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.DL - 数字图书馆
cs.IR - 信息检索
cs.IT - 信息论
cs.LG - 自动学习
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.SP - 信号处理
math.OC - 优化与控制
math.ST - 统计理论
physics.soc-ph - 物理学与社会
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
stat.OT - 其他统计学
• [cs.AI]A Summary of Adaptation of Techniques from Search-based Optimal Multi-Agent Path Finding Solvers to Compilation-based Approach
• [cs.AI]MEETING BOT: Reinforcement Learning for Dialogue Based Meeting Scheduling
• [cs.AI]Open-endedness in AI systems, cellular evolution and intellectual discussions
• [cs.AI]The Diagrammatic AI Language (DIAL): Version 0.1
• [cs.CL]Advancing the State of the Art in Open Domain Dialog Systems through the Alexa Prize
• [cs.CL]Identifying Computer-Translated Paragraphs using Coherence Features
• [cs.CL]Intent Detection and Slots Prompt in a Closed-Domain Chatbot
• [cs.CL]Knowledge Representation Learning: A Quantitative Review
• [cs.CL]Looking for ELMo's friends: Sentence-Level Pretraining Beyond Language Modeling
• [cs.CL]The Clickbait Challenge 2017: Towards a Regression Model for Clickbait Strength
• [cs.CL]The role of grammar in transition-probabilities of subsequent words in English text
• [cs.CR]A Precedent Approach to Assigning Access Rights
• [cs.CV]3D Point-Capsule Networks
• [cs.CV]Adaptive Image Sampling using Deep Learning and its Application on X-Ray Fluorescence Image Reconstruction
• [cs.CV]Artistic Object Recognition by Unsupervised Style Adaptation
• [cs.CV]Center Emphasized Visual Saliency and Contrast-based Full Reference Image Quality Index
• [cs.CV]Coarse-to-fine Semantic Segmentation from Image-level Labels
• [cs.CV]Deep Convolutional Neural Networks in the Face of Caricature: Identity and Image Revealed
• [cs.CV]Image Processing in Quantum Computers
• [cs.CV]Learning to Reconstruct Shapes from Unseen Classes
• [cs.CV]Salient Object Detection via High-to-Low Hierarchical Context Aggregation
• [cs.CV]Signal Classification under structure sparsity constraints
• [cs.CV]Spatiotemporal Data Fusion for Precipitation Nowcasting
• [cs.CV]TROVE Feature Detection for Online Pose Recovery by Binocular Cameras
• [cs.CY]Cardiology Admissions from Catheterization Laboratory: Time Series Forecasting
• [cs.CY]Early Prediction of Post-acute Care Discharge Disposition Using Predictive Analytics: Preponing Prior Health Insurance Authorization Thus Reducing the Inpatient Length of Stay
• [cs.CY]What did you see? Personalization, regionalization and the question of the filter bubble in Google's search engine
• [cs.DC]AT2: Asynchronous Trustworthy Transfers
• [cs.DC]An efficient cloud scheduler design supporting preemptible instances
• [cs.DC]Parallel Algorithm for Frequent Itemset Mining on Intel Many-core Systems
• [cs.DC]The Power of Distributed Verifiers in Interactive Proofs
• [cs.DC]Toward a self-learned Smart Contracts
• [cs.DL]Identifying translational science through embeddings of controlled vocabularies
• [cs.DL]Wikibook-Bot - Automatic Generation of a Wikipedia Book
• [cs.IR]QRFA: A Data-Driven Model of Information-Seeking Dialogues
• [cs.IR]Uni-DUE Student Team: Tackling fact checking through decomposable attention neural network
• [cs.IT]Generalization of the Ball-Collision Algorithm
• [cs.IT]On the Secrecy Performance of Generalized User Selection for Interference-Limited Multiuser Wireless Networks
• [cs.IT]Secure Modulo Sum via Multiple Access Channel
• [cs.IT]Skew Cyclic Codes Over
• [cs.LG]Classification of radiology reports by modality and anatomy: A comparative study
• [cs.LG]Differential Temporal Difference Learning
• [cs.LG]Exploring Weight Symmetry in Deep Neural Network
• [cs.LG]Generic adaptation strategies for automated machine learning
• [cs.LG]Hypergraph Clustering: A Modularity Maximization Approach
• [cs.LG]Improving the Interpretability of Deep Neural Networks with Knowledge Distillation
• [cs.LG]InstaGAN: Instance-aware Image-to-Image Translation
• [cs.LG]Learning to Walk via Deep Reinforcement Learning
• [cs.LG]Neural Model-Based Reinforcement Learning for Recommendation
• [cs.LG]On Computation and Generalization of GANs with Spectrum Control
• [cs.LG]Over-Parameterized Deep Neural Networks Have No Strict Local Minima For Any Continuous Activations
• [cs.LG]Reasoning About Physical Interactions with Object-Oriented Prediction and Planning
• [cs.LG]Scalable GAM using sparse variational Gaussian processes
• [cs.LG]Stanza: Distributed Deep Learning with Small Communication Footprint
• [cs.NE]A Tight Runtime Analysis for the EA
• [cs.RO]Car Detection using Unmanned Aerial Vehicles: Comparison between Faster R-CNN and YOLOv3
• [cs.RO]Online Decentralized Receding Horizon Trajectory Optimization for Multi-Robot systems
• [cs.SD]A Framework for Automated Pop-song Melody Generation with Piano Accompaniment Arrangement
• [cs.SI]A Variational Topological Neural Model for Cascade-based Diffusion in Networks
• [cs.SI]Rejection-Based Simulation of Stochastic Spreading Processes on Complex Networks
• [eess.IV]Vector Field-based Simulation of Tree-Like Non-Stationary Geostatistical Models
• [eess.SP]Continuity-Enhanced Basis Signal aided Low-Interference N-Continuous OFDM
• [math.OC]A continuous-time analysis of distributed stochastic gradient
• [math.ST]Asymptotic comparison of two-stage selection procedures under quasi-Bayesian framework
• [math.ST]How to avoid the zero-power trap in testing for correlation
• [math.ST]Rerandomization in Factorial Experiments
• [math.ST]Semiparametric Estimation for the Transformation Model with Length-Biased Data and Covariate Measurement Error
• [physics.soc-ph]Finding the proper node ranking method for complex networks
• [physics.soc-ph]Local Articulation Points in Complex Networks
• [quant-ph]Reinforcement learning architecture for automated quantum-adiabatic-algorithm design
• [stat.AP]A Descriptive Study of Variable Discretization and Cost-Sensitive Logistic Regression on Imbalanced Credit Data
• [stat.ME]Combining Non-probability and Probability Survey Samples Through Mass Imputation
• [stat.ME]Hybrid Wasserstein Distance and Fast Distribution Clustering
• [stat.ME]Quantile Treatment Effects and Bootstrap Inference under Covariate-Adaptive Randomization
• [stat.ML]Consistency of Interpolation with Laplace Kernels is a High-Dimensional Phenomenon
• [stat.ML]Divergence Triangle for Joint Training of Generator Model, Energy-based Model, and Inference Model
• [stat.ML]Predicting with Proxies
• [stat.ML]Reconciling modern machine learning and the bias-variance trade-off
• [stat.ML]Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization
• [stat.OT]Practical Considerations for Data Collection and Management in Mobile Health Micro-randomized Trials
·····································
• [cs.AI]A Summary of Adaptation of Techniques from Search-based Optimal Multi-Agent Path Finding Solvers to Compilation-based Approach
Pavel Surynek
http://arxiv.org/abs/1812.10851v1
• [cs.AI]MEETING BOT: Reinforcement Learning for Dialogue Based Meeting Scheduling
Vishwanath D, Lovekesh Vig, Gautam Shroff, Puneet Agarwal
http://arxiv.org/abs/1812.11158v1
• [cs.AI]Open-endedness in AI systems, cellular evolution and intellectual discussions
Kushal Shah
http://arxiv.org/abs/1812.10900v1
• [cs.AI]The Diagrammatic AI Language (DIAL): Version 0.1
Guy Marshall, André Freitas
http://arxiv.org/abs/1812.11142v1
• [cs.CL]Advancing the State of the Art in Open Domain Dialog Systems through the Alexa Prize
Chandra Khatri, Behnam Hedayatnia, Anu Venkatesh, Jeff Nunn, Yi Pan, Qing Liu, Han Song, Anna Gottardi, Sanjeev Kwatra, Sanju Pancholi, Ming Cheng, Qinglang Chen, Lauren Stubel, Karthik Gopalakrishnan, Kate Bland, Raefer Gabriel, Arindam Mandal, Dilek Hakkani-Tur, Gene Hwang, Nate Michel, Eric King, Rohit Prasad
http://arxiv.org/abs/1812.10757v1
• [cs.CL]Identifying Computer-Translated Paragraphs using Coherence Features
Hoang-Quoc Nguyen-Son, Ngoc-Dung T. Tieu, Huy H. Nguyen, Junichi Yamagishi, Isao Echizen
http://arxiv.org/abs/1812.10896v1
• [cs.CL]Intent Detection and Slots Prompt in a Closed-Domain Chatbot
Amber Nigam, Prashik Sahare, Kushagra Pandya
http://arxiv.org/abs/1812.10628v1
• [cs.CL]Knowledge Representation Learning: A Quantitative Review
Yankai Lin, Xu Han, Ruobing Xie, Zhiyuan Liu, Maosong Sun
http://arxiv.org/abs/1812.10901v1
• [cs.CL]Looking for ELMo's friends: Sentence-Level Pretraining Beyond Language Modeling
Samuel R. Bowman, Ellie Pavlick, Edouard Grave, Benjamin Van Durme, Alex Wang, Jan Hula, Patrick Xia, Raghavendra Pappagari, R. Thomas McCoy, Roma Patel, Najoung Kim, Ian Tenney, Yinghui Huang, Katherin Yu, Shuning Jin, Berlin Chen
http://arxiv.org/abs/1812.10860v1
• [cs.CL]The Clickbait Challenge 2017: Towards a Regression Model for Clickbait Strength
Martin Potthast, Tim Gollub, Matthias Hagen, Benno Stein
http://arxiv.org/abs/1812.10847v1
• [cs.CL]The role of grammar in transition-probabilities of subsequent words in English text
Rudolf Hanel, Stefan Thurner
http://arxiv.org/abs/1812.10991v1
• [cs.CR]A Precedent Approach to Assigning Access Rights
S. V. Belim, N. F. Bogachenko, A. N. Kabanov
http://arxiv.org/abs/1812.10961v1
• [cs.CV]3D Point-Capsule Networks
Yongheng Zhao, Tolga Birdal, Haowen Deng, Federico Tombari
http://arxiv.org/abs/1812.10775v1
• [cs.CV]Adaptive Image Sampling using Deep Learning and its Application on X-Ray Fluorescence Image Reconstruction
Qiqin Dai, Henry Chopp, Emeline Pouyet, Oliver Cossairt, Marc Walton, Aggelos K. Katsaggelos
http://arxiv.org/abs/1812.10836v1
• [cs.CV]Artistic Object Recognition by Unsupervised Style Adaptation
Christopher Thomas, Adriana Kovashka
http://arxiv.org/abs/1812.11139v1
• [cs.CV]Center Emphasized Visual Saliency and Contrast-based Full Reference Image Quality Index
Md Abu Layek, Sanjida Afroz, TaeChoong Chung, Eui-Nam Huh
http://arxiv.org/abs/1812.11163v1
• [cs.CV]Coarse-to-fine Semantic Segmentation from Image-level Labels
Longlong Jing, Yucheng Chen, Yingli Tian
http://arxiv.org/abs/1812.10885v1
• [cs.CV]Deep Convolutional Neural Networks in the Face of Caricature: Identity and Image Revealed
Matthew Q. Hill, Connor J. Parde, Carlos D. Castillo, Y. Ivette Colon, Rajeev Ranjan, Jun-Cheng Chen, Volker Blanz, Alice J. O'Toole
http://arxiv.org/abs/1812.10902v1
• [cs.CV]Image Processing in Quantum Computers
Aditya Dendukuri, Khoa Luu
http://arxiv.org/abs/1812.11042v1
• [cs.CV]Learning to Reconstruct Shapes from Unseen Classes
Xiuming Zhang, Zhoutong Zhang, Chengkai Zhang, Joshua B. Tenenbaum, William T. Freeman, Jiajun Wu
http://arxiv.org/abs/1812.11166v1
• [cs.CV]Salient Object Detection via High-to-Low Hierarchical Context Aggregation
Yun Liu, Yu Qiu, Le Zhang, JiaWang Bian, Guang-Yu Nie, Ming-Ming Cheng
http://arxiv.org/abs/1812.10956v1
• [cs.CV]Signal Classification under structure sparsity constraints
Tiep Huu Vu
http://arxiv.org/abs/1812.10859v1
• [cs.CV]Spatiotemporal Data Fusion for Precipitation Nowcasting
Vladimir Ivashkin, Vadim Lebedev
http://arxiv.org/abs/1812.10915v1
• [cs.CV]TROVE Feature Detection for Online Pose Recovery by Binocular Cameras
Yuance Liu, Michael Z. Q. Chen
http://arxiv.org/abs/1812.10967v1
• [cs.CY]Cardiology Admissions from Catheterization Laboratory: Time Series Forecasting
Avishek Choudhury, Sunanda Perumalla
http://arxiv.org/abs/1812.10486v1
• [cs.CY]Early Prediction of Post-acute Care Discharge Disposition Using Predictive Analytics: Preponing Prior Health Insurance Authorization Thus Reducing the Inpatient Length of Stay
Avishek Choudhury
http://arxiv.org/abs/1812.10487v1
• [cs.CY]What did you see? Personalization, regionalization and the question of the filter bubble in Google's search engine
Tobias D. Krafft, Michael Gamer, Katharina A. Zweig
http://arxiv.org/abs/1812.10943v1
• [cs.DC]AT2: Asynchronous Trustworthy Transfers
Guerraoui Rachid, Kuznetsov Petr, Monti Matteo, Pavlovic Matej, Seredinschi Dragos-Adrian
http://arxiv.org/abs/1812.10844v1
• [cs.DC]An efficient cloud scheduler design supporting preemptible instances
Álvaro López García, Enol Fernández-del-Castillo, Isabel Campos Plasencia
http://arxiv.org/abs/1812.10668v1
• [cs.DC]Parallel Algorithm for Frequent Itemset Mining on Intel Many-core Systems
Mikhail Zymbler
http://arxiv.org/abs/1812.10959v1
• [cs.DC]The Power of Distributed Verifiers in Interactive Proofs
Moni Naor, Merav Parter, Eylon Yogev
http://arxiv.org/abs/1812.10917v1
• [cs.DC]Toward a self-learned Smart Contracts
Ahmed S. Almasoud, Maged M. Eljazzar, Farookh Hussain
http://arxiv.org/abs/1812.10485v1
• [cs.DL]Identifying translational science through embeddings of controlled vocabularies
Qing Ke
http://arxiv.org/abs/1812.10609v1
• [cs.DL]Wikibook-Bot - Automatic Generation of a Wikipedia Book
Shahar Admati, Lior Rokach, Bracha Shapira
http://arxiv.org/abs/1812.10937v1
• [cs.IR]QRFA: A Data-Driven Model of Information-Seeking Dialogues
Svitlana Vakulenko, Kate Revoredo, Claudio Di Ciccio, Maarten de Rijke
http://arxiv.org/abs/1812.10720v1
• [cs.IR]Uni-DUE Student Team: Tackling fact checking through decomposable attention neural network
Jan Kowollik, Ahmet Aker
http://arxiv.org/abs/1812.10814v1
• [cs.IT]Generalization of the Ball-Collision Algorithm
Carmelo Interlando, Karan Khathuria, Nicole Rohrer, Joachim Rosenthal, Violetta Weger
http://arxiv.org/abs/1812.10955v1
• [cs.IT]On the Secrecy Performance of Generalized User Selection for Interference-Limited Multiuser Wireless Networks
Yazan H. Al-Badarneh, Costas N. Georghiades, Redha M. Radaydeh, Mohamed-Slim Alouini
http://arxiv.org/abs/1812.10829v1
• [cs.IT]Secure Modulo Sum via Multiple Access Channel
Masahito Hayashi
http://arxiv.org/abs/1812.10862v1
• [cs.IT]Skew Cyclic Codes Over
Nasreddine Benbelkacem, Martianus Frederic, Taher Abualrub, Aicha Batoul
http://arxiv.org/abs/1812.10692v1
• [cs.LG]Classification of radiology reports by modality and anatomy: A comparative study
Marina Bendersky, Joy Wu, Tanveer Syeda-Mahmood
http://arxiv.org/abs/1812.10818v1
• [cs.LG]Differential Temporal Difference Learning
Adithya M. Devraj, Ioannis Kontoyiannis, Sean P. Meyn
http://arxiv.org/abs/1812.11137v1
• [cs.LG]Exploring Weight Symmetry in Deep Neural Network
Xu Shell Hu, Sergey Zagoruyko, Nikos Komodakis
http://arxiv.org/abs/1812.11027v1
• [cs.LG]Generic adaptation strategies for automated machine learning
Rashid Bakirov, Bogdan Gabrys, Damien Fay
http://arxiv.org/abs/1812.10793v1
• [cs.LG]Hypergraph Clustering: A Modularity Maximization Approach
Tarun Kumar, Sankaran Vaidyanathan, Harini Ananthapadmanabhan, Srinivasan Parthasarathy, Balaraman Ravindran
http://arxiv.org/abs/1812.10869v1
• [cs.LG]Improving the Interpretability of Deep Neural Networks with Knowledge Distillation
Xuan Liu, Xiaoguang Wang, Stan Matwin
http://arxiv.org/abs/1812.10924v1
• [cs.LG]InstaGAN: Instance-aware Image-to-Image Translation
Sangwoo Mo, Minsu Cho, Jinwoo Shin
http://arxiv.org/abs/1812.10889v1
• [cs.LG]Learning to Walk via Deep Reinforcement Learning
Tuomas Haarnoja, Aurick Zhou, Sehoon Ha, Jie Tan, George Tucker, Sergey Levine
http://arxiv.org/abs/1812.11103v1
• [cs.LG]Neural Model-Based Reinforcement Learning for Recommendation
Xinshi Chen, Shuang Li, Hui Li, Shaohua Jiang, Yuan Qi, Le Song
http://arxiv.org/abs/1812.10613v1
• [cs.LG]On Computation and Generalization of GANs with Spectrum Control
Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao
http://arxiv.org/abs/1812.10912v1
• [cs.LG]Over-Parameterized Deep Neural Networks Have No Strict Local Minima For Any Continuous Activations
Dawei Li, Tian Ding, Ruoyu Sun
http://arxiv.org/abs/1812.11039v1
• [cs.LG]Reasoning About Physical Interactions with Object-Oriented Prediction and Planning
Michael Janner, Sergey Levine, William T. Freeman, Joshua B. Tenenbaum, Chelsea Finn, Jiajun Wu
http://arxiv.org/abs/1812.10972v1
• [cs.LG]Scalable GAM using sparse variational Gaussian processes
Vincent Adam, Nicolas Durrande, ST John
http://arxiv.org/abs/1812.11106v1
• [cs.LG]Stanza: Distributed Deep Learning with Small Communication Footprint
Xiaorui Wu, Hong Xu, Bo Li, Yongqiang Xiong
http://arxiv.org/abs/1812.10624v1
• [cs.NE]A Tight Runtime Analysis for the EA
Denis Antipov, Benjamin Doerr
http://arxiv.org/abs/1812.11061v1
• [cs.RO]Car Detection using Unmanned Aerial Vehicles: Comparison between Faster R-CNN and YOLOv3
Bilel Benjdira, Taha Khursheed, Anis Koubaa, Adel Ammar, Kais Ouni
http://arxiv.org/abs/1812.10968v1
• [cs.RO]Online Decentralized Receding Horizon Trajectory Optimization for Multi-Robot systems
Govind Aadithya R, Shravan Krishnan, Vijay Arvindh, Sivanathan K
http://arxiv.org/abs/1812.11135v1
• [cs.SD]A Framework for Automated Pop-song Melody Generation with Piano Accompaniment Arrangement
Ziyu Wang, Gus Xia
http://arxiv.org/abs/1812.10906v1
• [cs.SI]A Variational Topological Neural Model for Cascade-based Diffusion in Networks
Sylvain Lamprier
http://arxiv.org/abs/1812.10962v1
• [cs.SI]Rejection-Based Simulation of Stochastic Spreading Processes on Complex Networks
Gerrit Großmann, Verena Wolf
http://arxiv.org/abs/1812.10845v1
• [eess.IV]Vector Field-based Simulation of Tree-Like Non-Stationary Geostatistical Models
Viviana Lorena Vargas, Sinesio Pesco
http://arxiv.org/abs/1812.11030v1
• [eess.SP]Continuity-Enhanced Basis Signal aided Low-Interference N-Continuous OFDM
Peng Wei, Yue Xiao, Lilin Dan
http://arxiv.org/abs/1812.10944v1
• [math.OC]A continuous-time analysis of distributed stochastic gradient
Nicholas M. Boffi, Jean-Jacques E. Slotine
http://arxiv.org/abs/1812.10995v1
• [math.ST]Asymptotic comparison of two-stage selection procedures under quasi-Bayesian framework
Royi Jacobovic
http://arxiv.org/abs/1812.10742v1
• [math.ST]How to avoid the zero-power trap in testing for correlation
David Preinerstorfer
http://arxiv.org/abs/1812.10752v1
• [math.ST]Rerandomization in Factorial Experiments
Xinran Li, Peng Ding, Donald B. Rubin
http://arxiv.org/abs/1812.10911v1
• [math.ST]Semiparametric Estimation for the Transformation Model with Length-Biased Data and Covariate Measurement Error
Li-Pang Chen
http://arxiv.org/abs/1812.10758v1
• [physics.soc-ph]Finding the proper node ranking method for complex networks
Senbin Yu, Liang Gao, Yi-Fan Wang
http://arxiv.org/abs/1812.10616v1
• [physics.soc-ph]Local Articulation Points in Complex Networks
Senbin Yu, Liang Gao, Rongqiu Song
http://arxiv.org/abs/1812.10631v1
• [quant-ph]Reinforcement learning architecture for automated quantum-adiabatic-algorithm design
Jian Lin, Zhong Yuan Lai, Xiaopeng Li
http://arxiv.org/abs/1812.10797v1
• [stat.AP]A Descriptive Study of Variable Discretization and Cost-Sensitive Logistic Regression on Imbalanced Credit Data
Lili Zhang, Herman Ray, Soon Tan
http://arxiv.org/abs/1812.10857v1
• [stat.ME]Combining Non-probability and Probability Survey Samples Through Mass Imputation
Jae Kwang Kim, Seho Park, Yilin Chen, Changbao Wu
http://arxiv.org/abs/1812.10694v1
• [stat.ME]Hybrid Wasserstein Distance and Fast Distribution Clustering
Isabella Verdinelli, Larry Wasserman
http://arxiv.org/abs/1812.11026v1
• [stat.ME]Quantile Treatment Effects and Bootstrap Inference under Covariate-Adaptive Randomization
Xin Zheng, Yichong Zhang
http://arxiv.org/abs/1812.10644v1
• [stat.ML]Consistency of Interpolation with Laplace Kernels is a High-Dimensional Phenomenon
Alexander Rakhlin, Xiyu Zhai
http://arxiv.org/abs/1812.11167v1
• [stat.ML]Divergence Triangle for Joint Training of Generator Model, Energy-based Model, and Inference Model
Tian Han, Erik Nijkamp, Xiaolin Fang, Mitch Hill, Song-Chun Zhu, Ying Nian Wu
http://arxiv.org/abs/1812.10907v1
• [stat.ML]Predicting with Proxies
Hamsa Bastani
http://arxiv.org/abs/1812.11097v1
• [stat.ML]Reconciling modern machine learning and the bias-variance trade-off
Mikhail Belkin, Daniel Hsu, Siyuan Ma, Soumik Mandal
http://arxiv.org/abs/1812.11118v1
• [stat.ML]Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization
Aditya Grover, Stefano Ermon
http://arxiv.org/abs/1812.10539v1
• [stat.OT]Practical Considerations for Data Collection and Management in Mobile Health Micro-randomized Trials
Nicholas J. Seewald, Shawna N. Smith, Andy Jinseok Lee, Predrag Klasnja, Susan A. Murphy
http://arxiv.org/abs/1812.10800v1
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