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ORCIDQuang Nhat Huynh
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2020 – today
- 2022
[c6]Quang Nhat Huynh, Hemant Kumar Singh
, Tapabrata Ray:
Discovery of implicit relationships from data using linear programming and mixed integer linear programming. GECCO Companion 2022: 558-561- [c5]Quang Nhat Huynh, Hemant K. Singh, Tapabrata Ray, Akira Oyama:
Improved Genetic Programming for Symbolic Regression: Case Studies on Practical Applications. SSCI 2022: 1135-1142
2010 – 2019
- 2019
- [c4]Quang Nhat Huynh, Hemant Kumar Singh, Tapabrata Ray:
Investigating the use of linear programming to solve implicit symbolic regression problems. GECCO (Companion) 2019: 344-345 - 2018
- [j2]Shelvin Chand, Quang Nhat Huynh, Hemant K. Singh, Tapabrata Ray, Markus Wagner:
On the use of genetic programming to evolve priority rules for resource constrained project scheduling problems. Inf. Sci. 432: 146-163 (2018) - [j1]Quang Nhat Huynh, Shelvin Chand, Hemant Kumar Singh, Tapabrata Ray:
Genetic Programming With Mixed-Integer Linear Programming-Based Library Search. IEEE Trans. Evol. Comput. 22(5): 733-747 (2018) - 2016
- [c3]Quang Nhat Huynh, Hemant Kumar Singh, Tapabrata Ray:
Optimum redesign of scale-free networks with robustness and cost considerations. CEC 2016: 529-536 - [c2]Quang Nhat Huynh, Hemant Kumar Singh, Tapabrata Ray:
A Semantics based Symbolic Regression Framework for Mining Explicit and Implicit Equations from Data. GECCO (Companion) 2016: 103-104 - [c1]Quang Nhat Huynh, Hemant Kumar Singh, Tapabrata Ray:
Improving Symbolic Regression through a semantics-driven framework. SSCI 2016: 1-8
Coauthor Index
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