Generation of efficient frontiers in multi-objective optimization problems by generalized data envelopment analysis. - Yeboon Yun; Hirotaka Nakayama; Tetsuzo Tanino; Masao Arakawa (Eur. J. Oper. Res., 2001)

A role of total margin in support vector machines. - Min Yoon; Yeboon Yun; Hirotaka Nakayama (IJCNN, 2003)

Goal Programming Approaches to Support Vector Machines. - Hirotaka Nakayama; Yeboon Yun; Takeshi Asada; Min Yoon (KES, 2003)

Fitness evaluation using generalized data envelopment analysis in MOGA. - Yeboon Yun; Masao Arakawa; Hirotaka Nakayama (IEEE Congress on Evolutionary Computation, 2004)

Using support vector machines in multi-objective optimization. - Yeboon Yun; Hirotaka Nakayama; Masao Arakawa (IJCNN, 2004)

Prediction of Business Failure by Total Margin Support Vector Machines. - Yeboon Yun; Min Yoon; Hirotaka Nakayama; Wataru Shiraki (KES, 2004)

Pattern classification by goal programming and support vector machines. - Takeshi Asada; Yeboon Yun; Hirotaka Nakayama; Tetsuzo Tanino (Comput. Manag. Sci., 2004)

Multiple criteria decision making with generalized DEA and an aspiration level method. - Yeboon Yun; Hirotaka Nakayama; Masao Arakawa (Eur. J. Oper. Res., 2004)

A generalized model for data envelopment analysis. - Yeboon Yun; Hirotaka Nakayama; Tetsuzo Tanino (Eur. J. Oper. Res., 2004)

Total Margin Algorithms in Support Vector Machines. - Min Yoon; Yeboon Yun; Hirotaka Nakayama (IEICE Trans. Inf. Syst., 2004)

Genetic Algorithm for Multi-objective Optimization Using GDEA. - Yeboon Yun; Min Yoon; Hirotaka Nakayama (ICNC (3), 2005)

MOP/GP models for machine learning. - Hirotaka Nakayama; Yeboon Yun; Takeshi Asada; Min Yoon (Eur. J. Oper. Res., 2005)

Support Vector Regression Based on Goal Programming and Multi-objective Programming. - Hirotaka Nakayama; Yeboon Yun (IJCNN, 2006)

Generating Support Vector Machines Using Multi-Objective Optimization and Goal Programming. - Hirotaka Nakayama; Yeboon Yun (Multi-Objective Machine Learning, 2006)

Combining Aspiration Level Methods in Multi-objective Programming and Sequential Approximate Optimization using Computational Intelligence. - Hirotaka Nakayama; Yeboon Yun (MCDM, 2007)

Sequential Approximation Method in Multi-objective Optimization Using Aspiration Level Approach. - Yeboon Yun; Hirotaka Nakayama; Min Yoon (EMO, 2007)

Practical Approach to Outlier Detection Using Support Vector Regression. - Junya Nishiguchi; Chosei Kaseda; Hirotaka Nakayama; Masao Arakawa; Yeboon Yun (ICONIP (1), 2008)

Multi-objective Model Predictive Optimization using Computational Intelligence. - Hirotaka Nakayama; Yeboon Yun (IFIP AI, 2008)

Multi-objective Model Predictive Control. - Hirotaka Nakayama; Yeboon Yun; Masakazu Shirakawa (MCDM, 2008)

Sequential Approximate Multiobjective Optimization Using Computational Intelligence. - Min Yoon; Yeboon Yun; Hirotaka Nakayama (Springer, 2009)

Modified Support Vector Regression in outlier detection. - Junya Nishiguchi; Chosei Kaseda; Hirotaka Nakayama; Masao Arakawa; Yeboon Yun (IJCNN, 2010)

Evolutionary multi-objective optimization using expected improvement and generalized DEA. - Yeboon Yun; Hirotaka Nakayama; Min Yoon (SMC, 2011)

Evaluation of sewerage systems using data envelopment analysis. - Yeboon Yun; Kohei Furukawa; Takeshi Iida; Hirotaka Nakayama (SCIS&ISIS, 2012)

Parameter tuning of large scale support vector machines using ensemble learning with applications to imbalanced data sets. - Hirotaka Nakayama; Yeboon Yun; Yuki Uno (SMC, 2012)

Utilizing expected improvement and generalized data envelopment analysis in multi-objective genetic algorithms. - Yeboon Yun; Hirotaka Nakayama (J. Glob. Optim., 2013)

Generation of Pareto optimal solutions using generalized DEA and PSO. - Yeboon Yun; Hirotaka Nakayama; Min Yoon (J. Glob. Optim., 2016)

Multi-Objective Model Predictive Control. - Yeboon Yun; Hirotaka Nakayama; Min Yoon (SCIS&ISIS, 2018)

Application of Machine Learning to the Prediction of WBGT. - Chang Lu; Yeboon Yun; Min Yoon (SICE, 2021)

Multiclass Support Vector Machines for Determination of Reinforcement Degree in Constructing Large-scale Structures Based on Data Characteristics. - Keiji Tatsumi; Ryota Masui; Shunsuke Tsujioka; Yoshifumi Kusunoki; Yeboon Yun (SMC, 2021)

Determination of reinforcement degrees in constructing large-scale structures by using multiclass support vector machines. - Keiji Tatsumi; Shunsuke Tsujioka; Ryota Masui; Yoshifumi Kusunoki; Yeboon Yun (Knowl. Based Syst., 2022)

Multiclass piecewise-linear SVMs based on division of data space for determining the reinforcement degrees of large-scale structures. - Keiji Tatsumi; Satoshi Maruyama; Yeboon Yun (IJCNN, 2024)

Graph Convolutional Networks Approach for Alzheimer's Disease Stage Classification Using Multimodal Data. - Hyujeong Jeong; Do-Young Kang; Yeboon Yun; Jum-Ran Kang; Min Yoon; Gyu-Bin Lee (SCIS/ISIS, 2024)

Multiclass piecewise-linear SVMs with the restricted feasible region for the reinforcement degrees in constructing large-scale structures. - Keiji Tatsumi; Ryota Masui; Haruhisa Miyahara; Yeboon Yun (Knowl. Based Syst., 2024)