Jooyong Shim

发表

Transcription factor-binding site identification and gene classification via fusion of the supervised-weighted discrete kernel clustering and support vector machine

Insuk Sohn, Jooyong Shim, Changha Hwang, 2014 .

Varying coefficient modeling via least squares support vector regression

Jooyong Shim, Changha Hwang, Changha Hwang, 2015, Neurocomputing.

Semiparametric mixed-effect least squares support vector machine for analyzing pharmacokinetic and pharmacodynamic data

Jooyong Shim, Changha Hwang, Kyung Ha Seok, 2011, Neurocomputing.

Estimating value at risk with semiparametric support vector quantile regression

Jooyong Shim, Changha Hwang, Yong-Tae Kim, 2012, Comput. Stat..

Doubly Regularized Kernel Regression with Heteroscedastic Censored Data

Jooyong Shim, Changha Hwang, 2005, ICNC.

A Simple Quantile Regression via Support Vector Machine

Jooyong Shim, Changha Hwang, Changha Hwang, 2005, ICNC.

Kernel-based spatial error model for analyzing spatial panel data

Jooyong Shim, Sang Bum Lee, Dai-Won Kim, 2020 .

Composite support vector quantile regression estimation

Jooyong Shim, Changha Hwang, Kyung-Ha Seok, 2014, Comput. Stat..

Semiparametric spatial effects kernel minimum squared error model for predicting housing sales prices

Jooyong Shim, Changha Hwang, Okmyung Bin, 2014, Neurocomputing.

Estimating small area mean with mixed and fixed effects support vector median regressions

Jooyong Shim, Changha Hwang, Changha Hwang, 2014, Neurocomputing.

Support vector quantile regression with varying coefficients

Jooyong Shim, Changha Hwang, Kyung-Ha Seok, 2016, Comput. Stat..

Kernel-based orthogonal quantile regression model

Jooyong Shim, Changha Hwang, Changha Hwang, 2017, Model. Assist. Stat. Appl..

Selecting marker genes for cancer classification using supervised weighted kernel clustering and the support vector machine

Insuk Sohn, Jooyong Shim, Changha Hwang, 2009, Comput. Stat. Data Anal..

Locally Weighted LS-SVM for Fuzzy Nonlinear Regression with Fuzzy Input-Output

Dug Hun Hong, Jooyong Shim, Changha Hwang, 2006, 2006 International Conference on Computational Intelligence and Security.

Interval Regression Analysis Using Support Vector Machine and Quantile Regression

Dug Hun Hong, Jooyong Shim, Changha Hwang, 2005, FSKD.

Kernel-based random effect time-varying coefficient model for longitudinal data

Insuk Sohn, Jooyong Shim, Changha Hwang, 2017, Neurocomputing.

Support vector censored quantile regression under random censoring

Jooyong Shim, Changha Hwang, Changha Hwang, 2009, Comput. Stat. Data Anal..

Informative transcription factor selection using support vector machine-based generalized approximate cross validation criteria

Insuk Sohn, Jooyong Shim, Changha Hwang, 2009, Comput. Stat. Data Anal..

Incremental Feature Extraction Based on Empirical Kernel Map

Byung-Joo Kim, Jooyong Shim, Changha Hwang, 2003, ISMIS.

Robust LS-SVM Regression Using Fuzzy C-Means Clustering

Jooyong Shim, Changha Hwang, Sungkyun Nau, 2006, ICNC.

Feature selection in the semivarying coefficient LS-SVR

Jooyong Shim, Changha Hwang, Changha Hwang, 2017 .

Generalized kernel estimating equation for panel estimation of small area unemployment rates

Jooyong Shim, Changha Hwang, Changha Hwang, 2013 .

Detection of chromosome structural variation by targeted next-generation sequencing and a deep learning application

Insuk Sohn, Jooyong Shim, Changha Hwang, 2019, Scientific Reports.

Semivarying coefficient least-squares support vector regression for analyzing high-dimensional gene-environmental data

Insuk Sohn, Jooyong Shim, Changha Hwang, 2018 .