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ORCIDMichael Jong Kim
Person information
- affiliation: University of British Columbia, Sauder School of Business, Vancouver, BC, Canada
- affiliation (PhD 2012): University of Toronto, Department of Mechanical and Industrial Engineering, ON, Canada
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2020 – today
- 2023
[j16]Ya-Tang Chuang
, Michael Jong Kim:
Bayesian Inventory Control: Accelerated Demand Learning via Exploration Boosts. Oper. Res. 71(5): 1515-1529 (2023)- [i4]Michael Gimelfarb, Michael Jong Kim:
Thompson Sampling for Parameterized Markov Decision Processes with Uninformative Actions. CoRR abs/2305.07844 (2023) - 2022
- [j15]Jussi Keppo, Michael Jong Kim, Xinyuan Zhang:
Learning Manipulation Through Information Dissemination. Oper. Res. 70(6): 3490-3510 (2022) - 2021
- [j14]Akram Khaleghei, Michael Jong Kim:
Optimal Control of Partially Observable Semi-Markovian Failing Systems: An Analysis Using a Phase Methodology. Oper. Res. 69(4): 1282-1304 (2021) - [j13]Jun-ya Gotoh, Michael Jong Kim, Andrew E. B. Lim:
Calibration of Distributionally Robust Empirical Optimization Models. Oper. Res. 69(5): 1630-1650 (2021) - [i3]Jun-ya Gotoh, Michael Jong Kim, Andrew E. B. Lim:
A data-driven approach to beating SAA out-of-sample. CoRR abs/2105.12342 (2021) - 2020
- [j12]Michael Jong Kim:
Variance Regularization in Sequential Bayesian Optimization. Math. Oper. Res. 45(3): 966-992 (2020) - [i2]Jun-ya Gotoh, Michael Jong Kim, Andrew E. B. Lim:
Worst-case sensitivity. CoRR abs/2010.10794 (2020)
2010 – 2019
- 2019
- [j11]Dragan Banjevic, Michael Jong Kim:
Thompson Sampling for Stochastic Control: The Continuous Parameter Case. IEEE Trans. Autom. Control. 64(10): 4137-4152 (2019) - 2018
- [j10]Jun-ya Gotoh, Michael Jong Kim, Andrew E. B. Lim:
Robust empirical optimization is almost the same as mean-variance optimization. Oper. Res. Lett. 46(4): 448-452 (2018) - 2017
- [j9]Michael Jong Kim:
Thompson Sampling for Stochastic Control: The Finite Parameter Case. IEEE Trans. Autom. Control. 62(12): 6415-6422 (2017) - [i1]Jun-ya Gotoh, Michael Jong Kim, Andrew E. B. Lim:
Calibration of Distributionally Robust Empirical Optimization Models. CoRR abs/1711.06565 (2017) - 2016
- [j8]Michael Jong Kim:
Robust Control of Partially Observable Failing Systems. Oper. Res. 64(4): 999-1014 (2016) - [j7]Michael Jong Kim, Andrew E. B. Lim:
Robust Multiarmed Bandit Problems. Manag. Sci. 62(1): 264-285 (2016) - 2013
- [j6]Michael Jong Kim, Viliam Makis:
Joint Optimization of Sampling and Control of Partially Observable Failing Systems. Oper. Res. 61(3): 777-790 (2013) - [j5]Rui Jiang, Michael Jong Kim, Viliam Makis:
Availability maximization under partial observations. OR Spectr. 35(3): 691-710 (2013) - 2012
- [j4]Rui Jiang, Michael Jong Kim, Viliam Makis:
A Bayesian model and numerical algorithm for CBM availability maximization. Ann. Oper. Res. 196(1): 333-348 (2012) - [j3]Rui Jiang, Michael Jong Kim, Viliam Makis:
Maximum Likelihood Estimation for a Hidden Semi-Markov Model with Multivariate Observations. Qual. Reliab. Eng. Int. 28(7): 783-791 (2012) - 2011
- [j2]Michael Jong Kim, Rui Jiang, Viliam Makis, Chi-Guhn Lee:
Optimal Bayesian fault prediction scheme for a partially observable system subject to random failure. Eur. J. Oper. Res. 214(2): 331-339 (2011) - 2010
- [c1]Rui Jiang, Michael Jong Kim, Viliam Makis:
Residual life prediction for systems subject to condition monitoring. CASE 2010: 106-111
2000 – 2009
- 2009
- [j1]Michael Jong Kim, Viliam Makis:
Optimal maintenance policy for a multi-state deteriorating system with two types of failures under general repair. Comput. Ind. Eng. 57(1): 298-303 (2009)
Coauthor Index
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