Publications

Peer-Reviewed Conference Papers

Koki Ikeda, Masahiro Nomura and Ryoki Hamano, “Diversified Residual Symbolic Regression,” In ACM Genetic and Evolutionary Computation Conference (GECCO ‘26), 2026. [DOI]
Toshio Ito, Shizuko Matsuzoe, Tadashi Iwahashi, Hisatoshi Yamaoka and Miwa Ueki, Kota Nagakane, Hideaki Morozumi, Koki Ikeda and Isao Ono, “A Method for Revealing Implicit Emphasized Criteria for Decision Makers on Social Issues,” In IEEE Congress on Evolutionary Computation (CEC'24), 2024. [DOI]
Koki Ikeda and Isao Ono, “Natural Evolution Strategy for Mixed-Integer Black-Box Optimization,” In ACM Genetic and Evolutionary Computation Conference (GECCO ‘23), 2023. [DOI] [arXiv] [Code]

Selected Publications

Diversified Residual Symbolic Regression

This paper proposes diversified residual symbolic regression (DRSR), which uses the quality-diversity paradigm to collect accurate symbolic expressions with diverse residual patterns. It enables users to select expressions based on domain knowledge and reveals multiple underlying relationships in synthetic and real-world datasets.

Natural Evolution Strategy for Mixed-Integer Black-Box Optimization

This paper proposes DX-NES-ICI, a natural evolution strategy that accounts for implicit constraints and integer variables in mixed-integer black-box optimization. It demonstrates improved performance over CMA-ES w. Margin on benchmark problems, particularly when continuous variables contribute more to the objective function value than integer variables.