Ja-Yong Koo

33 papers Journal 33
YearRankTypeTitle / Venue / Authors
2025 J jnl
Low-Dimensional Adaptive Neural Network Regression With Directional Change Detection via Nuclear Norm Penalization.
Stat. Anal. Data Min.
Yongku Kim, Jae-Hwan Jhong, Ja-Yong Koo, Kwan-Young Bak
2025 J jnl
spheresmooth: An R Package for Penalized Piecewise Geodesic Curve Fitting on a Sphere.
R J.
Jae-Hwan Jhong, Seyoung Lee, Ja-Yong Koo, Kwan-Young Bak
2024 J jnl
An Adaptive Neural Network Regression Method for Structure Identification.
J. Comput. Graph. Stat.
Jae-Kyung Shin, Kwan-Young Bak, Ja-Yong Koo
2024 J jnl
Locally penalized single-index model using B-splines and spherical coordinates.
Commun. Stat. Simul. Comput.
Jae-Hwan Jhong, Jae-Young Kim, Jae-Deok Lee, Ja-Yong Koo
2023 J jnl
Minimax Density Estimation Under Radial Symmetry.
IEEE Access
Kwan-Young Bak, Ja-Yong Koo
2022 J jnl
Penalized additive neural network regression.
Intell. Data Anal.
Jae-Kyung Shin, Kwan-Young Bak, Ja-Yong Koo
2022 J jnl
Sparse neural network regression with variable selection.
Comput. Intell.
Jae-Kyung Shin, Kwan-Young Bak, Ja-Yong Koo
2021 J jnl
Penalized I-spline monotone regression estimation.
Commun. Stat. Simul. Comput.
Junsouk Choi, Jungjun Lee, Jae-Hwan Jhong, Ja-Yong Koo
2021 J jnl
Penalized logspline density estimation using total variation penalty.
Comput. Stat. Data Anal.
Kwan-Young Bak, Jae-Hwan Jhong, Jung-Jun Lee, Jae-Kyung Shin, Ja-Yong Koo
2020 J jnl
Penalized log-density estimation using Legendre polynomials.
Commun. Stat. Simul. Comput.
Jung-Jun Lee, Jae-Hwan Jhong, Young-Rae Cho, Sunghwan Kim, Ja-Yong Koo
2019 J jnl
Simultaneous estimation of quantile regression functions using B-splines and total variation penalty.
Comput. Stat. Data Anal.
Jae-Hwan Jhong, Ja-Yong Koo
2018 J jnl
Variable Selection and Joint Estimation of Mean and Covariance Models with an Application to eQTL Data.
Comput. Math. Methods Medicine
Jung-Jun Lee, Sunghwan Kim, Jae-Hwan Jhong, Ja-Yong Koo
2017 J jnl
Erratum to: Meta-analytic support vector machine for integrating multiple omics data.
BioData Min.
Sunghwan Kim, Jae-Hwan Jhong, Jung-Jun Lee, Ja-Yong Koo
2017 J jnl
Identifying novel NF-kB-regulated immune genes in the human genome using a Discrete Kernel Structured Support Vector Machine.
Model. Assist. Stat. Appl.
Insuk Sohn, Sujong Kim, Jae Won Lee, Ja-Yong Koo, Junsu Ko
2017 J jnl
Meta-analytic support vector machine for integrating multiple omics data.
BioData Min.
Sunghwan Kim, Jae-Hwan Jhong, Jung-Jun Lee, Ja-Yong Koo
2017 J jnl
Node-Structured Integrative Gaussian Graphical Model Guided by Pathway Information.
Comput. Math. Methods Medicine
Sunghwan Kim, Jae-Hwan Jhong, Jung-Jun Lee, Ja-Yong Koo, ByungYong Lee, Sungwon Han
2014 J jnl
Variable Selection for Naive Bayes Semisupervised Learning.
Commun. Stat. Simul. Comput.
Byoung-Jeong Choi, Kwang-Rae Kim, Kyu-Dong Cho, Changyi Park, Ja-Yong Koo
2013 J jnl
Frenet-Serret and the Estimation of Curvature and Torsion.
IEEE J. Sel. Top. Signal Process.
Kwang-Rae Kim, Peter T. Kim, Ja-Yong Koo, Michael R. Pierrynowski
2011 J jnl
Feature selection in the Laplacian support vector machine.
Comput. Stat. Data Anal.
Sangjun Lee, Changyi Park, Ja-Yong Koo
2010 J jnl
Support Vector Machine Using
Commun. Stat. Simul. Comput.
Sungwan Bang, Ja-Yong Koo, Myoungshic Jhun
2009 J jnl
Weyl eigenvalue asymptotics and sharp adaptation on vector bundles.
J. Multivar. Anal.
Peter T. Kim, Ja-Yong Koo, Zhi-Ming Luo
2008 J jnl
A Bahadur Representation of the Linear Support Vector Machine.
J. Mach. Learn. Res.
Ja-Yong Koo, Yoonkyung Lee, Yuwon Kim, Changyi Park
2008 J jnl
Asymptotic Minimax Bounds for Stochastic Deconvolution Over Groups.
IEEE Trans. Inf. Theory
Ja-Yong Koo, Peter T. Kim
2008 J jnl
Classification of gene functions using support vector machine for time-course gene expression data.
Comput. Stat. Data Anal.
Changyi Park, Ja-Yong Koo, Sujong Kim, Insuk Sohn, Jae Won Lee
2008 J jnl
Stepwise feature selection using generalized logistic loss.
Comput. Stat. Data Anal.
Changyi Park, Ja-Yong Koo, Peter T. Kim, Jae Won Lee
2007 J jnl
On the Use of Adaptive Nearest Neighbors for Missing Value Imputation.
Commun. Stat. Simul. Comput.
Myoungshic Jhun, Hyeong Chul Jeong, Ja-Yong Koo
2006 J jnl
Erratum to "Inverse boosting for monotone regression functions" [Computational Statistics and Data Analysis 49 (2005) 757-770].
Comput. Stat. Data Anal.
Yuwon Kim, Ja-Yong Koo
2006 J jnl
Structured polychotomous machine diagnosis of multiple cancer types using gene expression.
Bioinform.
Ja-Yong Koo, Insuk Sohn, Sujong Kim, Jae Won Lee
2005 J jnl
Inverse boosting for monotone regression functions.
Comput. Stat. Data Anal.
Yuwon Kim, Ja-Yong Koo
2004 J jnl
Rotational Matching Problems.
Int. J. Comput. Intell. Appl.
Gregory S. Chirikjian, Peter T. Kim, Ja-Yong Koo, Christine H. Lee
2002 J jnl
Poisson intensity estimation for tomographic data using a wavelet shrinkage approach.
IEEE Trans. Inf. Theory
L. Cavalier, Ja-Yong Koo
2002 J jnl
Wavelet deconvolution.
IEEE Trans. Inf. Theory
Jianqing Fan, Ja-Yong Koo
2001 J jnl
Image Reconstruction using the Wavelet Transform for Positron Emission Tomography.
IEEE Trans. Medical Imaging
Yong Choi, Ja-Yong Koo, Nam-Yong Lee