Research

Preprints

1.  The Bernstein-–von Mises theorem for Bayesian one-pass online learning

   • Jeyong Lee, Junhyeok Choi, Dongguen Kim, and Minwoo Chae

2.  Online Thompson sampling for generalized linear bandits

   • Dongguen Kim, Jeyong Lee, Junhyeok Choi, Gi-Soo Kim, and Minwoo Chae

Publications

3.  Online Bernstein-von Mises theorem

   • Jeyong Lee, Junhyeok Choi, and Minwoo Chae

   • Journal of Machine Learning Research. (2026)

4. Online Bayesian inference for Cox proportional hazards model

   • Junhyeok Choi, Jeyong Lee, Yongdai Kim, and Minwoo Chae 

   • Journal of Computational and Graphical Statistics. (2026)

5.  Advances in Bayesian model selection consistency for high-dimensional generalized linear models

   • Jeyong Lee, Minwoo Chae*, and Ryan Martin

   • Annals of Statistics. (2025)

6.  Group-constrained latent Dirichlet allocation for fashion item recommendation

   • Seonghwi Kim, Jeyong Lee, Junhyeok Choi, and Minwoo Chae

   • Journal of the Korean Statistical Society. (2025) 

7.  Rates of convergence for nonparametric estimation of singular distributions using generative adversarial networks

   • Jeyong Lee, Hyeok Kyu Kwon, and Minwoo Chae

   • Journal of the Korean Statistical Society. (2025)