchmarking machine learning models on eICU critical care dataset
    • [cs.LG]BioNLP-OST 2019 RDoC Tasks: Multi-grain Neural Relevance Ranking Using Topics and Attention Based Query-Document-Sentence Interactions
    • [cs.LG]CWAE-IRL: Formulating a supervised approach to Inverse Reinforcement Learning problem
    • [cs.LG]Concept Drift Detection and Adaptation with Weak Supervision on Streaming Unlabeled Data
    • [cs.LG]ConfusionFlow: A model-agnostic visualization for temporal analysis of classifier confusion
    • [cs.LG]Contextual Local Explanation for Black Box Classifiers
    • [cs.LG]Deep Lifetime Clustering
    • [cs.LG]DiffTaichi: Differentiable Programming for Physical Simulation
    • [cs.LG]Efficient Graph Generation with Graph Recurrent Attention Networks
    • [cs.LG]Forecasting Chaotic Systems with Very Low Connectivity Reservoir Computers
    • [cs.LG]Formal Language Constraints for Markov Decision Processes
    • [cs.LG]Generating Semantic Adversarial Examples with Differentiable Rendering
    • [cs.LG]IEG: Robust Neural Network Training to Tackle Severe Label Noise
    • [cs.LG]Identifying Weights and Architectures of Unknown ReLU Networks
    • [cs.LG]Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks
    • [cs.LG]Learning Maximally Predictive Prototypes in Multiple Instance Learning
    • [cs.LG]NESTA: Hamming Weight Compression-Based Neural Proc. Engine
    • [cs.LG]On the estimation of the Wasserstein distance in generative models
    • [cs.LG]Quantized Reinforcement Learning (QUARL)
    • [cs.LG]Randomized Ablation Feature Importance
    • [cs.LG]Re-balancing Variational Autoencoder Loss for Molecule Sequence Generation
    • [cs.LG]Robust Few-Shot Learning with Adversarially Queried Meta-Learners
    • [cs.LG]SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum
    • [cs.LG]Stabilizing Off-Policy Reinforcement Learning with Conservative Policy Gradients
    • [cs.LG]Structural Language Models for Any-Code Generation
    • [cs.LG]Task-Relevant Adversarial Imitation Learning
    • [cs.LG]TransGCN:Coupling Transformation Assumptions with Graph Convolutional Networks for Link Prediction
    • [cs.LG]Variational Temporal Abstraction
    • [cs.LG]Ward2ICU: A Vital Signs Dataset of Inpatients from the General Ward
    • [cs.LG]Wasserstein Neural Processes
    • [cs.MA]Cognitive Agent Based Simulation Model For Improving Disaster Response Procedures
    • [cs.MA]Emergence of Writing Systems Through Multi-Agent Cooperation
    • [cs.NE]Design Space Exploration of Hardware Spiking Neurons for Embedded Artificial Intelligence
    • [cs.NE]Optimising Optimisers with Push GP
    • [cs.NI]A Survey of Big Data Machine Learning Applications Optimization in Cloud Data Centers and Networks
    • [cs.RO]Accelerated Robot Learning via Human Brain Signals
    • [cs.RO]Action Anticipation for Collaborative Environments: The Impact of Contextual Information and Uncertainty-Based Prediction
    • [cs.RO]Adaptive Continuous Visual Odometry from RGB-D Images
    • [cs.RO]Area Graph: Generation of Topological Maps using the Voronoi Diagram
    • [cs.RO]Deploying the NASA Valkyrie Humanoid for IED Response: An Initial Approach and Evaluation Summary
    • [cs.RO]Estimating Lower Limb Kinematics using a Reduced Wearable Sensor Count
    • [cs.RO]Learning Continuous 3D Reconstructions for Geometrically Aware Grasping
    • [cs.RO]LiTE: Light-field Transparency Estimation for Refractive Object Localization
    • [cs.RO]Motion Decoupling and Composition via Reduced Order Model Optimization for Dynamic Humanoid Walking with CLF-QP based Active Force Control
    • [cs.RO]Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGB-D video
    • [cs.RO]Online Trajectory Planning Through Combined Trajectory Optimization and Function Approximation: Application to the Exoskeleton Atalante
    • [cs.RO]Orbit Characterization, Stabilization and Composition on 3D Underactuated Bipedal Walking via Hybrid Passive Linear Inverted Pendulum Model
    • [cs.RO]Pose Estimation for Omni-directional Cameras using Sinusoid Fitting
    • [cs.RO]ROS Rescue : Fault Tolerance System for Robot Operating System
    • [cs.RO]Robust Data-Driven Zero-Velocity Detection for Foot-Mounted Inertial Navigation
    • [cs.RO]TagSLAM: Robust SLAM with Fiducial Markers
    • [cs.RO]The OpenUAV Swarm Simulation Testbed: a Collaborative DesignStudio for Field Robotics
    • [cs.SI]Quantifying Voter Biases in Online Platforms: An Instrumental Variable Approach
    • [cs.SI]Retrieving Top Weighted Triangles in Graphs
    • [econ.EM]An introduction to flexible methods for policy evaluation
    • [eess.IV]Comparing Deep Learning Models for Multi-cell Classification in Liquid-based Cervical Cytology Images
    • [eess.IV]Deep learning within a priori temporal feature spaces for large-scale dynamic MR image reconstruction: Application to 5-D cardiac MR Multitasking
    • [eess.IV]Empirical evaluation of full-reference image quality metrics on MDID database
    • [eess.IV]Enhancing high-content imaging for studying microtubule networks at large-scale
    • [eess.IV]Improvement of Multiparametric MR Image Segmentation by Augmenting the Data with Generative Adversarial Networks for Glioma Patients
    • [eess.IV]W-Net: A CNN-based Architecture for White Blood Cells Image Classification
    • [eess.SP]A Machine Learning framework for Sleeping Cell Detection in a Smart-city IoT Telecommunications Infrastructure
    • [eess.SP]Deep 3D Pan via adaptive “t-shaped” convolutions with global and local adaptive dilations
    • [eess.SP]Near-Convex Archetypal Analysis
    • [eess.SY]An Iterative Quadratic Method for General-Sum Differential Games with Feedback Linearizable Dynamics
    • [eess.SY]Synthesis of Orchestrations and Choreographies: Bridging the Gap between Supervisory Control and Coordination of Services
    • [math.OC]Global exponential stability of primal-dual gradient flow dynamics based on the proximal augmented Lagrangian: A Lyapunov-based approach
    • [math.ST]A deterministic theory of low rank matrix completion
    • [math.ST]Covariance Matrix Estimation with Non Uniform and Data Dependent Missing Observations
    • [math.ST]Non-algorithmic theory of randomness
    • [math.ST]Non-uniform Berry-Esseen Bound by Unbounded Exchangeable Pair Approach
    • [math.ST]Parameter estimation for SPDEs based on discrete observations in time and space
    • [math.ST]Series Representation of Jointly S$α$S Distribution via A New Type of Symmetric Covariations
    • [math.ST]The Balakrishnan Alpha Skew Laplace Distribution: Properties and Its Applications
    • [physics.comp-ph]Deep learning at scale for subgrid modeling in turbulent flows
    • [physics.soc-ph]A machine learning approach to predicting dynamical observables from network structure
    • [physics.soc-ph]Prediction of citation dynamics of individual papers
    • [q-bio.QM]Identifying Cancer Patients at Risk for Heart Failure Using Machine Learning Methods
    • [stat.AP]Monotonic Nonparametric Dose Response Model
    • [stat.ME]Fast and Fair Simultaneous Confidence Bands for Functional Parameters
    • [stat.ME]Minimax D-optimal designs for multivariate regression models with multi-factors
    • [stat.ME]Robust Bayesian Regression with Synthetic Posterior
    • [stat.ML]A note on the consistency of the random forest algorithm
    • [stat.ML]Equivariant Flows: sampling configurations for multi-body systems with symmetric energies
    • [stat.ML]Learning Neural Causal Models from Unknown Interventions
    • [stat.ML]Order-Independent Structure Learning of Multivariate Regression Chain Graphs
    • [stat.ML]Reconsidering Analytical Variational Bounds for Output Layers of Deep Networks
    • [stat.ML]Scalable approximate inference for state space models with normalising flows
    • [stat.ML]Towards Unifying Neural Architecture Space Exploration and Generalization

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

    • [cs.AI]Decision Automation for Electric Power Network Recovery
    Yugandhar Sarkale, Saeed Nozhati, Edwin K. P. Chong, Bruce R. Ellingwood
    http://arxiv.org/abs/1910.00699v1

    • [cs.AI]The Choice Function Framework for Online Policy Improvement
    Murugeswari Issakkimuthu, Alan Fern, Prasad Tadepalli
    http://arxiv.org/abs/1910.00614v1

    • [cs.CC]TE-ETH: Lower Bounds for QBFs of Bounded Treewidth
    Johannes Klaus Fichte, Markus Hecher, Andreas Pfandler
    http://arxiv.org/abs/1910.01047v1

    • [cs.CL]A CCG-based Compositional Semantics and Inference System for Comparatives
    Izumi Haruta, Koji Mineshima, Daisuke Bekki
    http://arxiv.org/abs/1910.00930v1

    • [cs.CL]Abstractive Dialog Summarization with Semantic Scaffolds
    Lin Yuan, Zhou Yu
    http://arxiv.org/abs/1910.00825v1

    • [cs.CL]BookQA: Stories of Challenges and Opportunities
    Stefanos Angelidis, Lea Frermann, Diego Marcheggiani, Roi Blanco, Lluís Màrquez
    http://arxiv.org/abs/1910.00856v1

    • [cs.CL]Clinical Text Generation through Leveraging Medical Concept and Relations
    Wangjin Lee, Hyeryun Park, Jooyoung Yoon, Kyeongmo Kim, Jinwook Choi
    http://arxiv.org/abs/1910.00861v1

    • [cs.CL]DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
    Victor Sanh, Lysandre Debut, Julien Chaumond, Thomas Wolf
    http://arxiv.org/abs/1910.01108v1

    • [cs.CL]DyKgChat: Benchmarking Dialogue Generation Grounding on Dynamic Knowledge Graphs
    Yi-Lin Tuan, Yun-Nung Chen, Hung-yi Lee
    http://arxiv.org/abs/1910.00610v1

    • [cs.CL]Essentia: Mining Domain-specific Paraphrases with Word-Alignment Graphs
    Danni Ma, Chen Chen, Behzad Golshan, Wang-Chiew Tan
    http://arxiv.org/abs/1910.00637v1

    • [cs.CL]Exploiting BERT for End-to-End Aspect-based Sentiment Analysis
    Xin Li, Lidong Bing, Wenxuan Zhang, Wai Lam
    http://arxiv.org/abs/1910.00883v1

    • [cs.CL]Global Voices: Crossing Borders in Automatic News Summarization
    Khanh Nguyen, Hal Daumé III
    http://arxiv.org/abs/1910.00421v2

    • [cs.CL]Grammatical Error Correction in Low-Resource Scenarios
    Jakub Náplava, Milan Straka
    http://arxiv.org/abs/1910.00353v2

    • [cs.CL]Hierarchical Multi-Task Natural Language Understanding for Cross-domain Conversational AI: HERMIT NLU
    Andrea Vanzo, Emanuele Bastianelli, Oliver Lemon
    http://arxiv.org/abs/1910.00912v1

    • [cs.CL]Learning to estimate label uncertainty for automatic radiology report parsing
    Tobi Olatunji, Li Yao
    http://arxiv.org/abs/1910.00673v1

    • [cs.CL]Neural Word Decomposition Models for Abusive Language Detection
    Sravan Babu Bodapati, Spandana Gella, Kasturi Bhattacharjee, Yaser Al-Onaizan
    http://arxiv.org/abs/1910.01043v1

    • [cs.CL]Speech-to-speech Translation between Untranscribed Unknown Languages
    Andros Tjandra, Sakriani Sakti, Satoshi Nakamura
    http://arxiv.org/abs/1910.00795v1

    • [cs.CL]State-of-the-Art Speech Recognition Using Multi-Stream Self-Attention With Dilated 1D Convolutions
    Kyu J. Han, Ramon Prieto, Kaixing Wu, Tao Ma
    http://arxiv.org/abs/1910.00716v1

    • [cs.CL]SummAE: Zero-Shot Abstractive Text Summarization using Length-Agnostic Auto-Encoders
    Peter J. Liu, Yu-An Chung, Jie Ren
    http://arxiv.org/abs/1910.00998v1

    • [cs.CR]ChainSplitter: Towards Blockchain-based Industrial IoT Architecture for Supporting Hierarchical Storage
    Gang Wang, Zhijie Jerry Shi, Mark Nixon, Song Han
    http://arxiv.org/abs/1910.00742v1

    • [cs.CR]Detecting and Characterizing Lateral Phishing at Scale
    Grant Ho, Asaf Cidon, Lior Gavish, Marco Schweighauser, Vern Paxson, Stefan Savage, Geoffrey M. Voelker, David Wagner
    http://arxiv.org/abs/1910.00790v1

    • [cs.CR]Teaching Hardware Reverse Engineering: Educational Guidelines and Practical Insights
    Carina Wiesen, Steffen Becker, Marc Fyrbiak, Nils Albartus, Malte Elson, Nikol Rummel, Christof Paar
    http://arxiv.org/abs/1910.00312v1

    • [cs.CV]A Computationally Efficient Pipeline Approach to Full Page Offline Handwritten Text Recognition
    Jonathan Chung, Thomas Delteil
    http://arxiv.org/abs/1910.00663v1

    • [cs.CV]A Pre-defined Sparse Kernel Based Convolutionfor Deep CNNs
    Souvik Kundu, Saurav Prakash, Haleh Akrami, Peter A. Beerel, Keith M. Chugg
    http://arxiv.org/abs/1910.00724v1

    • [cs.CV]Animating Face using Disentangled Audio Representations
    Gaurav Mittal, Baoyuan Wang
    http://arxiv.org/abs/1910.00726v1

    • [cs.CV]Automated Crabgrass Detection in Aerial Imagery with Context
    Delia Bullock, Andrew Mangeni, Tyr Wiesner-Hanks, Chad DeChant, Ethan L. Stewart, Nicholas Kaczmar, Rebecca J. Nelson, Michael A. Gore, Hod Lipson
    http://arxiv.org/abs/1910.00652v1

    • [cs.CV]Bio-Inspired Foveated Technique for Augmented-Range Vehicle Detection Using Deep Neural Networks
    Pedro Azevedo, Sabrina S. Panceri, Rânik Guidolini, Vinicius B. Cardoso, Claudine Badue, Thiago Oliveira-Santos, Alberto F. De Souza
    http://arxiv.org/abs/1910.00944v1

    • [cs.CV]Boosting Image Recognition with Non-differentiable Constraints
    Xuan Li, Yuchen Lu, Peng Xu, Jizong Peng, Christian Desrosiers, Xue Liu
    http://arxiv.org/abs/1910.00736v1

    • [cs.CV]CNN-based Semantic Segmentation using Level Set Loss
    Youngeun Kim, Seunghyeon Kim, Taekyung Kim, Changick Kim
    http://arxiv.org/abs/1910.00950v1

    • [cs.CV]Joint Learning of Semantic Alignment and Object Landmark Detection
    Sangryul Jeon, Dongbo Min, Seungryong Kim, Kwanghoon Sohn
    http://arxiv.org/abs/1910.00754v1

    • [cs.CV]Object Parsing in Sequences Using CoordConv Gated Recurrent Networks
    Ayush Gaud, Y V S Harish, K Madhava Krishna
    http://arxiv.org/abs/1910.00895v1

    • [cs.CV]Privacy-preserving Federated Brain Tumour Segmentation
    Wenqi Li, Fausto Milletarì, Daguang Xu, Nicola Rieke, Jonny Hancox, Wentao Zhu, Maximilian Baust, Yan Cheng, Sébastien Ourselin, M. Jorge Cardoso, Andrew Feng
    http://arxiv.org/abs/1910.00962v1

    • [cs.CV]RITnet: Real-time Semantic Segmentation of the Eye for Gaze Tracking
    Aayush K. Chaudhary, Rakshit Kothari, Manoj Acharya, Shusil Dangi, Nitinraj Nair, Reynold Bailey, Christopher Kanan, Gabriel Diaz, Jeff B. Pelz
    http://arxiv.org/abs/1910.00694v1

    • [cs.CV]Temporal Multimodal Fusion for Driver Behavior Prediction Tasks using Gated Recurrent Fusion Units
    Athma Narayanan, Avinash Siravuru, Behzad Dariush
    http://arxiv.org/abs/1910.00628v1

    • [cs.CV]Training Kinetics in 15 Minutes: Large-scale Distributed Training on Videos
    Ji Lin, Chuang Gan, Song Han
    http://arxiv.org/abs/1910.00932v1

    • [cs.CV]Unsupervised Doodling and Painting with Improved SPIRAL
    John F. J. Mellor, Eunbyung Park, Yaroslav Ganin, Igor Babuschkin, Tejas Kulkarni, Dan Rosenbaum, Andy Ballard, Theophane Weber, Oriol Vinyals, S. M. Ali Eslami
    http://arxiv.org/abs/1910.01007v1

    • [cs.CV]Unsupervised Projection Networks for Generative Adversarial Networks
    Daiyaan Arfeen, Jesse Zhang
    http://arxiv.org/abs/1910.00579v1

    • [cs.CY]Race and Religion in Online Abuse towards UK Politicians: Working Paper
    Genevieve Gorrell, Mehmet E. Bakir, Mark A. Greenwood, Ian Roberts, Kalina Bontcheva
    http://arxiv.org/abs/1910.00920v1

    • [cs.CY]Reviewing National Cybersecurity Awareness for Users and Executives in Africa
    Maria Bada, Basie von Solms, Ioannis Agrafiotis
    http://arxiv.org/abs/1910.01005v1

    • [cs.DB]A Blueprint For Interoperable Blockhains
    Tien Tuan Anh Dinh, Anwitaman Datta, Beng Chin Ooi
    http://arxiv.org/abs/1910.00985v1

    • [cs.DB]SharPer: Sharding Permissioned Blockchains Over Network Clusters
    Mohammad Javad Amiri, Divyakant Agrawal, Amr El Abbadi
    http://arxiv.org/abs/1910.00765v1

    • [cs.DC]Research Intelligence (CRIS) and the Cloud: A Review
    Otmane Azeroual, Joachim Schöpfel
    http://arxiv.org/abs/1910.00862v1

    • [cs.DC]Scheduling Stochastic Real-Time Coflows in Unreliable Computing Machines
    Yu-Pin Hsu
    http://arxiv.org/abs/1910.00916v1

    • [cs.DC]Thread Homeostasis: Real-Time Anomalous Behavior Detection for Safety-Critical Software
    Mohamed Alsharnouby, Anil Somayaji
    http://arxiv.org/abs/1910.01012v1

    • [cs.DS]Streaming Balanced Clustering
    Hossein Esfandiari, Vahab Mirrokni, Peilin Zhong
    http://arxiv.org/abs/1910.00788v1

    • [cs.IR]The merits of Universal Language Model Fine-tuning for Small Datasets — a case with Dutch book reviews
    Benjamin van der Burgh, Suzan Verberne
    http://arxiv.org/abs/1910.00896v1

    • [cs.IT]A Self-contained Analysis of the Lempel-Ziv Compression Algorithm
    Madhu Sudan, David Xiang
    http://arxiv.org/abs/1910.00941v1

    • [cs.IT]Age of Information with Finite Horizon and Partial Updates
    David Ramirez, Elza Erkip, H. Vincent Poor
    http://arxiv.org/abs/1910.00963v1

    • [cs.IT]Beamspace Channel Estimation for Massive MIMO mmWave Systems: Algorithm and VLSI Design
    Seyed Hadi Mirfarshbafan, Alexandra Gallyas-Sanhueza, Ramina Ghods, Christoph Studer
    http://arxiv.org/abs/1910.00756v1

    • [cs.IT]Deep Learning for Communication over Dispersive Nonlinear Channels: Performance and Comparison with Classical Digital Signal Processing
    Boris Karanov, Gabriele Liga, Vahid Aref, Domaniç Lavery, Polina Bayvel, Laurent Schmalen
    http://arxiv.org/abs/1910.01028v1

    • [cs.IT]MIMO Assisted Networks Relying on Large Intelligent Surfaces: A Stochastic Geometry Model
    Tianwei Hou, Yuanwei Liu, Zhengyu Song, Xin Sun, Yue Chen, Lajos Hanzo
    http://arxiv.org/abs/1910.00959v1

    • [cs.IT]On the Optimality of Reconfigurable Intelligent Surfaces (RISs): Passive Beamforming, Modulation, and Resource Allocation
    Minchae Jung, Walid Saad, Merouane Debbah, Choong Seon Hong
    http://arxiv.org/abs/1910.00968v1

    • [cs.IT]Optimizing the Transition Waste in Coded Elastic Computing
    Hoang Dau, Ryan Gabrys, Yu-Chih Huang, Chen Feng, Quang-Hung Luu, Eidah Alzahrani, Zahir Tari
    http://arxiv.org/abs/1910.00796v1

    • [cs.IT]Performance Analysis and Design of Non-orthogonal Multiple Access for Wireless Communications
    Zhiqiang Wei
    http://arxiv.org/abs/1910.00946v1

    • [cs.IT]Potential Key Technologies for 6G Mobile Communications
    Yifei Yuan, Yajun Zhao, Baiqing Zong, Sergio Parolari
    http://arxiv.org/abs/1910.00730v1

    • [cs.IT]Probabilistic MIMO Symbol Detection with Expectation Consistency Approximate Inference
    Javier Cépedes, Pablo M. Olmos, Matilde Sánchez-Fernández, Fernando Pérez-Cruz
    http://arxiv.org/abs/1910.00853v1

    • [cs.LG]A Deep Factorization of Style and Structure in Fonts
    Akshay Srivatsan, Jonathan T. Barron, Dan Klein, Taylor Berg-Kirkpatrick
    http://arxiv.org/abs/1910.00748v1

    • [cs.LG]Accelerating Deep Learning by Focusing on the Biggest Losers
    Angela H. Jiang, Daniel L. -K. Wong, Giulio Zhou, David G. Andersen, Jeffrey Dean, Gregory R. Ganger, Gauri Joshi, Michael Kaminksy, Michael Kozuch, Zachary C. Lipton, Padmanabhan Pillai
    http://arxiv.org/abs/1910.00762v1

    • [cs.LG]Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning
    Xue Bin Peng, Aviral Kumar, Grace Zhang, Sergey Levine
    http://arxiv.org/abs/1910.00177v2

    • [cs.LG]An Introduction to Probabilistic Spiking Neural Networks
    Hyeryung Jang, Osvaldo Simeone, Brian Gardner, André Grüning
    http://arxiv.org/abs/1910.01059v1

    • [cs.LG]Benchmarking machine learning models on eICU critical care dataset
    Seyedmostafa Sheikhalishahi, Vevake Balaraman, Venet Osmani
    http://arxiv.org/abs/1910.00964v1

    • [cs.LG]BioNLP-OST 2019 RDoC Tasks: Multi-grain Neural Relevance Ranking Using Topics and Attention Based Query-Document-Sentence Interactions
    Yatin Chaudhary, Pankaj Gupta, Hinrich Schütze
    http://arxiv.org/abs/1910.00314v2

    • [cs.LG]CWAE-IRL: Formulating a supervised approach to Inverse Reinforcement Learning problem
    Arpan Kusari
    http://arxiv.org/abs/1910.00584v1

    • [cs.LG]Concept Drift Detection and Adaptation with Weak Supervision on Streaming Unlabeled Data
    Abhijit Suprem
    http://arxiv.org/abs/1910.01064v1

    • [cs.LG]ConfusionFlow: A model-agnostic visualization for temporal analysis of classifier confusion
    Andreas Hinterreiter, Peter Ruch, Holger Stitz, Martin Ennemoser, Jürgen Bernard, Hendrik Strobelt, Marc Streit
    http://arxiv.org/abs/1910.00969v1

    • [cs.LG]Contextual Local Explanation for Black Box Classifiers
    Zijian Zhang, Fan Yang, Haofan Wang, Xia Hu
    http://arxiv.org/abs/1910.00768v1

    • [cs.LG]Deep Lifetime Clustering
    S Chandra Mouli, Leonardo Teixeira, Jennifer Neville, Bruno Ribeiro
    http://arxiv.org/abs/1910.00547v2

    • [cs.LG]DiffTaichi: Differentiable Programming for Physical Simulation
    Yuanming Hu, Luke Anderson, Tzu-Mao Li, Qi Sun, Nathan Carr, Jonathan Ragan-Kelley, Frédo Durand
    http://arxiv.org/abs/1910.00935v1

    • [cs.LG]Efficient Graph Generation with Graph Recurrent Attention Networks
    Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, Charlie Nash, William L. Hamilton, David Duvenaud, Raquel Urtasun, Richard S. Zemel
    http://arxiv.org/abs/1910.00760v1

    • [cs.LG]Forecasting Chaotic Systems with Very Low Connectivity Reservoir Computers
    Aaron Griffith, Andrew Pomerance, Daniel J. Gauthier
    http://arxiv.org/abs/1910.00659v1

    • [cs.LG]Formal Language Constraints for Markov Decision Processes
    Eleanor Quint, Dong Xu, Haluk Dogan, Zeynep Hakguder, Stephen Scott, Matthew Dwyer
    http://arxiv.org/abs/1910.01074v1

    • [cs.LG]Generating Semantic Adversarial Examples with Differentiable Rendering
    Lakshya Jain, Wilson Wu, Steven Chen, Uyeong Jang, Varun Chandrasekaran, Sanjit Seshia, Somesh Jha
    http://arxiv.org/abs/1910.00727v1

    • [cs.LG]IEG: Robust Neural Network Training to Tackle Severe Label Noise
    Zizhao Zhang, Han Zhang, Sercan O. Arik, Honglak Lee, Tomas Pfister
    http://arxiv.org/abs/1910.00701v1

    • [cs.LG]Identifying Weights and Architectures of Unknown ReLU Networks
    David Rolnick, Konrad P. Kording
    http://arxiv.org/abs/1910.00744v1

    • [cs.LG]Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks
    Guillaume Salha, Romain Hennequin, Michalis Vazirgiannis
    http://arxiv.org/abs/1910.00942v1

    • [cs.LG]Learning Maximally Predictive Prototypes in Multiple Instance Learning
    Mert Yuksekgonul, Ozgur Emre Sivrikaya, Mustafa Gokce Baydogan
    http://arxiv.org/abs/1910.00965v1

    • [cs.LG]NESTA: Hamming Weight Compression-Based Neural Proc. Engine
    Ali Mirzaeian, Houman Homayoun, Avesta Sasan
    http://arxiv.org/abs/1910.00700v1

    • [cs.LG]On the estimation of the Wasserstein distance in generative models
    Thomas Pinetz, Daniel Soukup, Thomas Pock
    http://arxiv.org/abs/1910.00888v1

    • [cs.LG]Quantized Reinforcement Learning (QUARL)
    Srivatsan Krishnan, Sharad Chitlangia, Maximilian Lam, Zishen Lam, Aleksandra Faust, Vijay Janapa Reddi
    http://arxiv.org/abs/1910.01055v1

    • [cs.LG]Randomized Ablation Feature Importance
    Luke Merrick
    http://arxiv.org/abs/1910.00174v2

    • [cs.LG]Re-balancing Variational Autoencoder Loss for Molecule Sequence Generation
    Chaochao Yan, Sheng Wang, Jinyu Yang, Tingyang Xu, Junzhou Huang
    http://arxiv.org/abs/1910.00698v1

    • [cs.LG]Robust Few-Shot Learning with Adversarially Queried Meta-Learners
    Micah Goldblum, Liam Fowl, Tom Goldstein
    http://arxiv.org/abs/1910.00982v1

    • [cs.LG]SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum
    Jianyu Wang, Vinayak Tantia, Nicolas Ballas, Michael Rabbat
    http://arxiv.org/abs/1910.00643v1

    • [cs.LG]Stabilizing Off-Policy Reinforcement Learning with Conservative Policy Gradients
    Chen Tessler, Nadav Merlis, Shie Mannor
    http://arxiv.org/abs/1910.01062v1

    • [cs.LG]Structural Language Models for Any-Code Generation
    Uri Alon, Roy Sadaka, Omer Levy, Eran Yahav
    http://arxiv.org/abs/1910.00577v1

    • [cs.LG]Task-Relevant Adversarial Imitation Learning
    Konrad Zolna, Scott Reed, Alexander Novikov, Sergio Gomez Colmenarej, David Budden, Serkan Cabi, Misha Denil, Nando de Freitas, Ziyu Wang
    http://arxiv.org/abs/1910.01077v1

    • [cs.LG]TransGCN:Coupling Transformation Assumptions with Graph Convolutional Networks for Link Prediction
    Ling Cai, Bo Yan, Gengchen Mai, Krzysztof Janowicz, Rui Zhu
    http://arxiv.org/abs/1910.00702v1

    • [cs.LG]Variational Temporal Abstraction
    Taesup Kim, Sungjin Ahn, Yoshua Bengio
    http://arxiv.org/abs/1910.00775v1

    • [cs.LG]Ward2ICU: A Vital Signs Dataset of Inpatients from the General Ward
    Daniel Severo, Flávio Amaro, Estevam R. Hruschka Jr, André Soares de Moura Costa
    http://arxiv.org/abs/1910.00752v1

    • [cs.LG]Wasserstein Neural Processes
    Andrew Carr, Jared Nielson, David Wingate
    http://arxiv.org/abs/1910.00668v1

    • [cs.MA]Cognitive Agent Based Simulation Model For Improving Disaster Response Procedures
    Rohit K. Dubey, Samuel S. Sohn, Christoph Hoelscher, Mubbasir Kapadia
    http://arxiv.org/abs/1910.00767v1

    • [cs.MA]Emergence of Writing Systems Through Multi-Agent Cooperation
    Shresth Verma, Joydip Dhar
    http://arxiv.org/abs/1910.00741v1

    • [cs.NE]Design Space Exploration of Hardware Spiking Neurons for Embedded Artificial Intelligence
    Nassim Abderrahmane, Edgar Lemaire, Benoît Miramond
    http://arxiv.org/abs/1910.01010v1

    • [cs.NE]Optimising Optimisers with Push GP
    Michael Lones
    http://arxiv.org/abs/1910.00945v1

    • [cs.NI]A Survey of Big Data Machine Learning Applications Optimization in Cloud Data Centers and Networks
    Sanaa Hamid Mohamed, Taisir E. H. El-Gorashi, Jaafar M. H. Elmirghani
    http://arxiv.org/abs/1910.00731v1

    • [cs.RO]Accelerated Robot Learning via Human Brain Signals
    Iretiayo Akinola, Zizhao Wang, Junyao Shi, Xiaomin He, Pawan Lapborisuth, Jingxi Xu, David Watkins-Valls, Paul Sajda, Peter Allen
    http://arxiv.org/abs/1910.00682v1

    • [cs.RO]Action Anticipation for Collaborative Environments: The Impact of Contextual Information and Uncertainty-Based Prediction
    Clebeson Canuto dos Santos, Plinio Moreno, Jorge Leonide Aching Samatelo, Raquel Frizera Vassallo, José Santos-Victor
    http://arxiv.org/abs/1910.00714v1

    • [cs.RO]Adaptive Continuous Visual Odometry from RGB-D Images
    Tzu-Yuan Lin, William Clark, Ryan M. Eustice, Jessy W. Grizzle, Anthony Bloch, Maani Ghaffari
    http://arxiv.org/abs/1910.00713v1

    • [cs.RO]Area Graph: Generation of Topological Maps using the Voronoi Diagram
    Jiawei Hou, Yijun Yuan, Sören Schwertfeger
    http://arxiv.org/abs/1910.01019v1

    • [cs.RO]Deploying the NASA Valkyrie Humanoid for IED Response: An Initial Approach and Evaluation Summary
    Steven Jens Jorgensen, Michael W. Lanighan, Sylvain S. Bertrand, Andrew Watson, Joseph S. Altemus, R. Scott Askew, Lyndon Bridgwater, Beau Domingue, Charlie Kendrick, Jason Lee, Mark Paterson, Jairo Sanchez, Patrick Beeson, Seth Gee, Stephen Hart, Ana Huaman Quispe, Robert Griffin, Inho Lee, Stephen McCrory, Luis Sentis, Jerry Pratt, Joshua S. Mehling
    http://arxiv.org/abs/1910.00761v1

    • [cs.RO]Estimating Lower Limb Kinematics using a Reduced Wearable Sensor Count
    Luke Sy, Michael Raitor, Michael Del Rosario, Heba Khamis, Lauren Kark, Nigel H. Lovell, Stephen J. Redmond
    http://arxiv.org/abs/1910.00910v1

    • [cs.RO]Learning Continuous 3D Reconstructions for Geometrically Aware Grasping
    Mark Van der Merwe, Qingkai Lu, Balakumar Sundaralingam, Martin Matak, Tucker Hermans
    http://arxiv.org/abs/1910.00983v1

    • [cs.RO]LiTE: Light-field Transparency Estimation for Refractive Object Localization
    Zheming Zhou, Xiaotong Chen, Odest Chadwicke Jenkins
    http://arxiv.org/abs/1910.00721v1

    • [cs.RO]Motion Decoupling and Composition via Reduced Order Model Optimization for Dynamic Humanoid Walking with CLF-QP based Active Force Control
    Xiaobin Xiong, Aaron Ames
    http://arxiv.org/abs/1910.00687v1

    • [cs.RO]Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGB-D video
    Maria Bauza, Ferran Alet, Yen-Chen Lin, Tomas Lozano-Perez, Leslie P. Kaelbling, Phillip Isola, Alberto Rodriguez
    http://arxiv.org/abs/1910.00618v1

    • [cs.RO]Online Trajectory Planning Through Combined Trajectory Optimization and Function Approximation: Application to the Exoskeleton Atalante
    Alexis Duburcq, Yann Chevaleyre, Nicolas Bredeche, Guilhem Boéris
    http://arxiv.org/abs/1910.00514v2

    • [cs.RO]Orbit Characterization, Stabilization and Composition on 3D Underactuated Bipedal Walking via Hybrid Passive Linear Inverted Pendulum Model
    Xiaobin Xiong, Aaron Ames
    http://arxiv.org/abs/1910.00684v1

    • [cs.RO]Pose Estimation for Omni-directional Cameras using Sinusoid Fitting
    Haofei Kuang, Qingwen Xu, Sören Schwertfeger
    http://arxiv.org/abs/1910.00882v1

    • [cs.RO]ROS Rescue : Fault Tolerance System for Robot Operating System
    Pushyami Kaveti, Hanumant Singh
    http://arxiv.org/abs/1910.01078v1

    • [cs.RO]Robust Data-Driven Zero-Velocity Detection for Foot-Mounted Inertial Navigation
    Brandon Wagstaff, Valentin Peretroukhin, Jonathan Kelly
    http://arxiv.org/abs/1910.00529v2

    • [cs.RO]TagSLAM: Robust SLAM with Fiducial Markers
    Bernd Pfrommer, Kostas Daniilidis
    http://arxiv.org/abs/1910.00679v1

    • [cs.RO]The OpenUAV Swarm Simulation Testbed: a Collaborative DesignStudio for Field Robotics
    Harish Anand, Zhiang Chen, Jnaneshwar Das
    http://arxiv.org/abs/1910.00739v1

    • [cs.SI]Quantifying Voter Biases in Online Platforms: An Instrumental Variable Approach
    Himel Dev, Karrie Karahalios, Hari Sundaram
    http://arxiv.org/abs/1910.00757v1

    • [cs.SI]Retrieving Top Weighted Triangles in Graphs
    Raunak Kumar, Paul Liu, Moses Charikar, Austin R. Benson
    http://arxiv.org/abs/1910.00692v1

    • [econ.EM]An introduction to flexible methods for policy evaluation
    Martin Huber
    http://arxiv.org/abs/1910.00641v1

    • [eess.IV]Comparing Deep Learning Models for Multi-cell Classification in Liquid-based Cervical Cytology Images
    Sudhir Sornapudi, G. T. Brown, Zhiyun Xue, Rodney Long, Lisa Allen, Sameer Antani
    http://arxiv.org/abs/1910.00722v1

    • [eess.IV]Deep learning within a priori temporal feature spaces for large-scale dynamic MR image reconstruction: Application to 5-D cardiac MR Multitasking
    Yuhua Chen, Jaime L. Shaw, Yibin Xie, Debiao Li, Anthony G. Christodoulou
    http://arxiv.org/abs/1910.00956v1

    • [eess.IV]Empirical evaluation of full-reference image quality metrics on MDID database
    Domonkos Varga
    http://arxiv.org/abs/1910.01050v1

    • [eess.IV]Enhancing high-content imaging for studying microtubule networks at large-scale
    Hao-Chih Lee, Sarah T Cherng, Riccardo Miotto, Joel T Dudley
    http://arxiv.org/abs/1910.00662v1

    • [eess.IV]Improvement of Multiparametric MR Image Segmentation by Augmenting the Data with Generative Adversarial Networks for Glioma Patients
    Eric Carver, Zhenzhen Dai, Evan Liang, James Snyder, Ning Wen
    http://arxiv.org/abs/1910.00696v1

    • [eess.IV]W-Net: A CNN-based Architecture for White Blood Cells Image Classification
    Changhun Jung, Mohammed Abuhamad, Jumabek Alikhanov, Aziz Mohaisen, Kyungja Han, DaeHun Nyang
    http://arxiv.org/abs/1910.01091v1

    • [eess.SP]A Machine Learning framework for Sleeping Cell Detection in a Smart-city IoT Telecommunications Infrastructure
    Orestes Manzanilla-Salazar, Filippo Malandra, Hakim Mellah, Constant Wette, Brunilde Sanso
    http://arxiv.org/abs/1910.01092v1

    • [eess.SP]Deep 3D Pan via adaptive “t-shaped” convolutions with global and local adaptive dilations
    Juan Luis Gonzalez Bello, Munchurl Kim
    http://arxiv.org/abs/1910.01089v1

    • [eess.SP]Near-Convex Archetypal Analysis
    Pierre De Handschutter, Nicolas Gillis, Arnaud Vandaele, Xavier Siebert
    http://arxiv.org/abs/1910.00821v1

    • [eess.SY]An Iterative Quadratic Method for General-Sum Differential Games with Feedback Linearizable Dynamics
    David Fridovich-Keil, Vicenc Rubies-Royo, Claire J. Tomlin
    http://arxiv.org/abs/1910.00681v1

    • [eess.SY]Synthesis of Orchestrations and Choreographies: Bridging the Gap between Supervisory Control and Coordination of Services
    Davide Basile, Maurice H. ter Beek, Rosario Pugliese
    http://arxiv.org/abs/1910.00849v1

    • [math.OC]Global exponential stability of primal-dual gradient flow dynamics based on the proximal augmented Lagrangian: A Lyapunov-based approach
    Dongsheng Ding, Mihailo R. Jovanović
    http://arxiv.org/abs/1910.00783v1

    • [math.ST]A deterministic theory of low rank matrix completion
    Sourav Chatterjee
    http://arxiv.org/abs/1910.01079v1

    • [math.ST]Covariance Matrix Estimation with Non Uniform and Data Dependent Missing Observations
    Eduardo Pavez, Antonio Ortega
    http://arxiv.org/abs/1910.00667v1

    • [math.ST]Non-algorithmic theory of randomness
    Vladimir Vovk
    http://arxiv.org/abs/1910.00585v1

    • [math.ST]Non-uniform Berry-Esseen Bound by Unbounded Exchangeable Pair Approach
    Dali Liu, Zheng Li, Hanchao Wang, Zengjing Chen
    http://arxiv.org/abs/1909.13477v2

    • [math.ST]Parameter estimation for SPDEs based on discrete observations in time and space
    Florian Hildebrandt, Mathias Trabs
    http://arxiv.org/abs/1910.01004v1

    • [math.ST]Series Representation of Jointly S$α$S Distribution via A New Type of Symmetric Covariations
    Yujia Ding, Qidi Peng
    http://arxiv.org/abs/1910.00675v1

    • [math.ST]The Balakrishnan Alpha Skew Laplace Distribution: Properties and Its Applications
    Sricharan Shah, Partha Jyoti Hazarika, Subrata Chakraborty
    http://arxiv.org/abs/1910.01084v1

    • [physics.comp-ph]Deep learning at scale for subgrid modeling in turbulent flows
    Mathis Bode, Michael Gauding, Konstantin Kleinheinz, Heinz Pitsch
    http://arxiv.org/abs/1910.00928v1

    • [physics.soc-ph]A machine learning approach to predicting dynamical observables from network structure
    Francisco A. Rodrigues, Thomas Peron, Colm Connaughton, Jurgen Kurths, Yamir Moreno
    http://arxiv.org/abs/1910.00544v1

    • [physics.soc-ph]Prediction of citation dynamics of individual papers
    Michael Golosovsky
    http://arxiv.org/abs/1910.00867v1

    • [q-bio.QM]Identifying Cancer Patients at Risk for Heart Failure Using Machine Learning Methods
    Xi Yang, Yan Gong, Nida Waheed, Keith March, Jiang Bian, William R. Hogan, Yonghui Wu
    http://arxiv.org/abs/1910.00582v1

    • [stat.AP]Monotonic Nonparametric Dose Response Model
    Faten S. Alamri, Edward L. Boone, David J. Edwards
    http://arxiv.org/abs/1910.00150v2

    • [stat.ME]Fast and Fair Simultaneous Confidence Bands for Functional Parameters
    Dominik Liebl, Matthew Reimherr
    http://arxiv.org/abs/1910.00131v2

    • [stat.ME]Minimax D-optimal designs for multivariate regression models with multi-factors
    Lucy L. Gao, Julie Zhou
    http://arxiv.org/abs/1910.00745v1

    • [stat.ME]Robust Bayesian Regression with Synthetic Posterior
    Shintaro Hashimoto, Shonosuke Sugasawa
    http://arxiv.org/abs/1910.00812v1

    • [stat.ML]A note on the consistency of the random forest algorithm
    José A. Ferreira
    http://arxiv.org/abs/1910.00943v1

    • [stat.ML]Equivariant Flows: sampling configurations for multi-body systems with symmetric energies
    Jonas Köhler, Leon Klein, Frank Noé
    http://arxiv.org/abs/1910.00753v1

    • [stat.ML]Learning Neural Causal Models from Unknown Interventions
    Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Chris Pal, Yoshua Bengio
    http://arxiv.org/abs/1910.01075v1

    • [stat.ML]Order-Independent Structure Learning of Multivariate Regression Chain Graphs
    Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi
    http://arxiv.org/abs/1910.01067v1

    • [stat.ML]Reconsidering Analytical Variational Bounds for Output Layers of Deep Networks
    Otmane Sakhi, Stephen Bonner, David Rohde, Flavian Vasile
    http://arxiv.org/abs/1910.00877v1

    • [stat.ML]Scalable approximate inference for state space models with normalising flows
    Tom Ryder, Andrew Golightly, Isaac Matthews, Dennis Prangle
    http://arxiv.org/abs/1910.00879v1

    • [stat.ML]Towards Unifying Neural Architecture Space Exploration and Generalization
    Kartikeya Bhardwaj, Radu Marculescu
    http://arxiv.org/abs/1910.00780v1