Optimal maintenance policy for a multi-state deteriorating system with two types of failures under general repair. - Michael Jong Kim; Viliam Makis (Comput. Ind. Eng., 2009)

Residual life prediction for systems subject to condition monitoring. - Rui Jiang; Michael Jong Kim; Viliam Makis (CASE, 2010)

Optimal Bayesian fault prediction scheme for a partially observable system subject to random failure. - Michael Jong Kim; Rui Jiang; Viliam Makis; Chi-Guhn Lee (Eur. J. Oper. Res., 2011)

A Bayesian model and numerical algorithm for CBM availability maximization. - Rui Jiang; Michael Jong Kim; Viliam Makis (Ann. Oper. Res., 2012)

Maximum Likelihood Estimation for a Hidden Semi-Markov Model with Multivariate Observations. - Rui Jiang; Michael Jong Kim; Viliam Makis (Qual. Reliab. Eng. Int., 2012)

Joint Optimization of Sampling and Control of Partially Observable Failing Systems. - Michael Jong Kim; Viliam Makis (Oper. Res., 2013)

Availability maximization under partial observations. - Rui Jiang; Michael Jong Kim; Viliam Makis (OR Spectr., 2013)

Robust Control of Partially Observable Failing Systems. - Michael Jong Kim (Oper. Res., 2016)

Robust Multiarmed Bandit Problems. - Michael Jong Kim; Andrew E. B. Lim (Manag. Sci., 2016)

Thompson Sampling for Stochastic Control: The Finite Parameter Case. - Michael Jong Kim (IEEE Trans. Autom. Control., 2017)

Robust empirical optimization is almost the same as mean-variance optimization. - Jun-ya Gotoh; Michael Jong Kim; Andrew E. B. Lim (Oper. Res. Lett., 2018)

Thompson Sampling for Stochastic Control: The Continuous Parameter Case. - Dragan Banjevic; Michael Jong Kim (IEEE Trans. Autom. Control., 2019)

Worst-case sensitivity. - Jun-ya Gotoh; Michael Jong Kim; Andrew E. B. Lim (CoRR, 2020)

Variance Regularization in Sequential Bayesian Optimization. - Michael Jong Kim (Math. Oper. Res., 2020)

A data-driven approach to beating SAA out-of-sample. - Jun-ya Gotoh; Michael Jong Kim; Andrew E. B. Lim (CoRR, 2021)

Calibration of Distributionally Robust Empirical Optimization Models. - Jun-ya Gotoh; Michael Jong Kim; Andrew E. B. Lim (Oper. Res., 2021)

Optimal Control of Partially Observable Semi-Markovian Failing Systems: An Analysis Using a Phase Methodology. - Akram Khaleghei; Michael Jong Kim (Oper. Res., 2021)

Learning Manipulation Through Information Dissemination. - Jussi Keppo; Michael Jong Kim; Xinyuan Zhang (Oper. Res., 2022)

Thompson Sampling for Parameterized Markov Decision Processes with Uninformative Actions. - Michael Gimelfarb; Michael Jong Kim (CoRR, 2023)

Bayesian Inventory Control: Accelerated Demand Learning via Exploration Boosts. - Ya-Tang Chuang; Michael Jong Kim (Oper. Res., 2023)

Technical Note - A Data-Driven Approach to Beating SAA Out of Sample. - Jun-ya Gotoh; Michael Jong Kim; Andrew E. B. Lim (Oper. Res., 2025)

Distributionally Robust Optimization is a Multi-Objective Problem. - Jun-ya Gotoh; Michael Jong Kim; Andrew E. B. Lim (CoRR, 2025)