Research
My main research interests broadly lie in statistical theory and methodology. In particular, I was attracted by decision theory that combines the information from the data with consequences of our decisions in a given statistical problem. Current research interests also include the model misspecification problem, shape restricted estimation, high-dimensional analysis, and adaptive and computationally feasible estimators.
Publications and preprints
Kim, A. K. H.* and Guntuboyina, A. (2022) Minimax bounds for estimating multivariate Gaussian location mixtures, Electronic Journal of Statistics 16, 1461-1484.
Choi, T., Kim, A. K. H. and Choi, S. (2021) Semiparametric least-squares regression with doubly censored data. Computational Statistics & Data Analysis 164, 107306.
Kim, A. K. H.* and Chung, H. (2021) The effect of rebalancing on LDA in imbalanced classification. Stat, 10(1), e384.
Feng, O. Y., Guntuboyina, A., Kim, A. K. H.* and Samworth, R. J. (2021) Adaptation in multivariate log-concave density estimation. Annals of Statistics 49(1), 129-153. Arxiv 1812.11634.
Kim, A. K. H. (2020) Obtaining minimax lower bounds: a review. Journal of Korean Statistical Society 49, 673-701.
Kim, A. K. H., Guntuboyina, A. and Samworth, R. J. (2018) Adaptation in log-concave density estimation. Annals of Statistics 46(5), 2279-2306. Available here.
Carpentier, A.^ and Kim, A. K. H.^ (2018) An iterative hard thresholding estimator for low rank matrix recovery with explicit limiting distribution. Statistica Sinica 28(3), 1371-1393. Available here.
Kim, A. K. H. and Shin, S. J. (2017) The cumulative Kolmogorov filter for model-free screening in ultrahigh dimensional data. Statistics and Probability Letters 126, 238-243.
Kim, A. K. H. and Samworth, R. J. (2016) Global rates of convergence in log-concave density estimation. Annals of Statistics 44 (6), 2756-2779. Available here and the supplement material can be found here. Chosen by the editors to be presented in a JSM 2017 Special Invited session (only four papers were chosen in total).
Kim, A. K. H. and Zhou, H. H. (2015) Tight minimax rates for manifold estimation under Hausdorff loss, Electronic Journal of Statistics 9 (1), 1562-1582. Available here.
Carpentier, A.^ and Kim, A. K. H.^ (2015) Adaptive and minimax optimal estimation of the tail coefficient, Statistica Sinica 25 (3), 1133-1144. Available here.
Carpentier, A. and Kim, A. K. H.* (2014) Adaptive confidence intervals for the tail coefficient in a wide second order class of Pareto models. Electronic Journal of Statistics 8 (2), 2066-2110.Available here.
Kim, A. K. H.* (2014) Minimax bounds for estimation of normal mixtures. Bernoulli 20 (4), 1802-1818. Available here.
* : corresponding author
^: authors contributed equally
Conference and Seminar presentations
Minimax bounds for estimating multivariate Gaussian location mixtures, KSS(online), Korea, Nov 2021
Global rates of convergence in scale mixtures of uniform density estimation, Ecosta(online), Hong Kong, June 2021, WC2020(online), Korea, Oct 2021
Adaptation in multivariate log-concave density estimation, ICSA, China, Dec 2019, Joint Statistical Meetings(virtual), US, Aug 2020,
Adaptation in log-concave density estimation - SNU dept seminar, Korea, May 2017, Young Statistician's Meeting, Korea, June, 2017 & Joint Statistical Meetings, Baltimore, US, Aug 3, 2017
An iterative hard thresholding estimator for low rank matrix recovery with explicit limiting distribution - CMStatistics, London, U.K., Dec 13, 2015 & KSS, Korea, Nov, 2016
Adaptive confidence intervals for the tail coefficient in a wide second order class of Pareto models - European Meeting of Statisticians, Netherlands, Jul 9, 2015
Adaptive and minimax optimal estimation of the tail coefficient, and associated confidence intervals - Korea University, Seoul, Korea, May 28, 2015
Global rates of convergence in log-concave density estimation - IMS-APRM, Taipei, Taiwan, Jul 1, 2014
Global convergence rates for estimating log-concave densities - Joint Statistical Meetings, Montreal, Canada, Aug 4, 2013
An overview of the minimax paradigm - Cambridge Statistics Initiative (CSI) One-Day Meeting, Cambridge, UK, Apr 22, 2013
Minimax lower bounds using Assouad's lemma - Cambridge Statistics Reading Group Seminar, Cambridge, UK, Feb 27, 2013
Minimax bounds for estimation of normal location mixtures - Yale Probabilistic Networks Group (YPNG) Seminar, Yale University, Connecticut, US, Feb 3, 2012
Minimax lower bound in sparse approximation sets - Joint Statistical Meetings, Vancouver, Canada, Aug 3, 2010
Arlene (Kyoung Hee) Kim, Email: arlenent[at]korea.ac.kr, Mailing: Department of Statistics, Political Science and Economics Building, 145 Anam-ro, Seongbuk-gu, Seoul, Korea (02841), Tel: +82-2-3290-2232