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Ja-Yong Koo
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2020 – today
- 2024
- [j30]Jae-Hwan Jhong
, Jae-Young Kim, Jae-Deok Lee, Ja-Yong Koo:
Locally penalized single-index model using B-splines and spherical coordinates. Commun. Stat. Simul. Comput. 53(1): 273-287 (2024) - 2023
- [j29]Kwan-Young Bak
, Ja-Yong Koo
:
Minimax Density Estimation Under Radial Symmetry. IEEE Access 11: 126447-126461 (2023) - 2022
- [j28]Jae-Kyung Shin, Kwan-Young Bak
, Ja-Yong Koo:
Sparse neural network regression with variable selection. Comput. Intell. 38(6): 2075-2094 (2022) - [j27]Jae-Kyung Shin, Kwan-Young Bak
, Ja-Yong Koo:
Penalized additive neural network regression. Intell. Data Anal. 26(6): 1597-1616 (2022) - 2021
- [j26]Kwan-Young Bak
, Jae-Hwan Jhong
, Jung-Jun Lee, Jae-Kyung Shin
, Ja-Yong Koo
:
Penalized logspline density estimation using total variation penalty. Comput. Stat. Data Anal. 153: 107060 (2021) - [j25]Junsouk Choi, Jungjun Lee, Jae-Hwan Jhong
, Ja-Yong Koo:
Penalized I-spline monotone regression estimation. Commun. Stat. Simul. Comput. 50(11): 3714-3732 (2021) - 2020
- [j24]Jung-Jun Lee, Jae-Hwan Jhong
, Young-Rae Cho, Sunghwan Kim, Ja-Yong Koo:
Penalized log-density estimation using Legendre polynomials. Commun. Stat. Simul. Comput. 49(11): 2844-2860 (2020)
2010 – 2019
- 2019
- [j23]Jae-Hwan Jhong
, Ja-Yong Koo
:
Simultaneous estimation of quantile regression functions using B-splines and total variation penalty. Comput. Stat. Data Anal. 133: 228-244 (2019) - 2018
- [j22]Jung-Jun Lee
, Sunghwan Kim
, Jae-Hwan Jhong
, Ja-Yong Koo
:
Variable Selection and Joint Estimation of Mean and Covariance Models with an Application to eQTL Data. Comput. Math. Methods Medicine 2018: 4626307:1-4626307:13 (2018) - 2017
- [j21]Sunghwan Kim, Jae-Hwan Jhong
, Jung-Jun Lee, Ja-Yong Koo:
Meta-analytic support vector machine for integrating multiple omics data. BioData Min. 10(1): 2:1-2:14 (2017) - [j20]Sunghwan Kim, Jae-Hwan Jhong, Jung-Jun Lee, Ja-Yong Koo:
Erratum to: Meta-analytic support vector machine for integrating multiple omics data. BioData Min. 10(1): 8:1-8:2 (2017) - [j19]Sunghwan Kim, Jae-Hwan Jhong
, Jung-Jun Lee
, Ja-Yong Koo
, ByungYong Lee
, Sungwon Han
:
Node-Structured Integrative Gaussian Graphical Model Guided by Pathway Information. Comput. Math. Methods Medicine 2017: 8520480:1-8520480:10 (2017) - [j18]Insuk Sohn, Sujong Kim, Jae Won Lee, Ja-Yong Koo, Junsu Ko:
Identifying novel NF-kB-regulated immune genes in the human genome using a Discrete Kernel Structured Support Vector Machine. Model. Assist. Stat. Appl. 12(3): 209-216 (2017) - 2014
- [j17]Byoung-Jeong Choi, Kwang-Rae Kim, Kyu-Dong Cho, Changyi Park
, Ja-Yong Koo:
Variable Selection for Naive Bayes Semisupervised Learning. Commun. Stat. Simul. Comput. 43(10): 2702-2713 (2014) - 2013
- [j16]Kwang-Rae Kim, Peter T. Kim, Ja-Yong Koo, Michael R. Pierrynowski:
Frenet-Serret and the Estimation of Curvature and Torsion. IEEE J. Sel. Top. Signal Process. 7(4): 646-654 (2013) - 2011
- [j15]Sangjun Lee, Changyi Park
, Ja-Yong Koo:
Feature selection in the Laplacian support vector machine. Comput. Stat. Data Anal. 55(1): 567-577 (2011) - 2010
- [j14]Sungwan Bang, Ja-Yong Koo, Myoungshic Jhun:
Support Vector Machine Using k-Spatial Medians Clustering and Recovery Process. Commun. Stat. Simul. Comput. 39(7): 1422-1434 (2010)
2000 – 2009
- 2009
- [j13]Peter T. Kim, Ja-Yong Koo, Zhi-Ming Luo:
Weyl eigenvalue asymptotics and sharp adaptation on vector bundles. J. Multivar. Anal. 100(9): 1962-1978 (2009) - 2008
- [j12]Changyi Park
, Ja-Yong Koo, Sujong Kim, Insuk Sohn, Jae Won Lee:
Classification of gene functions using support vector machine for time-course gene expression data. Comput. Stat. Data Anal. 52(5): 2578-2587 (2008) - [j11]Changyi Park
, Ja-Yong Koo, Peter T. Kim, Jae Won Lee:
Stepwise feature selection using generalized logistic loss. Comput. Stat. Data Anal. 52(7): 3709-3718 (2008) - [j10]Ja-Yong Koo, Yoonkyung Lee, Yuwon Kim, Changyi Park:
A Bahadur Representation of the Linear Support Vector Machine. J. Mach. Learn. Res. 9: 1343-1368 (2008) - [j9]Ja-Yong Koo, Peter T. Kim:
Asymptotic Minimax Bounds for Stochastic Deconvolution Over Groups. IEEE Trans. Inf. Theory 54(1): 289-298 (2008) - 2007
- [j8]Myoungshic Jhun, Hyeong Chul Jeong, Ja-Yong Koo:
On the Use of Adaptive Nearest Neighbors for Missing Value Imputation. Commun. Stat. Simul. Comput. 36(6): 1275-1286 (2007) - 2006
- [j7]Ja-Yong Koo, Insuk Sohn, Sujong Kim, Jae Won Lee:
Structured polychotomous machine diagnosis of multiple cancer types using gene expression. Bioinform. 22(8): 950-958 (2006) - [j6]Yuwon Kim, Ja-Yong Koo:
Erratum to "Inverse boosting for monotone regression functions" [Computational Statistics and Data Analysis 49 (2005) 757-770]. Comput. Stat. Data Anal. 50(2): 583 (2006) - 2005
- [j5]Yuwon Kim, Ja-Yong Koo:
Inverse boosting for monotone regression functions. Comput. Stat. Data Anal. 49(3): 757-770 (2005) - 2004
- [j4]Gregory S. Chirikjian, Peter T. Kim, Ja-Yong Koo, Christine H. Lee:
Rotational Matching Problems. Int. J. Comput. Intell. Appl. 4(4): 401-416 (2004) - 2002
- [j3]Jianqing Fan, Ja-Yong Koo:
Wavelet deconvolution. IEEE Trans. Inf. Theory 48(3): 734-747 (2002) - [j2]L. Cavalier, Ja-Yong Koo:
Poisson intensity estimation for tomographic data using a wavelet shrinkage approach. IEEE Trans. Inf. Theory 48(10): 2794-2802 (2002) - 2001
- [j1]Yong Choi, Ja-Yong Koo, Nam-Yong Lee:
Image Reconstruction using the Wavelet Transform for Positron Emission Tomography. IEEE Trans. Medical Imaging 20(11): 1188-1193 (2001)
Coauthor Index
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