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Hong Seo Ryoo
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2020 – today
- 2022
- [j16]Kedong Yan, Hong Seo Ryoo:
Graph, clique and facet of boolean logical polytope. J. Glob. Optim. 82(4): 1015-1052 (2022) - 2021
- [j15]Cui Guo, Hong Seo Ryoo:
On Pareto-Optimal Boolean Logical Patterns for Numerical Data. Appl. Math. Comput. 403: 126153 (2021) - [j14]Zhengyu Ma, Hong Seo Ryoo
:
Spherical Classification of Data, a New Rule-Based Learning Method. J. Classif. 38(1): 44-71 (2021) - [c7]Taekgeun Jung, Hong Seo Ryoo:
Analysis of Brain fMRI Data via Topological Data Clustering Method IoPS. BIBM 2021: 1655-1657 - [c6]Dongwoo Kang, Sunyoung Kim, Yoonsik Jung, Hong Seo Ryoo:
Generating Interpretable Patterns for Biomedical Image Classification. BIBM 2021: 1658-1660 - [c5]Sunung Kim, Sangkyun Noh, Hong Seo Ryoo:
Identifying Combinatorial Significance for Classification of Alzheimer's Disease Proteomics Expression with Logical Analysis of Data. BIBM 2021: 1661-1663
2010 – 2019
- 2019
- [j13]Kedong Yan, Hong Seo Ryoo:
A multi-term, polyhedral relaxation of a 0-1 multilinear function for Boolean logical pattern generation. J. Glob. Optim. 74(4): 705-735 (2019) - [c4]Kedong Yan, Hong Seo Ryoo:
Cliques for Multi-Term Linearization of 0-1 Multilinear Program for Boolean Logical Pattern Generation. WCGO 2019: 376-386 - 2017
- [j12]Kedong Yan, Hong Seo Ryoo:
0-1 multilinear programming as a unifying theory for LAD pattern generation. Discret. Appl. Math. 218: 21-39 (2017) - [j11]Kedong Yan, Hong Seo Ryoo:
Strong valid inequalities for Boolean logical pattern generation. J. Glob. Optim. 69(1): 183-230 (2017) - 2012
- [j10]Cui Guo, Hong Seo Ryoo:
Compact MILP models for optimal and Pareto-optimal LAD patterns. Discret. Appl. Math. 160(16-17): 2339-2348 (2012)
2000 – 2009
- 2009
- [j9]Hong Seo Ryoo, In-Yong Jang:
MILP approach to pattern generation in logical analysis of data. Discret. Appl. Math. 157(4): 749-761 (2009) - 2008
- [j8]Hong Seo Ryoo, Matthias Ehrgott
Biomedical informatics and OR. OR Spectr. 30(2): 219-221 (2008) - [j7]Kwangsoo Kim, Hong Seo Ryoo:
A LAD-based method for selecting short oligo probes for genotyping applications. OR Spectr. 30(2): 249-268 (2008) - 2007
- [j6]Kwangsoo Kim, Hong Seo Ryoo:
Data separation via a finite number of discriminant functions: A global optimization approach. Appl. Math. Comput. 190(1): 476-489 (2007) - [j5]Kwangsoo Kim, Hong Seo Ryoo:
Nonlinear separation of data via Mixed 0-1 Integer and Linear Programming. Appl. Math. Comput. 193(1): 183-196 (2007) - [j4]Hong Seo Ryoo:
A compact mean-variance-skewness model for large-scale portfolio optimization and its application to the NYSE market. J. Oper. Res. Soc. 58(4): 505-515 (2007) - [c3]Hong Seo Ryoo, In-Yong Jang:
A Heuristic Method for Selecting Support Features from Large Datasets. AAIM 2007: 411-423 - [c2]Kwangsoo Kim, Hong Seo Ryoo:
Selecting Genotyping Oligo Probes Via Logical Analysis of Data. Canadian AI 2007: 86-97 - [c1]Hong Seo Ryoo, Kwangsoo Kim:
Separation of Data Via Concurrently Determined Discriminant Functions. TAMC 2007: 533-541 - 2006
- [j3]Hong Seo Ryoo:
Pattern classification by concurrently determined piecewise linear and convex discriminant functions. Comput. Ind. Eng. 51(1): 79-89 (2006) - [j2]Hong Seo Ryoo, Premnath Ayyalasomayajula:
A simulation-based heuristic solution procedure for analyzing human postural balance. OR Spectr. 28(3): 399-415 (2006) - 2005
- [j1]Hong Seo Ryoo:
Robust Metaheuristic Algorithm for Redundancy Optimization in Large-Scale Complex Systems. Ann. Oper. Res. 133(1-4): 209-228 (2005)
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