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Hongju Park
Hongju Park
Ph.D. Student, University of Georgia
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Partially collapsed Gibbs sampling for latent Dirichlet allocation
H Park, T Park, YS Lee
Expert Systems with Applications 131, 208-218, 2019
242019
Analysis of Thompson sampling for partially observable contextual multi-armed bandits
H Park, MKS Faradonbeh
IEEE Control Systems Letters 6, 2150-2155, 2021
152021
Efficient algorithms for learning to control bandits with unobserved contexts
H Park, MKS Faradonbeh
IFAC-PapersOnLine 55 (12), 383-388, 2022
52022
Worst-case performance of greedy policies in bandits with imperfect context observations
H Park, MKS Faradonbeh
2022 IEEE 61st Conference on Decision and Control (CDC), 1374-1379, 2022
42022
Analysis of patterns in meteorological research and development using a text-mining algorithm
H Park, H Kim, T Park, YS Lee
The Korean Journal of Applied Statistics 29 (5), 935-947, 2016
32016
A regret bound for greedy partially observed stochastic contextual bandits
H Park, MKS Faradonbeh
Decision Awareness in Reinforcement Learning Workshop at ICML 2022, 2022
12022
Thompson Sampling in Partially Observable Contextual Bandits
H Park, MKS Faradonbeh
arXiv preprint arXiv:2402.10289, 2024
2024
Sequentially Adaptive Experimentation for Learning Optimal Options subject to Unobserved Contexts
H Park, MKS Faradonbeh
NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning in ¡¦, 2023
2023
Online Learning of Optimal Prescriptions under Bandit Feedback with Unknown Contexts
H Park, MKS Faradonbeh
NeurIPS 2023 Workshop on New Frontiers of AI for Drug Discovery and Development, 2023
2023
Balancing exploration and exploitation in Partially Observed Linear Contextual Bandits via Thompson Sampling
H Park, MKS Faradonbeh
ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems, 2023
2023
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