Naoki Hamada
Orcid: 0000-0002-3630-5987Affiliations:
- KLab Inc., Tokyo, Japan
- RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Fujitsu Laboratories, Kawasaki, Japan
- Tokyo Institute of Technology, Interdisciplinary Graduate School of Science and Engineering, Japan (PhD)
According to our database1,
Naoki Hamada
authored at least 20 papers
between 2008 and 2023.
Collaborative distances:
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Bibliography
2023
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Free Disposal Hull Condition to Verify When Efficiency Coincides with Weak Efficiency.
J. Optim. Theory Appl., 2022
Bézier Flow: a Surface-wise Gradient Descent Method for Multi-objective Optimization.
CoRR, 2022
A two-phase framework with a bézier simplex-based interpolation method for computationally expensive multi-objective optimization.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022
2021
2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
Neural-network assistance to calculate precise eigenvalue for fitness evaluation of real product design.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019
Bézier Simplex Fitting: Describing Pareto Fronts of Simplicial Problems with Small Samples in Multi-Objective Optimization.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
2018
Proceedings of the Genetic and Evolutionary Computation Conference, 2018
2017
Proceedings of the Genetic and Evolutionary Computation Conference, 2017
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017
2015
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015
2012
A new Pareto frontier covering strategy in FS-MOGA for multi-objective function optimization.
Proceedings of the 6th International Conference on Soft Computing and Intelligent Systems (SCIS), 2012
2011
Adaptive Weighted Aggregation 2: More scalable AWA for multiobjective function optimization.
Proceedings of the IEEE Congress on Evolutionary Computation, 2011
On scalability of Adaptive Weighted Aggregation for multiobjective function optimization.
Proceedings of the IEEE Congress on Evolutionary Computation, 2011
2010
Adaptive weighted aggregation: A multiobjective function optimization framework taking account of spread and evenness of approximate solutions.
Proceedings of the IEEE Congress on Evolutionary Computation, 2010
2008
Proceedings of the Parallel Problem Solving from Nature, 2008