Functional-Specialization Multi-Objective Real-Coded Genetic Algorithm: FS-MOGA. - Naoki Hamada; Jun Sakuma; Shigenobu Kobayashi; Isao Ono (PPSN, 2008)

Adaptive weighted aggregation: A multiobjective function optimization framework taking account of spread and evenness of approximate solutions. - Naoki Hamada; Yuichi Nagata; Shigenobu Kobayashi; Isao Ono (IEEE Congress on Evolutionary Computation, 2010)

On scalability of Adaptive Weighted Aggregation for multiobjective function optimization. - Naoki Hamada; Yuichi Nagata; Shigenobu Kobayashi; Isao Ono (IEEE Congress on Evolutionary Computation, 2011)

Adaptive Weighted Aggregation 2: More scalable AWA for multiobjective function optimization. - Naoki Hamada; Yuichi Nagata; Shigenobu Kobayashi; Isao Ono (IEEE Congress on Evolutionary Computation, 2011)

A new Pareto frontier covering strategy in FS-MOGA for multi-objective function optimization. - Ryo Miyazaki; Naoki Hamada; Yuichi Nagata; Isao Ono (SCIS&ISIS, 2012)

Population Synthesis via k-Nearest Neighbor Crossover Kernel. - Naoki Hamada; Katsumi Homma; Hiroyuki Higuchi; Hideyuki Kikuchi (ICDM, 2015)

Knee point analysis of many-objective Pareto fronts based on Reeb graph. - Naoki Hamada; Kazuhisa Chiba (CEC, 2017)

Simple problems: the simplicial gluing structure of pareto sets and pareto fronts. - Naoki Hamada (GECCO (Companion), 2017)

Data-driven analysis of pareto set topology. - Naoki Hamada; Keisuke Goto 001 (GECCO, 2018)

Bézier Simplex Fitting: Describing Pareto Fronts of Simplicial Problems with Small Samples in Multi-Objective Optimization. - Ken Kobayashi; Naoki Hamada; Akiyoshi Sannai; Akinori Tanaka; Kenichi Bannai; Masashi Sugiyama (AAAI, 2019)

Neural-network assistance to calculate precise eigenvalue for fitness evaluation of real product design. - Yukito Tsunoda; Takahiro Notsu; Yasufumi Sakai; Naoki Hamada; Toshihiko Mori; Teruo Ishihara; Atsuki Inoue (GECCO (Companion), 2019)

Asymptotic Risk of Bézier Simplex Fitting. - Akinori Tanaka; Akiyoshi Sannai; Ken Kobayashi; Naoki Hamada (AAAI, 2020)

Topology of Pareto Sets of Strongly Convex Problems. - Naoki Hamada; Kenta Hayano; Shunsuke Ichiki; Yutaro Kabata; Hiroshi Teramoto (SIAM J. Optim., 2020)

Approximate Bayesian Computation of Bézier Simplices. - Akinori Tanaka; Akiyoshi Sannai; Ken Kobayashi; Naoki Hamada (CoRR, 2021)

All unconstrained strongly convex problems are weakly simplicial. - Yusuke Mizota; Naoki Hamada; Shunsuke Ichiki (CoRR, 2021)

Explicitly Multi-Modal Benchmarks for Multi-Objective Optimization. - Reiya Hagiwara; Takahiro Yamamoto; Naoki Hamada; Daisuke Sakurai (CoRR, 2021)

A two-phase framework with a bézier simplex-based interpolation method for computationally expensive multi-objective optimization. - Ryoji Tanabe; Youhei Akimoto; Ken Kobayashi; Hiroshi Umeki; Shinichi Shirakawa; Naoki Hamada (GECCO, 2022)

Free Disposal Hull Condition to Verify When Efficiency Coincides with Weak Efficiency. - Naoki Hamada; Shunsuke Ichiki (J. Optim. Theory Appl., 2022)

GenéLive! Generating Rhythm Actions in Love Live! - Atsushi Takada; Daichi Yamazaki; Yudai Yoshida; Nyamkhuu Ganbat; Takayuki Shimotomai; Naoki Hamada; Likun Liu; Taiga Yamamoto; Daisuke Sakurai (AAAI, 2023)

Visualization of Multiobjective Multimodal Benchmarking Based on Basin Connectivity. - Likun Liu; Ryosuke Ota; Takahiro Yamamoto; Naoki Hamada; Daisuke Sakurai (GECCO Companion, 2024)

Stochastic Gradient Descent for Bézier Simplex Representation of Pareto Set in Multi-Objective Optimization. - Yasunari Hikima; Ken Kobayashi; Akinori Tanaka; Akiyoshi Sannai; Naoki Hamada (AISTATS, 2025)

Bézier Flow: a Surface-wise Gradient Descent Method for Multi-objective Optimization. - Akiyoshi Sannai; Yasunari Hikima; Ken Kobayashi; Akinori Tanaka; Naoki Hamada (Trans. Mach. Learn. Res., 2025)