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.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.IT - 信息论 cs.LG - 自动学习 cs.MM - 多媒体 cs.MS - 数学软件 cs.NE - 神经与进化计算 cs.RO - 机器人学 cs.SD - 声音处理 cs.SI - 社交网络与信息网络 eess.IV - 图像与视频处理 eess.SY - 系统和控制 math.OC - 优化与控制 math.ST - 统计理论 physics.flu-dyn - 流体动力学 q-bio.QM - 定量方法 quant-ph - 量子物理 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cs.AI]Deep Q-Network for Angry Birds
• [cs.CL]Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods
• [cs.CL]Character Feature Engineering for Japanese Word Segmentation
• [cs.CL]Detecting Deception in Political Debates Using Acoustic and Textual Features
• [cs.CL]DialectGram: Automatic Detection of Dialectal Variation at Multiple Geographic Resolutions
• [cs.CL]Distilling Transformers into Simple Neural Networks with Unlabeled Transfer Data
• [cs.CL]Modeling Confidence in Sequence-to-Sequence Models
• [cs.CL]Multi-level Gated Recurrent Neural Network for Dialog Act Classification
• [cs.CL]Predicting the Role of Political Trolls in Social Media
• [cs.CL]Semi-Supervised Generative Modeling for Controllable Speech Synthesis
• [cs.CL]Tanbih: Get To Know What You Are Reading
• [cs.CL]Template-free Data-to-Text Generation of Finnish Sports News
• [cs.CR]Boomerang: Redundancy Improves Latency and Throughput in Payment Networks
• [cs.CR]PINFER: Privacy-Preserving Inference for Machine Learning
• [cs.CV]360-Indoor: Towards Learning Real-World Objects in 360° Indoor Equirectangular Images
• [cs.CV]A Topological Loss Function for Deep-Learning based Image Segmentation using Persistent Homology
• [cs.CV]Active Learning with Weak Supervision for Cost-Effective Panicle Detection in Cereal Crops
• [cs.CV]DELP-DAR System for License Plate Detection and Recognition
• [cs.CV]EBBIOT: A Low-complexity Tracking Algorithm for Surveillance in IoVT Using Stationary Neuromorphic Vision Sensors
• [cs.CV]Generating Relevant Counter-Examples from a Positive Unlabeled Dataset for Image Classification
• [cs.CV]Layout-Graph Reasoning for Fashion Landmark Detection
• [cs.CV]NeurReg: Neural Registration and Its Application to Image Segmentation
• [cs.CV]Neural Puppet: Generative Layered Cartoon Characters
• [cs.CV]Neural Turtle Graphics for Modeling City Road Layouts
• [cs.CV]On the Detection of Digital Face Manipulation
• [cs.CV]Robust Semi-Supervised Monocular Depth Estimation with Reprojected Distances
• [cs.CV]SELF: Learning to Filter Noisy Labels with Self-Ensembling
• [cs.CV]Stacked Autoencoder Based Deep Random Vector Functional Link Neural Network for Classification
• [cs.CV]Talk2Nav: Long-Range Vision-and-Language Navigation in Cities
• [cs.CV]Two Stream Networks for Self-Supervised Ego-Motion Estimation
• [cs.CV]Unsupervised Keypoint Learning for Guiding Class-Conditional Video Prediction
• [cs.CV]Variational Osmosis for Non-linear Image Fusion
• [cs.CY]The Effects of Digitalization on Human Energy and Fatigue: A Review
• [cs.DB]A Blueprint For Interoperable Blockhains
• [cs.DC]Scheduling Stochastic Real-Time Coflows in Unreliable Computing Machines
• [cs.DS]Efficient Symmetric Norm Regression via Linear Sketching
• [cs.IT]A DNN Architecture for the Detection of Generalized Spatial Modulation Signals
• [cs.IT]Analytical Performance Evaluation of THz Wireless Fiber Extenders
• [cs.IT]Ergodic capacity evaluation of wireless THz fiber extenders
• [cs.IT]On some distributed scheduling algorithms for wireless networks with hypergraph interference models
• [cs.IT]On the Effectiveness of OTFS for Joint Radar and Communication
• [cs.IT]Secret key agreement for hypergraphical sources with limited total discussion
• [cs.LG]Benchmarking Batch Deep Reinforcement Learning Algorithms
• [cs.LG]Causal Induction from Visual Observations for Goal Directed Tasks
• [cs.LG]Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints
• [cs.LG]Conditional out-of-sample generation for unpaired data using trVAE
• [cs.LG]Dynamic Joint Variational Graph Autoencoders
• [cs.LG]Enriching Visual with Verbal Explanations for Relational Concepts — Combining LIME with Aleph
• [cs.LG]Few-Shot Abstract Visual Reasoning With Spectral Features
• [cs.LG]Fluid Flow Mass Transport for Generative Networks
• [cs.LG]Generalized Inner Loop Meta-Learning
• [cs.LG]Generative Adversarial Networks for Failure Prediction
• [cs.LG]If MaxEnt RL is the Answer, What is the Question?
• [cs.LG]Learning Robust Representations with Graph Denoising Policy Network
• [cs.LG]Manufacturing Dispatching using Reinforcement and Transfer Learning
• [cs.LG]Measuring Arithmetic Extrapolation Performance
• [cs.LG]On the Duality between Network Flows and Network Lasso
• [cs.LG]PPGAN: Privacy-preserving Generative Adversarial Network
• [cs.LG]Randomized Shortest Paths with Net Flows and Capacity Constraints
• [cs.LG]Revisiting Classical Bagging with Modern Transfer Learning for On-the-fly Disaster Damage Detector
• [cs.LG]SNDCNN: Self-normalizing deep CNNs with scaled exponential linear units for speech recognition
• [cs.LG]Scalable Global Optimization via Local Bayesian Optimization
• [cs.LG]The Complexity of Finding Stationary Points with Stochastic Gradient Descent
• [cs.LG]Unsupervised Representation for EHR Signals and Codes as Patient Status Vector
• [cs.LG]Using Logical Specifications of Objectives in Multi-Objective Reinforcement Learning
• [cs.LG]ZeRO: Memory Optimization Towards Training A Trillion Parameter Models
• [cs.MM]SMP Challenge: An Overview of Social Media Prediction Challenge 2019
• [cs.MS]GPU Fast Convolution via the Overlap-and-Save Method in Shared Memory
• [cs.NE]Order Acceptance and Scheduling with Sequence-dependent Setup Times: a New Memetic Algorithm and Benchmark of the State of the Art
• [cs.RO]Behavior Mixing with Minimum Global and Subgroup Connectivity Maintenance for Large-Scale Multi-Robot Systems
• [cs.RO]Estimating Lower Limb Kinematics using a Lie Group Constrained EKF and a Reduced Wearable IMU Count
• [cs.RO]Higher Order Function Networks for View Planning and Multi-View Reconstruction
• [cs.RO]Hybrid Zero Dynamics Inspired Feedback Control Policy Design for 3D Bipedal Locomotion using Reinforcement Learning
• [cs.RO]Low-cost LIDAR based Vehicle Pose Estimation and Tracking
• [cs.RO]Motion Planning through Demonstration to Deal with Complex Motions in Assembly Process
• [cs.RO]Prediction of Human Full-Body Movements with Motion Optimization and Recurrent Neural Networks
• [cs.RO]Reach Out and Help: Assisted Remote Collaboration through a Handheld Robot
• [cs.RO]Resilient Coverage: Exploring the Local-to-Global Trade-off
• [cs.RO]Zero Shot Learning on Simulated Robots
• [cs.SD]Midi Miner — A Python library for tonal tension and track classification
• [cs.SI]A new method for quantifying network cyclic structure to improve community detection
• [cs.SI]An adaptive hybrid algorithm for social networks to choose groups with independent members
• [cs.SI]Bots, elections, and social media: a brief overview
• [cs.SI]Constant State of Change: Engagement Inequality in Temporal Dynamic Networks
• [cs.SI]From Senseless Swarms to Smart Mobs: Tuning Networks for Prosocial Behaviour
• [cs.SI]Token Economics in Real-Life: Cryptocurrency and Incentives Design for Insolar Blockchain Network
• [eess.IV]4D MRI: Robust sorting of free breathing MRI slices for use in interventional settings
• [eess.IV]Memory efficient brain tumor segmentation using an autoencoder-regularized U-Net
• [eess.SY]Convolutional Neural Networks for Speech Controlled Prosthetic Hands
• [math.OC]Approximate policy iteration using neural networks for storage problems
• [math.OC]Inexact Online Proximal-gradient Method for Time-varying Convex Optimization
• [math.ST]Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization
• [math.ST]On the Asymptotic Distribution of the Scan Statistic for Point Clouds
• [math.ST]On the strong uniform consistency for relative error of the regression function estimator for censoring times series model
• [physics.flu-dyn]Path-planning microswimmers can swim efficiently in turbulent flows
• [q-bio.QM]A Random Interaction Forest for Prioritizing Predictive Biomarkers
• [q-bio.QM]A machine learning method correlating pulse pressure wave data with pregnancy
• [quant-ph]Quantum Hamiltonian-Based Models and the Variational Quantum Thermalizer Algorithm
• [stat.AP]Computationally efficient surrogate-based optimization of coastal storm waves heights and run-ups
• [stat.AP]Profile regression for subgrouping patients with early stage Parkinson’s disease
• [stat.AP]Usage-Based Vehicle Insurance: Driving Style Factors of Accident Probability and Severity
• [stat.ME]Algebraic statistics, tables, and networks: The Fienberg advantage
• [stat.ME]Automating Data Monitoring: Detecting Structural Breaks in Time Series Data Using Bayesian Minimum Description Length
• [stat.ME]Function-on-function kriging, with applications to 3D printing of aortic tissues
• [stat.ME]SIMPLE: Statistical Inference on Membership Profiles in Large Networks
• [stat.ME]Streamlined Variational Inference for Linear Mixed Models with Crossed Random Effects
• [stat.ML]Bayesian Optimization for Materials Design with Mixed Quantitative and Qualitative Variables
• [stat.ML]Dual Learning Algorithm for Delayed Feedback in Display Advertising
• [stat.ML]Simulations evaluating resampling methods for causal discovery: ensemble performance and calibration
• [stat.ML]Sparse Popularity Adjusted Stochastic Block Model
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• [cs.AI]Deep Q-Network for Angry Birds
Ekaterina Nikonova, Jakub Gemrot
http://arxiv.org/abs/1910.01806v1
• [cs.CL]Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods
Camburu Oana-Maria, Giunchiglia Eleonora, Foerster Jakob, Lukasiewicz Thomas, Blunsom Phil
http://arxiv.org/abs/1910.02065v1
• [cs.CL]Character Feature Engineering for Japanese Word Segmentation
Mike Tian-Jian Jiang
http://arxiv.org/abs/1910.01761v1
• [cs.CL]Detecting Deception in Political Debates Using Acoustic and Textual Features
Daniel Kopev, Ahmed Ali, Ivan Koychev, Preslav Nakov
http://arxiv.org/abs/1910.01990v1
• [cs.CL]DialectGram: Automatic Detection of Dialectal Variation at Multiple Geographic Resolutions
Hang Jiang, Haoshen Hong, Yuxing Chen, Vivek Kulkarni
http://arxiv.org/abs/1910.01818v1
• [cs.CL]Distilling Transformers into Simple Neural Networks with Unlabeled Transfer Data
Subhabrata Mukherjee, Ahmed Hassan Awadallah
http://arxiv.org/abs/1910.01769v1
• [cs.CL]Modeling Confidence in Sequence-to-Sequence Models
Jan Niehues, Ngoc-Quan Pham
http://arxiv.org/abs/1910.01859v1
• [cs.CL]Multi-level Gated Recurrent Neural Network for Dialog Act Classification
Wei Li, Yunfang Wu
http://arxiv.org/abs/1910.01822v1
• [cs.CL]Predicting the Role of Political Trolls in Social Media
Atanas Atanasov, Gianmarco De Francisci Morales, Preslav Nakov
http://arxiv.org/abs/1910.02001v1
• [cs.CL]Semi-Supervised Generative Modeling for Controllable Speech Synthesis
Raza Habib, Soroosh Mariooryad, Matt Shannon, Eric Battenberg, RJ Skerry-Ryan, Daisy Stanton, David Kao, Tom Bagby
http://arxiv.org/abs/1910.01709v1
• [cs.CL]Tanbih: Get To Know What You Are Reading
Yifan Zhang, Giovanni Da San Martino, Alberto Barrón-Cedeño, Salvatore Romeo, Jisun An, Haewoon Kwak, Todor Staykovski, Israa Jaradat, Georgi Karadzhov, Ramy Baly, Kareem Darwish, James Glass, Preslav Nakov
http://arxiv.org/abs/1910.02028v1
• [cs.CL]Template-free Data-to-Text Generation of Finnish Sports News
Jenna Kanerva, Samuel Rönnqvist, Riina Kekki, Tapio Salakoski, Filip Ginter
http://arxiv.org/abs/1910.01863v1
• [cs.CR]Boomerang: Redundancy Improves Latency and Throughput in Payment Networks
Vivek Bagaria, Joachim Neu, David Tse
http://arxiv.org/abs/1910.01834v1
• [cs.CR]PINFER: Privacy-Preserving Inference for Machine Learning
Marc Joye, Fabien A. P. Petitcolas
http://arxiv.org/abs/1910.01865v1
• [cs.CV]360-Indoor: Towards Learning Real-World Objects in 360° Indoor Equirectangular Images
Shih-Han Chou, Cheng Sun, Wen-Yen Chang, Wan-Ting Hsu, Min Sun, Jianlong Fu
http://arxiv.org/abs/1910.01712v1
• [cs.CV]A Topological Loss Function for Deep-Learning based Image Segmentation using Persistent Homology
James R. Clough, Ilkay Oksuz, Nicholas Byrne, Veronika A. Zimmer, Julia A. Schnabel, Andrew P. King
http://arxiv.org/abs/1910.01877v1
• [cs.CV]Active Learning with Weak Supervision for Cost-Effective Panicle Detection in Cereal Crops
Akshay C Lagandula, Sai Vikas Desai, Vineeth N Balasubramanian, Seishi Ninomiya, Wei Guo
http://arxiv.org/abs/1910.01789v1
• [cs.CV]DELP-DAR System for License Plate Detection and Recognition
Zied Selmi, Mohamed Ben Halima, Umapada Pal, M. Adel Alimi
http://arxiv.org/abs/1910.01853v1
• [cs.CV]EBBIOT: A Low-complexity Tracking Algorithm for Surveillance in IoVT Using Stationary Neuromorphic Vision Sensors
Jyotibdha Acharya, Andres Ussa Caycedo, Vandana Reddy Padala, Rishi Raj Sidhu Singh, Garrick Orchard, Bharath Ramesh, Arindam Basu
http://arxiv.org/abs/1910.01851v1
• [cs.CV]Generating Relevant Counter-Examples from a Positive Unlabeled Dataset for Image Classification
Florent Chiaroni, Ghazaleh Khodabandelou, Mohamed-Cherif Rahal, Nicolas Hueber, Frederic Dufaux
http://arxiv.org/abs/1910.01968v1
• [cs.CV]Layout-Graph Reasoning for Fashion Landmark Detection
Weijiang Yu, Xiaodan Liang, Ke Gong, Chenhan Jiang, Nong Xiao, Liang Lin
http://arxiv.org/abs/1910.01923v1
• [cs.CV]NeurReg: Neural Registration and Its Application to Image Segmentation
Wentao Zhu, Andriy Myronenko, Ziyue Xu, Wenqi Li, Holger Roth, Yufang Huang, Fausto Milletari, Daguang Xu
http://arxiv.org/abs/1910.01763v1
• [cs.CV]Neural Puppet: Generative Layered Cartoon Characters
Omid Poursaeed, Vladimir G. Kim, Eli Shechtman, Jun Saito, Serge Belongie
http://arxiv.org/abs/1910.02060v1
• [cs.CV]Neural Turtle Graphics for Modeling City Road Layouts
Hang Chu, Daiqing Li, David Acuna, Amlan Kar, Maria Shugrina, Xinkai Wei, Ming-Yu Liu, Antonio Torralba, Sanja Fidler
http://arxiv.org/abs/1910.02055v1
• [cs.CV]On the Detection of Digital Face Manipulation
Joel Stehouwer, Hao Dang, Feng Liu, Xiaoming Liu, Anil Jain
http://arxiv.org/abs/1910.01717v1
• [cs.CV]Robust Semi-Supervised Monocular Depth Estimation with Reprojected Distances
Vitor Guizilini, Jie Li, Rares Ambrus, Sudeep Pillai, Adrien Gaidon
http://arxiv.org/abs/1910.01765v1
• [cs.CV]SELF: Learning to Filter Noisy Labels with Self-Ensembling
Duc Tam Nguyen, Chaithanya Kumar Mummadi, Thi Phuong Nhung Ngo, Thi Hoai Phuong Nguyen, Laura Beggel, Thomas Brox
http://arxiv.org/abs/1910.01842v1
• [cs.CV]Stacked Autoencoder Based Deep Random Vector Functional Link Neural Network for Classification
Rakesh Katuwal, P. N. Suganthan
http://arxiv.org/abs/1910.01858v1
• [cs.CV]Talk2Nav: Long-Range Vision-and-Language Navigation in Cities
Arun Balajee Vasudevan, Dengxin Dai, Luc Van Gool
http://arxiv.org/abs/1910.02029v1
• [cs.CV]Two Stream Networks for Self-Supervised Ego-Motion Estimation
Rares Ambrus, Vitor Guizilini, Jie Li, Sudeep Pillai, Adrien Gaidon
http://arxiv.org/abs/1910.01764v1
• [cs.CV]Unsupervised Keypoint Learning for Guiding Class-Conditional Video Prediction
Yunji Kim, Seonghyeon Nam, In Cho, Seon Joo Kim
http://arxiv.org/abs/1910.02027v1
• [cs.CV]Variational Osmosis for Non-linear Image Fusion
Simone Parisotto, Luca Calatroni, Aurélie Bugeau, Nicolas Papadakis, Carola-Bibiane Schönlieb
http://arxiv.org/abs/1910.02012v1
• [cs.CY]The Effects of Digitalization on Human Energy and Fatigue: A Review
Jana Korunovska, Sarah Spiekermann
http://arxiv.org/abs/1910.01970v1
• [cs.DB]A Blueprint For Interoperable Blockhains
Tien Tuan Anh Dinh, Anwitaman Datta, Beng Chin Ooi
http://arxiv.org/abs/1910.00985v2
• [cs.DC]Scheduling Stochastic Real-Time Coflows in Unreliable Computing Machines
Yu-Pin Hsu
http://arxiv.org/abs/1910.00916v3
• [cs.DS]Efficient Symmetric Norm Regression via Linear Sketching
Zhao Song, Ruosong Wang, Lin F. Yang, Peilin Zhong, Hongyang Zhang
http://arxiv.org/abs/1910.01788v1
• [cs.IT]A DNN Architecture for the Detection of Generalized Spatial Modulation Signals
Bharath Shamasundar, A. Chockalingam
http://arxiv.org/abs/1910.01948v1
• [cs.IT]Analytical Performance Evaluation of THz Wireless Fiber Extenders
Alexandros-Apostolos A. Boulogeorgos, Evangelos N. Papasotiriou, Angeliki Alexiou
http://arxiv.org/abs/1910.01885v1
• [cs.IT]Ergodic capacity evaluation of wireless THz fiber extenders
Evangelos N. Papasotiriou, Alexandros-Apostolos A. Boulogeorgos, Angeliki Alexiou
http://arxiv.org/abs/1910.01836v1
• [cs.IT]On some distributed scheduling algorithms for wireless networks with hypergraph interference models
Ashwin Ganesan
http://arxiv.org/abs/1910.01909v1
• [cs.IT]On the Effectiveness of OTFS for Joint Radar and Communication
Lorenzo Gaudio, Mari Kobayashi, Giuseppe Caire, Giulio Colavolpe
http://arxiv.org/abs/1910.01896v1
• [cs.IT]Secret key agreement for hypergraphical sources with limited total discussion
Chung Chan
http://arxiv.org/abs/1910.01894v1
• [cs.LG]Benchmarking Batch Deep Reinforcement Learning Algorithms
Scott Fujimoto, Edoardo Conti, Mohammad Ghavamzadeh, Joelle Pineau
http://arxiv.org/abs/1910.01708v1
• [cs.LG]Causal Induction from Visual Observations for Goal Directed Tasks
Suraj Nair, Yuke Zhu, Silvio Savarese, Li Fei-Fei
http://arxiv.org/abs/1910.01751v1
• [cs.LG]Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints
Felix Sattler, Klaus-Robert Müller, Wojciech Samek
http://arxiv.org/abs/1910.01991v1
• [cs.LG]Conditional out-of-sample generation for unpaired data using trVAE
Mohammad Lotfollahi, Mohsen Naghipourfar, Fabian J. Theis, F. Alexander Wolf
http://arxiv.org/abs/1910.01791v1
• [cs.LG]Dynamic Joint Variational Graph Autoencoders
Sedigheh Mahdavi, Shima Khoshraftar, Aijun An
http://arxiv.org/abs/1910.01963v1
• [cs.LG]Enriching Visual with Verbal Explanations for Relational Concepts — Combining LIME with Aleph
Johannes Rabold, Hannah Deininger, Michael Siebers, Ute Schmid
http://arxiv.org/abs/1910.01837v1
• [cs.LG]Few-Shot Abstract Visual Reasoning With Spectral Features
Tanner Bohn, Yining Hu, Charles X. Ling
http://arxiv.org/abs/1910.01833v1
• [cs.LG]Fluid Flow Mass Transport for Generative Networks
Jingrong Lin, Keegan Lensink, Eldad Haber
http://arxiv.org/abs/1910.01694v1
• [cs.LG]Generalized Inner Loop Meta-Learning
Edward Grefenstette, Brandon Amos, Denis Yarats, Phu Mon Htut, Artem Molchanov, Franziska Meier, Douwe Kiela, Kyunghyun Cho, Soumith Chintala
http://arxiv.org/abs/1910.01727v1
• [cs.LG]Generative Adversarial Networks for Failure Prediction
Shuai Zheng, Ahmed Farahat, Chetan Gupta
http://arxiv.org/abs/1910.02034v1
• [cs.LG]If MaxEnt RL is the Answer, What is the Question?
Benjamin Eysenbach, Sergey Levine
http://arxiv.org/abs/1910.01913v1
• [cs.LG]Learning Robust Representations with Graph Denoising Policy Network
Lu Wang, Wenchao Yu, Wei Wang, Wei Cheng, Wei Zhang, Hongyuan Zha, Xiaofeng He, Haifeng Chen
http://arxiv.org/abs/1910.01784v1
• [cs.LG]Manufacturing Dispatching using Reinforcement and Transfer Learning
Shuai Zheng, Chetan Gupta, Susumu Serita
http://arxiv.org/abs/1910.02035v1
• [cs.LG]Measuring Arithmetic Extrapolation Performance
Andreas Madsen, Alexander Rosenberg Johansen
http://arxiv.org/abs/1910.01888v1
• [cs.LG]On the Duality between Network Flows and Network Lasso
Alexander Jung
http://arxiv.org/abs/1910.01805v1
• [cs.LG]PPGAN: Privacy-preserving Generative Adversarial Network
Yi Liu, Jialiang Peng, James J. Q Yu, Yi Wu
http://arxiv.org/abs/1910.02007v1
• [cs.LG]Randomized Shortest Paths with Net Flows and Capacity Constraints
Sylvain Courtain, Pierre Leleux, Ilkka Kivimaki, Guillaume Guex, Marco Saerens
http://arxiv.org/abs/1910.01849v1
• [cs.LG]Revisiting Classical Bagging with Modern Transfer Learning for On-the-fly Disaster Damage Detector
Junghoon Seo, Seungwon Lee, Beomsu Kim, Taegyun Jeon
http://arxiv.org/abs/1910.01911v1
• [cs.LG]SNDCNN: Self-normalizing deep CNNs with scaled exponential linear units for speech recognition
Zhen Huang, Tim Ng, Leo Liu, Henry Mason, Xiaodan Zhuang, Daben Liu
http://arxiv.org/abs/1910.01992v1
• [cs.LG]Scalable Global Optimization via Local Bayesian Optimization
David Eriksson, Michael Pearce, Jacob R Gardner, Ryan Turner, Matthias Poloczek
http://arxiv.org/abs/1910.01739v1
• [cs.LG]The Complexity of Finding Stationary Points with Stochastic Gradient Descent
Yoel Drori, Ohad Shamir
http://arxiv.org/abs/1910.01845v1
• [cs.LG]Unsupervised Representation for EHR Signals and Codes as Patient Status Vector
Sajad Darabi, Mohammad Kachuee, Majid Sarrafzadeh
http://arxiv.org/abs/1910.01803v1
• [cs.LG]Using Logical Specifications of Objectives in Multi-Objective Reinforcement Learning
Kolby Nottingham, Anand Balakrishnan, Jyotirmoy Deshmukh, Connor Christopherson, David Wingate
http://arxiv.org/abs/1910.01723v1
• [cs.LG]ZeRO: Memory Optimization Towards Training A Trillion Parameter Models
Samyam Rajbhandari, Jeff Rasley, Olatunji Ruwase, Yuxiong He
http://arxiv.org/abs/1910.02054v1
• [cs.MM]SMP Challenge: An Overview of Social Media Prediction Challenge 2019
Bo Wu, Wen-Huang Cheng, Peiye Liu, Zhaoyang Zeng, Jiebo Luo
http://arxiv.org/abs/1910.01795v1
• [cs.MS]GPU Fast Convolution via the Overlap-and-Save Method in Shared Memory
Karel Adámek, Sofia Dimoudi, Mike Giles, Wesley Armour
http://arxiv.org/abs/1910.01972v1
• [cs.NE]Order Acceptance and Scheduling with Sequence-dependent Setup Times: a New Memetic Algorithm and Benchmark of the State of the Art
Lei He, Arthur Guijt, Mathijs de Weerdt, Lining Xing, Neil Yorke-Smith
http://arxiv.org/abs/1910.01982v1
• [cs.RO]Behavior Mixing with Minimum Global and Subgroup Connectivity Maintenance for Large-Scale Multi-Robot Systems
Wenhao Luo, Sha Yi, Katia Sycara
http://arxiv.org/abs/1910.01693v1
• [cs.RO]Estimating Lower Limb Kinematics using a Lie Group Constrained EKF and a Reduced Wearable IMU Count
Luke Sy, Nigel H. Lovell, Stephen J. Redmond
http://arxiv.org/abs/1910.01808v1
• [cs.RO]Higher Order Function Networks for View Planning and Multi-View Reconstruction
Selim Engin, Eric Mitchell, Daewon Lee, Volkan Isler, Daniel D. Lee
http://arxiv.org/abs/1910.02066v1
• [cs.RO]Hybrid Zero Dynamics Inspired Feedback Control Policy Design for 3D Bipedal Locomotion using Reinforcement Learning
Guillermo A. Castillo, Bowen Weng, Wei Zhang, Ayonga Hereid
http://arxiv.org/abs/1910.01748v1
• [cs.RO]Low-cost LIDAR based Vehicle Pose Estimation and Tracking
Chen Fu, Chiyu Dong, Xiao Zhang, John M. Dolan
http://arxiv.org/abs/1910.01701v1
• [cs.RO]Motion Planning through Demonstration to Deal with Complex Motions in Assembly Process
Yan Wang, Kensuke Harada, Weiwei Wan
http://arxiv.org/abs/1910.01821v1
• [cs.RO]Prediction of Human Full-Body Movements with Motion Optimization and Recurrent Neural Networks
Philipp Kratzer, Marc Toussaint, Jim Mainprice
http://arxiv.org/abs/1910.01843v1
• [cs.RO]Reach Out and Help: Assisted Remote Collaboration through a Handheld Robot
Janis Stolzenwald, Walterio W. Mayol-Cuevas
http://arxiv.org/abs/1910.02015v1
• [cs.RO]Resilient Coverage: Exploring the Local-to-Global Trade-off
Ragesh K. Ramachandran, Lifeng Zhou, Gaurav S. Sukhatme
http://arxiv.org/abs/1910.01917v1
• [cs.RO]Zero Shot Learning on Simulated Robots
Robert Kwiatkowski, Hod Lipson
http://arxiv.org/abs/1910.01994v1
• [cs.SD]Midi Miner — A Python library for tonal tension and track classification
Rui Guo, Dorien Herremans, Thor Magnusson
http://arxiv.org/abs/1910.02049v1
• [cs.SI]A new method for quantifying network cyclic structure to improve community detection
Behnaz Moradi-Jamei, Heman Shakeri, Pietro Poggi-Corradini, Michael J. Higgins
http://arxiv.org/abs/1910.01921v1
• [cs.SI]An adaptive hybrid algorithm for social networks to choose groups with independent members
Parham Hadikhani, Pooria Hadikhani
http://arxiv.org/abs/1910.01875v1
• [cs.SI]Bots, elections, and social media: a brief overview
Emilio Ferrara
http://arxiv.org/abs/1910.01720v1
• [cs.SI]Constant State of Change: Engagement Inequality in Temporal Dynamic Networks
Hadar Miller, Osnat Mokryn
http://arxiv.org/abs/1910.01722v1
• [cs.SI]From Senseless Swarms to Smart Mobs: Tuning Networks for Prosocial Behaviour
Sun Sun Lim, Roland Bouffanais
http://arxiv.org/abs/1910.01303v2
• [cs.SI]Token Economics in Real-Life: Cryptocurrency and Incentives Design for Insolar Blockchain Network
Marek Laskowski, Henry M. Kim, Michael Zargham, Matt Barlin, Danil Kabanov
http://arxiv.org/abs/1910.02064v1
• [eess.IV]4D MRI: Robust sorting of free breathing MRI slices for use in interventional settings
Gino Gulamhussene, Fabian Joeres, Marko Rak, Maciej Pech, Christian Hansen
http://arxiv.org/abs/1910.01902v1
• [eess.IV]Memory efficient brain tumor segmentation using an autoencoder-regularized U-Net
Markus Frey, Matthias Nau
http://arxiv.org/abs/1910.02058v1
• [eess.SY]Convolutional Neural Networks for Speech Controlled Prosthetic Hands
Mohsen Jafarzadeh, Yonas Tadesse
http://arxiv.org/abs/1910.01918v1
• [math.OC]Approximate policy iteration using neural networks for storage problems
Trivikram Dokka, Richlove Frimpong
http://arxiv.org/abs/1910.01895v1
• [math.OC]Inexact Online Proximal-gradient Method for Time-varying Convex Optimization
Amirhossein Ajalloeian, Andrea Simonetto, Emiliano Dall’Anese
http://arxiv.org/abs/1910.02018v1
• [math.ST]Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization
Ying Zhang, Ömer Deniz Akyildiz, Theo Damoulas, Sotirios Sabanis
http://arxiv.org/abs/1910.02008v1
• [math.ST]On the Asymptotic Distribution of the Scan Statistic for Point Clouds
Andrew Ying, Wen-Xin Zhou
http://arxiv.org/abs/1910.01809v1
• [math.ST]On the strong uniform consistency for relative error of the regression function estimator for censoring times series model
Bouhadjera Feriel, Elias Ould Said
http://arxiv.org/abs/1910.01964v1
• [physics.flu-dyn]Path-planning microswimmers can swim efficiently in turbulent flows
Jaya Kumar Alageshan, Akhilesh Kumar Verma, Jérémie Bec, Rahul Pandit
http://arxiv.org/abs/1910.01728v1
• [q-bio.QM]A Random Interaction Forest for Prioritizing Predictive Biomarkers
Zhen Zeng, Yuefeng Lu, Judong Shen, Wei Zheng, Peter Shaw, Mary Beth Dorr
http://arxiv.org/abs/1910.01786v1
• [q-bio.QM]A machine learning method correlating pulse pressure wave data with pregnancy
Jianhong Chen, Huang Huang, Wenrui Hao, Jinchao Xu
http://arxiv.org/abs/1910.01726v1
• [quant-ph]Quantum Hamiltonian-Based Models and the Variational Quantum Thermalizer Algorithm
Guillaume Verdon, Jacob Marks, Sasha Nanda, Stefan Leichenauer, Jack Hidary
http://arxiv.org/abs/1910.02071v1
• [stat.AP]Computationally efficient surrogate-based optimization of coastal storm waves heights and run-ups
Theodoros Mathikolonis, Volker Roeber, Serge Guillas
http://arxiv.org/abs/1910.01932v1
• [stat.AP]Profile regression for subgrouping patients with early stage Parkinson’s disease
Sarini Abdullah, James McGree, Nicole White, Kerrie Mengersen, Graham Kerr
http://arxiv.org/abs/1910.01864v1
• [stat.AP]Usage-Based Vehicle Insurance: Driving Style Factors of Accident Probability and Severity
Konstantin Korishchenko, Ivan Stankevich, Nikolay Pilnik, Daria Petrova
http://arxiv.org/abs/1910.00460v2
• [stat.ME]Algebraic statistics, tables, and networks: The Fienberg advantage
Elizabeth Gross, Vishesh Karwa, Sonja Petrović
http://arxiv.org/abs/1910.01692v1
• [stat.ME]Automating Data Monitoring: Detecting Structural Breaks in Time Series Data Using Bayesian Minimum Description Length
Yingbo Li, Robert Cezeaux, Di Yu
http://arxiv.org/abs/1910.01793v1
• [stat.ME]Function-on-function kriging, with applications to 3D printing of aortic tissues
Jialei Chen, Simon Mak, V. Roshan Joseph, Chuck Zhang
http://arxiv.org/abs/1910.01754v1
• [stat.ME]SIMPLE: Statistical Inference on Membership Profiles in Large Networks
Jianqing Fan, Yingying Fan, Xiao Han, Jinchi Lv
http://arxiv.org/abs/1910.01734v1
• [stat.ME]Streamlined Variational Inference for Linear Mixed Models with Crossed Random Effects
Marianne Menictas, Gioia Di Credico, Matt P. Wand
http://arxiv.org/abs/1910.01799v1
• [stat.ML]Bayesian Optimization for Materials Design with Mixed Quantitative and Qualitative Variables
Yichi Zhang, Daniel Apley, Wei Chen
http://arxiv.org/abs/1910.01688v1
• [stat.ML]Dual Learning Algorithm for Delayed Feedback in Display Advertising
Yuta Saito, Gota Morishita, Shota Yasui
http://arxiv.org/abs/1910.01847v1
• [stat.ML]Simulations evaluating resampling methods for causal discovery: ensemble performance and calibration
Erich Kummerfeld, Alexander Rix
http://arxiv.org/abs/1910.02047v1
• [stat.ML]Sparse Popularity Adjusted Stochastic Block Model
Majid Noroozi, Ramchandra Rimal, Marianna Pensky
http://arxiv.org/abs/1910.01931v1