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Eric B. Laber
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- affiliation: North Carolina State University, USA
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2020 – today
- 2023
- [i12]Tao Ma, Hengrui Cai, Zhengling Qi, Chengchun Shi, Eric B. Laber:
Sequential Knockoffs for Variable Selection in Reinforcement Learning. CoRR abs/2303.14281 (2023) - 2021
- [j6]Daniel J. Luckett, Eric B. Laber, Siyeon Kim, Michael R. Kosorok:
Estimation and Optimization of Composite Outcomes. J. Mach. Learn. Res. 22: 167:1-167:40 (2021) - [c2]Alex Cloud, Eric B. Laber:
Variance Decompositions for Extensive-Form Games. CoG 2021: 1-8
2010 – 2019
- 2019
- [j5]Ying-Qi Zhao, Eric B. Laber, Yang Ning, Sumona Saha, Bruce E. Sands:
Efficient augmentation and relaxation learning for individualized treatment rules using observational data. J. Mach. Learn. Res. 20: 48:1-48:23 (2019) - [j4]Wenhao Hu, Eric B. Laber, Clay Barker, Leonard A. Stefanski:
Assessing Tuning Parameter Selection Variability in Penalized Regression. Technometrics 61(2): 154-164 (2019) - [i11]Neal S. Grantham, Brian J. Reich, Eric B. Laber, Krishna Pacifici, Robert R. Dunn, Noah Fierer, Matthew Gebert, Julia S. Allwood, Seth A. Faith:
Global forensic geolocation with deep neural networks. CoRR abs/1905.11765 (2019) - [i10]Jesse Clifton, Lili Wu, Eric B. Laber:
Parameterized Exploration. CoRR abs/1907.06090 (2019) - [i9]Zhen Li, Eric B. Laber:
Convergence Rates of Posterior Distributions in Markov Decision Process. CoRR abs/1907.09083 (2019) - [i8]Longshaokan Wang, Eric B. Laber, Yeng Saanchi, Sherrie Caltagirone:
Sex Trafficking Detection with Ordinal Regression Neural Networks. CoRR abs/1908.05434 (2019) - [i7]Naim U. Rashid, Daniel J. Luckett, Jingxiang Chen, Michael T. Lawson, Longshaokan Wang, Yunshu Zhang, Eric B. Laber, Yufeng Liu, Jen Jen Yeh, Donglin Zeng, Michael R. Kosorok:
High dimensional precision medicine from patient-derived xenografts. CoRR abs/1912.06667 (2019) - 2018
- [i6]Daniel J. Luckett, Eric B. Laber, Samer S. El-Kamary, Cheng Fan, Ravi Jhaveri, Charles M. Perou, Fatma M. Shebl, Michael R. Kosorok:
Receiver Operating Characteristic Curves and Confidence Bands for Support Vector Machines. CoRR abs/1807.06711 (2018) - [i5]Zhen Li, Nicholas J. Meyer, Eric B. Laber, Robert T. Brigantic:
Thompson Sampling for Pursuit-Evasion Problems. CoRR abs/1811.04471 (2018) - 2016
- [j3]Paulo C. Rodrigues
, Eric B. Laber:
Preface. Commun. Stat. Simul. Comput. 45(7): 2657 (2016) - [j2]Daniel J. Lizotte, Eric B. Laber:
Multi-Objective Markov Decision Processes for Data-Driven Decision Support. J. Mach. Learn. Res. 17: 211:1-211:28 (2016) - [i4]Susan A. Murphy, Yanzhen Deng, Eric B. Laber, Hamid Reza Maei, Richard S. Sutton, Katie Witkiewitz:
A Batch, Off-Policy, Actor-Critic Algorithm for Optimizing the Average Reward. CoRR abs/1607.05047 (2016) - 2012
- [i3]Phillip J. Schulte, Anastasios A. Tsiatis, Eric B. Laber, Marie Davidian:
Q- and A-learning Methods for Estimating Optimal Dynamic Treatment Regimes. CoRR abs/1202.4177 (2012) - [i2]Eric B. Laber, Susan A. Murphy:
Small Sample Inference for Generalization Error in Classification Using the CUD Bound. CoRR abs/1206.3274 (2012) - [i1]Eric B. Laber, Daniel J. Lizotte, Bradley Ferguson:
Set-valued dynamic treatment regimes for competing outcomes. CoRR abs/1207.3100 (2012) - 2011
- [j1]Susan M. Shortreed, Eric B. Laber, Daniel J. Lizotte
Informing sequential clinical decision-making through reinforcement learning: an empirical study. Mach. Learn. 84(1-2): 109-136 (2011)
2000 – 2009
- 2008
- [c1]Eric B. Laber, Susan A. Murphy:
Small Sample Inference for Generalization Error in Classification Using the CUD Bound. UAI 2008: 357-365
Coauthor Index
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