Publication

Submitted Papers

• Group-constrained latent Dirichlet allocation for fashion item recommendation
  Kim, S., Lee, J., Choi, J., Cho, J., Park, K. and Chae, M.
  

• Rates of convergence for nonparametric estimation of singular distributions using generative adversarial networks [arXiv]
  Chae, M.
  

• A likelihood approach to nonparametric estimation of a singular distribution using deep generative models [arXiv]
  Chae, M., Kim, D., Kim, Y. and Lin, L.
  

• Online learning for Dirichlet process mixture models via weakly conjugate approximation
  Jeong, K., Kim, Y. and Chae, M.

Publications

• Adaptive Bayesian inference for current status data on a grid
  Chae, M.
  Bernoulli. (To appear)

• Posterior asymptotics in Wasserstein metrics on the real line [arXiv]
  Chae, M., De Blasi, P. and Walker, S.
  Electronic Journal of Statistics. (2021). 15:3635-3677

• Bayesian high-dimensional semi-parametric inference beyond sub-Gaussian errors
  Lee, K., Chae, M. and Lin, L.
  Journal of the Korean Statistical Society. (2021). 50(2):511-527

• Wasserstein upper bounds of the total variation for smooth densities
  Chae, M. and Walker, S.
  Statistics & Probability Letters. (2020). 163:1-6

• An EM-based iterative method for solving large sparse linear systems [arXiv]
  Chae, M. and Walker, S.
  Linear and Multilinear Algebra. (2020). 68(1):45–62

• Bayesian sparse linear regression with unknown symmetric error [arXiv]
  Chae, M., Lin, L. and Dunson, D.
  Information and Inference. (2019). 8(3):621–653

• The semi-parametric Bernstein-von Mises theorem for regression models with symmetric errors [arXiv]
  Chae, M., Kim, Y. and Kleijn, B.
  Statistica Sinica. (2019). 29(3):1465–1487

• On an algorithm for solving Fredholm integrals of the first kind [arXiv]
  Chae, M., Martin, R. and Walker, S.
  Statistics and Computing. (2019). 29(4):645–654

• Additive time-dependent hazard model with doubly truncated data
  Frank, G., Chae, M. and Kim, Y.
  Journal of the Korean Statistical Society. (2019). 48(2):179–193

• Bayesian consistency for a nonparametric stationary Markov model
  Chae, M. and Walker, S.
  Bernoulli. (2019). 25(2):877–901

• Convergence of an iterative algorithm to the nonparametric MLE of a mixing distribution [arXiv]
  Chae, M., Martin, R. and Walker, S.
  Statistics & Probability Letters. (2018). 140:142–146

• A novel approach to Bayesian consistency
  Chae, M. and Walker, S.
  Electronic Journal of Statistics. (2017). 11(2):4723–4745

• An online Gibbs sampler algorithm for hierarchical Dirichlet processes prior
  Kim, Y., Chae, M., Jeong, K., Kang, B. and Chung, H.
  In Proceedings of the ECML-PKDD Discovery Challenge Workshop. (2016). pp. 509–523

• A closer look at the personality turnover relationship: criterion expansion, dark traits, and time
  Woo, S., Chae, M., Jebb, A. and Kim, Y.
  Journal of Management. (2016). 42(2):357–385

• Beta processes and survival analysis
  Kim, Y. and Chae, M.
  The Korean Journal of Applied Statistics. (2014). 27(6):891–907 (Written in Korean)

• Development of high-value traits of dairy cattle using survival analysis
  Jeong, K., Chae, M., Lee, S., Cho, K. and Kim, Y.
  Journal of the Korean Data Analysis Society. (2013). 15(5):2407–2416 (Written in Korean)

• Documents recommendation using large citation data
  Chae, M., Kang, M. and Kim, Y.
  Journal of the Korean Data and Information Science Society. (2013). 24(5):999–1011 (Written in Korean)

• A mixture of beta-Dirichlet processes prior for Bayesian analysis of event history data
  Chae, M., Weissbach, R., Cho, K. and Kim, Y.
  Journal of the Korean Statistical Society. (2013). 42(3):313–321