A T-sum bound of LR-fuzzy numbers. - Dug Hun Hong; Changha Hwang (Fuzzy Sets Syst., 1997)

Extended Fuzzy Regression Models. - Dug Hun Hong; Changha Hwang (JCIS, 2002)

Incremental Feature Extraction Based on Empirical Kernel Map. - Byung-Joo Kim; Jooyong Shim; Changha Hwang; Il Kon Kim; Joon Hyun Song (ISMIS, 2003)

Support vector fuzzy regression machines. - Dug Hun Hong; Changha Hwang (Fuzzy Sets Syst., 2003)

Usefulness of artificial neural networks for early warning system of economic crisis. - Tae Yoon Kim; Kyong Joo Oh; Insuk Sohn; Changha Hwang (Expert Syst. Appl., 2004)

Ridge estimation for regression models with crisp inputs and Gaussian fuzzy output. - Dug Hun Hong; Changha Hwang; Chulhwan Ahn (Fuzzy Sets Syst., 2004)

Ridge Regression Procedures For Fuzzy Models Using Triangular Fuzzy Numbers. - Dug Hun Hong; Changha Hwang (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2004)

Extended fuzzy regression models using regularization method. - Dug Hun Hong; Changha Hwang (Inf. Sci., 2004)

Interval Regression Analysis Using Support Vector Machine and Quantile Regression. - Changha Hwang; Dug Hun Hong; Eunyoung Na; Hyejung Park; Jooyong Shim (FSKD (1), 2005)

Exon Structure Analysis via PCA and ICA of Short-Time Fourier Transform. - Changha Hwang; David K. Y. Chiu; Insuk Sohn (ICNC (2), 2005)

A Simple Quantile Regression via Support Vector Machine. - Changha Hwang; Jooyong Shim (ICNC (1), 2005)

A Prediction Interval Estimation Method for KMSE. - Changha Hwang; Kyung Ha Seok; Daehyeon Cho (ICNC (1), 2005)

Doubly Regularized Kernel Regression with Heteroscedastic Censored Data. - Jooyong Shim; Changha Hwang (ICNC (1), 2005)

Analyzing the Nonlinear Time Series of Turbulent Flows with Kernel Interval Regression Machine. - Changha Hwang; Dug Hun Hong (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2005)

Interval regression analysis using quadratic loss support vector machine. - Dug Hun Hong; Changha Hwang (IEEE Trans. Fuzzy Syst., 2005)

Locally Weighted LS-SVM for Fuzzy Nonlinear Regression with Fuzzy Input-Output. - Dug Hun Hong; Changha Hwang; Jooyong Shim; Kyung Ha Seok (CIS, 2006)

Fuzzy Nonlinear Regression Model Based on LS-SVM in Feature Space. - Dug Hun Hong; Changha Hwang (FSKD, 2006)

Robust LS-SVM Regression Using Fuzzy C-Means Clustering. - Jooyong Shim; Changha Hwang; Sungkyun Nau (ICNC (1), 2006)

Support vector interval regression machine for crisp input and output data. - Changha Hwang; Dug Hun Hong; Kyung Ha Seok (Fuzzy Sets Syst., 2006)

T-sum of sigmoid-shaped fuzzy intervals. - Dug Hun Hong; Changha Hwang; Kyung Tae Kim (Inf. Sci., 2007)

New normalization methods using support vector machine quantile regression approach in microarray analysis. - Insuk Sohn; Sujong Kim; Changha Hwang; Jae Won Lee (Comput. Stat. Data Anal., 2008)

Support vector censored quantile regression under random censoring. - Jooyong Shim; Changha Hwang (Comput. Stat. Data Anal., 2009)

Selecting marker genes for cancer classification using supervised weighted kernel clustering and the support vector machine. - Jooyong Shim; Insuk Sohn; Sujong Kim; Jae Won Lee; Paul E. Green 002; Changha Hwang (Comput. Stat. Data Anal., 2009)

Informative transcription factor selection using support vector machine-based generalized approximate cross validation criteria. - Insuk Sohn; Jooyong Shim; Changha Hwang; Sujong Kim; Jae Won Lee (Comput. Stat. Data Anal., 2009)

Non-crossing quantile regression via doubly penalized kernel machine. - Jooyong Shim; Changha Hwang; Kyung Ha Seok (Comput. Stat., 2009)

Semiparametric mixed-effect least squares support vector machine for analyzing pharmacokinetic and pharmacodynamic data. - Kyung Ha Seok; Jooyong Shim; Daehyeon Cho; Gyu-Jeong Noh; Changha Hwang (Neurocomputing, 2011)

Estimating value at risk with semiparametric support vector quantile regression. - Jooyong Shim; Yongtae Kim; Jangtaek Lee; Changha Hwang (Comput. Stat., 2012)

Composite support vector quantile regression estimation. - Jooyong Shim; Changha Hwang; Kyung Ha Seok (Comput. Stat., 2014)

Semiparametric spatial effects kernel minimum squared error model for predicting housing sales prices. - Jooyong Shim; Okmyung Bin; Changha Hwang (Neurocomputing, 2014)

Estimating small area mean with mixed and fixed effects support vector median regressions. - Jooyong Shim; Changha Hwang (Neurocomputing, 2014)

Varying coefficient modeling via least squares support vector regression. - Jooyong Shim; Changha Hwang (Neurocomputing, 2015)

Support vector quantile regression with varying coefficients. - Jooyong Shim; Changha Hwang; Kyung Ha Seok (Comput. Stat., 2016)

Kernel-based random effect time-varying coefficient model for longitudinal data. - Jooyong Shim; Insuk Sohn; Changha Hwang (Neurocomputing, 2017)

Kernel-based orthogonal quantile regression model. - Jooyong Shim; Changha Hwang (Model. Assist. Stat. Appl., 2017)

AndroClass: An Effective Method to Classify Android Applications by Applying Deep Neural Networks to Comprehensive Features. - Masoud Reyhani Hamedani; Dongjin Shin; Myeonggeon Lee; Seong-je Cho; Changha Hwang (Wirel. Commun. Mob. Comput., 2018)

Subject-specific Deep Neural Networks for Count Data with High-cardinality Categorical Features. - Hangbin Lee; Il Do Ha; Changha Hwang; Youngjo Lee (CoRR, 2023)