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Eric B Laber
Susan A Murphy

Showing results (11-20 of 145) with videos related to

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Clinical Therapeutics|January 21, 2022
Reinforcement Learning Methods in Public HealthJustin Weltz, Alex Volfovsky, Eric B Laber
Biometrics|July 13, 2013
Inference for optimal dynamic treatment regimes using an adaptive m-out-of-n bootstrap schemeBibhas Chakraborty, Eric B Laber, Yingqi Zhao
Biostatistics (Oxford, England)|April 10, 2021
A spatiotemporal recommendation engine for malaria controlQian Guan, Brian J Reich, Eric B Laber
Clinical Trials (London, England)|June 14, 2014
Inference about the expected performance of a data-driven dynamic treatment regimeBibhas Chakraborty, Eric B Laber, Ying-Qi Zhao
Journal of the American Statistical Association|December 23, 2016
CommentQian Guan, Eric B Laber, Brian J Reich
Biometrics|January 10, 2014
Set-valued dynamic treatment regimes for competing outcomesEric B Laber, Daniel J Lizotte, Bradley Ferguson
Biometrika|December 27, 2014
Interactive model building for <i>Q</i>-learningEric B Laber, Kristin A Linn, Leonard A Stefanski
Journal of Statistical Software|February 23, 2016
iqLearn: Interactive Q-Learning in RKristin A Linn, Eric B Laber, Leonard A Stefanski
Journal of the American Statistical Association|September 12, 2017
Interactive Q-learning for QuantilesKristin A Linn, Eric B Laber, Leonard A Stefanski
Biometrics|July 22, 2015
Using decision lists to construct interpretable and parsimonious treatment regimesYichi Zhang, Eric B Laber, Anastasios Tsiatis, et al.
Pageof 15

Showing results (11-20 of 145) with videos related to

Sort By:
Pageof 15
Clinical Therapeutics|January 21, 2022
Reinforcement Learning Methods in Public HealthJustin Weltz, Alex Volfovsky, Eric B Laber
Biometrics|July 13, 2013
Inference for optimal dynamic treatment regimes using an adaptive m-out-of-n bootstrap schemeBibhas Chakraborty, Eric B Laber, Yingqi Zhao
Biostatistics (Oxford, England)|April 10, 2021
A spatiotemporal recommendation engine for malaria controlQian Guan, Brian J Reich, Eric B Laber
Clinical Trials (London, England)|June 14, 2014
Inference about the expected performance of a data-driven dynamic treatment regimeBibhas Chakraborty, Eric B Laber, Ying-Qi Zhao
Journal of the American Statistical Association|December 23, 2016
CommentQian Guan, Eric B Laber, Brian J Reich
Biometrics|January 10, 2014
Set-valued dynamic treatment regimes for competing outcomesEric B Laber, Daniel J Lizotte, Bradley Ferguson
Biometrika|December 27, 2014
Interactive model building for <i>Q</i>-learningEric B Laber, Kristin A Linn, Leonard A Stefanski
Journal of Statistical Software|February 23, 2016
iqLearn: Interactive Q-Learning in RKristin A Linn, Eric B Laber, Leonard A Stefanski
Journal of the American Statistical Association|September 12, 2017
Interactive Q-learning for QuantilesKristin A Linn, Eric B Laber, Leonard A Stefanski
Biometrics|July 22, 2015
Using decision lists to construct interpretable and parsimonious treatment regimesYichi Zhang, Eric B Laber, Anastasios Tsiatis, et al.
Pageof 15