Publication

Submitted Papers

• Machine learning-based risk scoring using clinical and surgical variables for severe complications after rectal cancer surgery
  Seung Ho Song, Hyeok Kyu Kwon, Jun Seok Park, Soo Yeun Park, Hye Jin Kim, Jeongjik Lee, Minwoo Chae & Gyu-Seog Choi.
  

• Multimodal dataset distillation made simple by prototype-guided data synthesis
  Junhyeok Choi, Sangwoo Mo & Minwoo Chae.
  

• Distributionally robust classification for multi-source unsupervised domain adaptation
  Seonghwi Kim, Sung Ho Jo, Wooseok Ha & Minwoo Chae.
  

• Evaluating image generation models via sliced Wasserstein distance
  Hyeok Kyu Kwon, Jaeseung Yang & Minwoo Chae.
  

• Online Bernstein-von Mises theorem [arXiv]
  Jeyong Lee, Junhyeok Choi & Minwoo Chae.
  

• Mitigating spurious correlation via distributionally robust learning with hierarchical ambiguity sets
  Sung Ho Jo, Seonghwi Kim & Minwoo Chae.
  

• Nonparametric estimation of a factorizable density using diffusion models [arXiv]
  Hyeok Kyu Kwon, Dongha Kim, Ilsang Ohn & Minwoo Chae.
  

Publications

• Wearable soft ionic tactile controller for virtual reality: decoupling normal and shear forces without motion artifacts
  Woosung Cho, Younghyun Lee, Taeyeong Kim, Jun Choi, Dongguen Kim, Minwoo Chae, Chaeyong Park, Wonjeong Suh & Unyong Jeong.
  ACS Applied Materials & Interfaces. (2025+).

• Online Bayesian inference for Cox proportional hazards model
  Junhyeok Choi, Jeyong Lee, Yongdai Kim & Minwoo Chae.
  Journal of Computational and Graphical Statistics. (2025+).

• A Bayesian approach to contextual dynamic pricing using the proportional hazards model with discrete price data
  Dongguen Kim, Young-Geun Choi & Minwoo Chae.
  Neural Information Processing Systems (NeurIPS). (2025).

• A monotone single-index model for spatially-referenced multistate current status data
  Snigdha Das, Minwoo Chae, Debdeep Pati & Dipankar Bandyopadhyay.
  Biometrics. (2025)

• Advances in Bayesian model selection consistency for high-dimensional generalized linear models [arXiv]
  Jeyong Lee, Minwoo Chae & Ryan Martin.
  Annals of Statistics. (2025).

• Group-constrained latent Dirichlet allocation for fashion item recommendation
  Seonghwi Kim, Jeyong Lee, Junhyeok Choi, Minwoo Chae, Minseok Song, Jong Hyun Cho & Kyungho Park.
  Journal of the Korean Statistical Society. (2025).

• On reverse inequalities for Besov integral probability metrics between smooth densities
  Jeongjik Lee & Minwoo Chae.
  Statistics & Probability Letters. (2025).

• Rates of convergence for nonparametric estimation of singular distributions using generative adversarial networks [arXiv]
  Jeyong Lee, Hyeok Kyu Kwon & Minwoo Chae.
  Journal of the Korean Statistical Society. (2025).

• Fairness through matching
  Kunwoong Kim, Insung Kong, Jongjin Lee, Minwoo Chae, Sangchul Park & Yongdai Kim.
  Transactions on Machine Learning Research. (2025).

• Using statistical models for optimal packaging in semiconductor manufacturing processes
  Dongguen Kim, Heejin Kim, Yejin Kim, Minwoo Chae, Young Myoung Ko, Young-Mok Bae, Hyungsub Sim, Young Chan Oh & Keum Hwan Noh.
  Journal of the Korean Statistical Society. (2025).

• Wasserstein upper bounds of Lp-norms for multivariate densities in Besov spaces
  Minwoo Chae.
  Statistics & Probability Letters. (2024).

• Minimax optimal density estimation using a shallow generative model with a one-dimensional latent variable [arXiv]
  Hyeok Kyu Kwon & Minwoo Chae.
  International Conference on Artificial Intelligence and Statistics (AISTATS). (2024).

• A likelihood approach to nonparametric estimation of a singular distribution using deep generative models [arXiv]
  Minwoo Chae, Dongha Kim, Yongdai Kim & Lizhen Lin.
  Journal of Machine Learning Research. (2023).

• Online learning for Dirichlet process mixture models via weakly conjugate approximation
  Kuhwan Jeong, Minwoo Chae & Yongdai Kim.
  Computational Statistics and Data Analysis. (2023).

• Adaptive Bayesian inference for current status data on a grid
  Minwoo Chae.
  Bernoulli. (2023).

• Posterior asymptotics in Wasserstein metrics on the real line [arXiv]
  Minwoo Chae, Pierpaolo De Blasi & Stephen Walker.
  Electronic Journal of Statistics. (2021).

• Bayesian high-dimensional semi-parametric inference beyond sub-Gaussian errors
  Kyoungjae Lee, Minwoo Chae & Lizhen Lin.
  Journal of the Korean Statistical Society. (2021).

• Wasserstein upper bounds of the total variation for smooth densities
  Minwoo Chae & Stephen Walker.
  Statistics & Probability Letters. (2020).

• An EM-based iterative method for solving large sparse linear systems [arXiv]
  Minwoo Chae & Stephen Walker.
  Linear and Multilinear Algebra. (2020).

• Bayesian sparse linear regression with unknown symmetric error [arXiv]
  Minwoo Chae, Lizhen Lin & David Dunson.
  Information and Inference. (2019).

• The semi-parametric Bernstein-von Mises theorem for regression models with symmetric errors [arXiv]
  Minwoo Chae, Yongdai Kim & Bas Kleijn.
  Statistica Sinica. (2019).

• On an algorithm for solving Fredholm integrals of the first kind [arXiv]
  Minwoo Chae, Ryan Martin & Stephen Walker.
  Statistics and Computing. (2019).

• Additive time-dependent hazard model with doubly truncated data
  Gordon Frank, Minwoo Chae & Yongdai Kim.
  Journal of the Korean Statistical Society. (2019).

• Bayesian consistency for a nonparametric stationary Markov model
  Minwoo Chae & Stephen Walker.
  Bernoulli. (2019).

• Convergence of an iterative algorithm to the nonparametric MLE of a mixing distribution [arXiv]
  Minwoo Chae, Ryan Martin & Stephen Walker.
  Statistics & Probability Letters. (2018).

• A novel approach to Bayesian consistency
  Minwoo Chae & Stephen Walker.
  Electronic Journal of Statistics. (2017).

• An online Gibbs sampler algorithm for hierarchical Dirichlet processes prior
  Yongdai Kim, Minwoo Chae, Kuhwan Jeong, Byungyup Kang & Hyoju Chung.
  European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD). (2016).

• A closer look at the personality turnover relationship: criterion expansion, dark traits, and time
  Sang Eun Woo, Minwoo Chae, Andrew Jebb & Yongdai Kim.
  Journal of Management. (2016).

• Beta processes and survival analysis
  Yongdai Kim & Minwoo Chae.
  Korean Journal of Applied Statistics. (2014). (Written in Korean)

• Development of high-value traits of dairy cattle using survival analysis
  Kuhwan Jeong, Minwoo Chae, Seulgi Lee, Kwang Hyun Cho & Yongdai Kim.
  Journal of the Korean Data Analysis Society. (2013). (Written in Korean)

• Documents recommendation using large citation data
  Minwoo Chae, Minsoo Kang & Yongdai Kim.
  Journal of the Korean Data and Information Science Society. (2013). (Written in Korean)

• A mixture of beta-Dirichlet processes prior for Bayesian analysis of event history data
  Minwoo Chae, Rafael Weissbach, Kwang Hyun Cho & Yongdai Kim.
  Journal of the Korean Statistical Society. (2013).