Image Reconstruction using the Wavelet Transform for Positron Emission Tomography. - Yong Choi; Ja-Yong Koo; Nam-Yong Lee (IEEE Trans. Medical Imaging, 2001)

Poisson intensity estimation for tomographic data using a wavelet shrinkage approach. - L. Cavalier; Ja-Yong Koo (IEEE Trans. Inf. Theory, 2002)

Wavelet deconvolution. - Jianqing Fan; Ja-Yong Koo (IEEE Trans. Inf. Theory, 2002)

Rotational Matching Problems. - Gregory S. Chirikjian; Peter T. Kim; Ja-Yong Koo; Christine H. Lee (Int. J. Comput. Intell. Appl., 2004)

Inverse boosting for monotone regression functions. - Yuwon Kim; Ja-Yong Koo (Comput. Stat. Data Anal., 2005)

Structured polychotomous machine diagnosis of multiple cancer types using gene expression. - Ja-Yong Koo; Insuk Sohn; Sujong Kim; Jae Won Lee (Bioinform., 2006)

Erratum to "Inverse boosting for monotone regression functions" [Computational Statistics and Data Analysis 49 (2005) 757-770]. - Yuwon Kim; Ja-Yong Koo (Comput. Stat. Data Anal., 2006)

On the Use of Adaptive Nearest Neighbors for Missing Value Imputation. - Myoungshic Jhun; Hyeong Chul Jeong; Ja-Yong Koo (Commun. Stat. Simul. Comput., 2007)

Stepwise feature selection using generalized logistic loss. - Changyi Park; Ja-Yong Koo; Peter T. Kim; Jae Won Lee (Comput. Stat. Data Anal., 2008)

Classification of gene functions using support vector machine for time-course gene expression data. - Changyi Park; Ja-Yong Koo; Sujong Kim; Insuk Sohn; Jae Won Lee (Comput. Stat. Data Anal., 2008)

A Bahadur Representation of the Linear Support Vector Machine. - Ja-Yong Koo; Yoonkyung Lee; Yuwon Kim; Changyi Park (J. Mach. Learn. Res., 2008)

Asymptotic Minimax Bounds for Stochastic Deconvolution Over Groups. - Ja-Yong Koo; Peter T. Kim (IEEE Trans. Inf. Theory, 2008)

Weyl eigenvalue asymptotics and sharp adaptation on vector bundles. - Peter T. Kim; Ja-Yong Koo; Zhi-Ming Luo (J. Multivar. Anal., 2009)

Support Vector Machine Using k-Spatial Medians Clustering and Recovery Process. - Sungwan Bang; Ja-Yong Koo; Myoungshic Jhun (Commun. Stat. Simul. Comput., 2010)

Feature selection in the Laplacian support vector machine. - Sangjun Lee; Changyi Park; Ja-Yong Koo (Comput. Stat. Data Anal., 2011)

Frenet-Serret and the Estimation of Curvature and Torsion. - Kwang-Rae Kim; Peter T. Kim; Ja-Yong Koo; Michael R. Pierrynowski (IEEE J. Sel. Top. Signal Process., 2013)

Variable Selection for Naive Bayes Semisupervised Learning. - Byoung-Jeong Choi; Kwang-Rae Kim; Kyu-Dong Cho; Changyi Park; Ja-Yong Koo (Commun. Stat. Simul. Comput., 2014)

Meta-analytic support vector machine for integrating multiple omics data. - Sunghwan Kim 003; Jae-Hwan Jhong; Jung-Jun Lee; Ja-Yong Koo (BioData Min., 2017)

Erratum to: Meta-analytic support vector machine for integrating multiple omics data. - Sunghwan Kim 003; Jae-Hwan Jhong; Jung-Jun Lee; Ja-Yong Koo (BioData Min., 2017)

Node-Structured Integrative Gaussian Graphical Model Guided by Pathway Information. - Sunghwan Kim 003; Jae-Hwan Jhong; Jung-Jun Lee; Ja-Yong Koo; ByungYong Lee; Sungwon Han 003 (Comput. Math. Methods Medicine, 2017)

Identifying novel NF-kB-regulated immune genes in the human genome using a Discrete Kernel Structured Support Vector Machine. - Insuk Sohn; Sujong Kim; Jae Won Lee; Ja-Yong Koo; Junsu Ko (Model. Assist. Stat. Appl., 2017)

Variable Selection and Joint Estimation of Mean and Covariance Models with an Application to eQTL Data. - Jung-Jun Lee; Sunghwan Kim 003; Jae-Hwan Jhong; Ja-Yong Koo (Comput. Math. Methods Medicine, 2018)

Simultaneous estimation of quantile regression functions using B-splines and total variation penalty. - Jae-Hwan Jhong; Ja-Yong Koo (Comput. Stat. Data Anal., 2019)

Penalized log-density estimation using Legendre polynomials. - Jung-Jun Lee; Jae-Hwan Jhong; Young-Rae Cho; Sunghwan Kim 003; Ja-Yong Koo (Commun. Stat. Simul. Comput., 2020)

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 I-spline monotone regression estimation. - Junsouk Choi; Jungjun Lee; Jae-Hwan Jhong; Ja-Yong Koo (Commun. Stat. Simul. Comput., 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)

Locally penalized single-index model using B-splines and spherical coordinates. - Jae-Hwan Jhong; Jae-Young Kim; Jae-Deok Lee; Ja-Yong Koo (Commun. Stat. Simul. Comput., 2024)

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)