Publications

Published and accepted papers are listed by year. Working papers appear below.

2026

• Lee, E. and Park, S.* (2026). Distilling Conditional Image Generators into Spatial Effect Maps. NeurIPS 2026 (accepted). Conference

• Kim, J. and Park, S.* (2026). Transfer Learning in High-dimensional Ising Models. ICML 2026. Conference · arXiv

• Jung, W., Park, S.^, Hong, H. G., and Lee, E. (2026). Reduced varying coefficient models for regional quantile regression with multiple responses. Biometrics, 82(1), ujag040. Article · Code

• Park, S. and Lee, E. (2026). Overparametrized linear regression with noisy and missing data. Journal of the Korean Statistical Society, 55(2), 381–405. Article

• Park, S.*, Lee, E., Kim, H., and Zhao, H. (2026). Transfer Learning Under Large-Scale Low-Rank Regression Models. Journal of the American Statistical Association, Theory and Methods, 121(554), 1154–1166. Article · Code

2025

• Kim, Y., Kim, I.*, and Park, S.* (2025). Transfer learning for benign overfitting in high-dimensional linear regression. NeurIPS 2025 (Spotlight). Proceedings · arXiv

2024

• Lee, E.^, Park, S.^, Mammen, E., and Park, B. U. (2024). Efficient functional Lasso kernel smoothing for high-dimensional additive regression, Annals of Statistics, 52(4). 1741-1773. Article

• Park, S., Lee, E.*, and Zhao, H. (2024). Low-rank regression models for multiple binary responses and their applications to cancer cell-line encyclopedia data. Journal of the American Statistical Association, Theory & Methods, 119, 202-216. Article

2023

• Kim, H., Lee, E. and Park, S.* (2023). Debiased inference for heterogeneous subpopulations in a high-dimensional logistic regression model, Scientific Reports, 13, 21979.

• Park, S., Kim, H. and Lee, E.* (2023). Regional quantile regression for multiple responses. Computational Statistics and Data Analysis, 188, 107826.

• Park, S.^, Lee, E.^ and Hong, G.* (2023). Varying-coefficients for regional quantile via KNN-based LASSO with applications to health outcome study, Statistics in Medicine, 42, 3903-3918.

• Lee, E.^, Park, S.^, Lee, S. and Hong, G. (2023). Quantile forward regression for high-dimensional survival data. Lifetime Data Analysis, 29, 769-806.

2022

• Tang, D., Park, S., and Zhao, H. (2022). SCADIE: simultaneous estimation of cell type proportions and cell type-specific gene expressions using SCAD-based iterative estimating procedure. Genome Biology, 23, 129.

• Cho, Y. and Park, S. * (2022). Multivariate response regression with low-rank and generalized sparsity. Journal of the Korean Statistical Society, 51, 847-867.

• Lee, E., Cho, J., and Park, S.* (2022). Penalized kernel quantile regression for varying coefficient models. Journal of Statistical Planning and Inference, Vol. 217, 8-23.

2021

• Park, S. and Lee, E. (2021). Hypothesis testing of varying coefficients for regional quantiles. Computational Statistics and Data Analysis, Vol. 159, 107204.

• Lee, E. and Park, S.^ (2021). Poisson reduced-rank models with sparse loadings. Journal of the Korean Statistical Society, Vol. 50, 1079-1097.

• Park, S., Xu, H., and Zhao, H.* (2021). Integrating multidimensional data for clustering analysis with applications to cancer patient data. Journal of the American Statistical Association, Applications & Case Studies, Vol. 116, No.533, 14-26. Article

2020

• Tang, D., Park, S.^, and Zhao, H. (2020). NITUMID: NMF-based Immune-TUmor MIcroenvironment Deconvolution. Bioinformatics, Vol. 36, No. 5, 1344-1350.

2019

• Park, S.* and Zhao, H. (2019). Sparse principal component analysis with missing observations. Annals of Applied Statistics, Vol.13, No.2, 1016-1042.

• Park, S.* and Lee, S. (2019). Linear programming models for portfolio optimization using a benchmark. European Journal of Finance, Vol. 25, 435-457.

2018

• Park, S.* and Zhao, H. (2018). Spectral clustering based on learning similarity matrix. Bioinformatics, Vol. 34, No. 12, 2069-2076.

2017

• Park, S.*, He, X., and Zhou, S. (2017). Dantzig-type penalization for multiple quantile regression with high dimensional covariates. Statistica Sinica, Vol. 27, No. 4, 1619-1638. (Winner of the 2015 Student Paper Competition in the ASA Section on SLDM).

• Park, S.* and He, X. (2017). Hypothesis testing for regional quantiles. Journal of Statistical Planning and Inference, Vol. 191, 13-24.

• Greenewald, K., Park, S., Giessing, A., and Zhou, S. (2017). Time-Varying Matrix-Variate Graphical Models. NeurIPS.