Penalized logspline density estimation using total variation penalty. - Kwan-Young Bak; Jae-Hwan Jhong; Jung-Jun Lee; Jae-Kyung Shin; Ja-Yong Koo (Comput. Stat. Data Anal., 2021)

Penalized additive neural network regression. - Jae-Kyung Shin; Kwan-Young Bak; Ja-Yong Koo (Intell. Data Anal., 2022)

Sparse neural network regression with variable selection. - Jae-Kyung Shin; Kwan-Young Bak; Ja-Yong Koo (Comput. Intell., 2022)

Minimax Density Estimation Under Radial Symmetry. - Kwan-Young Bak; Ja-Yong Koo (IEEE Access, 2023)

An Adaptive Neural Network Regression Method for Structure Identification. - Jae-Kyung Shin; Kwan-Young Bak; Ja-Yong Koo (J. Comput. Graph. Stat., 2024)

The regularization paths of total variation-penalized regression splines. - Kwan-Young Bak (Commun. Stat. Simul. Comput., 2024)

ALTBI: Constructing Improved Outlier Detection Models via Optimization of Inlier-Memorization Effect. - Seoyoung Cho; Jaesung Hwang; Kwan-Young Bak; Dongha Kim (AAAI, 2025)

Multi-Task Nonparametric Regression Under Joint Sparsity. - Jae-Hwan Jhong; Gyeongmin Kim; Kwan-Young Bak (IEEE Access, 2025)

Linear covariance selection model via ℓ1-penalization. - Kwan-Young Bak; Seongoh Park (Comput. Stat. Data Anal., 2025)

Low-Dimensional Adaptive Neural Network Regression With Directional Change Detection via Nuclear Norm Penalization. - Yongku Kim; Jae-Hwan Jhong; Ja-Yong Koo; Kwan-Young Bak (Stat. Anal. Data Min., 2025)