AKIMOTO Yohei
- Conference, etc.
- Benchmarking the Novel CMA-ES Restart Strategy Using the Search History on the BBOB Noiseless Testbed
Yamaguchi Takahiro; Akimoto Yohei
GECCO 2017 Workshop on Real-Parameter Black-Box Optimization Benchmarking (BBOB 2017)/2017-07-15--2017-07-19 - Introducing the Cumulation to the Population Based Incremental Learning and the Compact GA to Relax Genetic Drift
Tanaka Keigo; Akimoto Yohei
Genetic and Evolutionary Computation Conference (GECCO 2017)/2017-07-15--2017-07-19 - Modified Box Constraint Handling for the Covariance Matrix Adaptation Evolution Strategy
Hidekazu Miyazawa; Akimoto Yohei
Genetic and Evolutionary Computation Conference (GECCO 2017)/2017-07-15--2017-07-19 - Effect of the Mean Vector Learning Rate in CMA-ES
Hidekazu Miyazawa; Akimoto Yohei
Genetic and Evolutionary Computation Conference (GECCO 2017)/2017-07-15--2017-07-19 - Optimal Step-Size for the Weighted Recombination Evolution Strategy
Akimoto Yohei; Anne Auger; Nikolaus Hansen
Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 17191)/2017-05-07--2017-05-12 - Population Size Adaptation for the CMA-ES Based on the Accuracy of the Parameter Update
Nishida Kouhei; Akimoto Yohei
APSCIT 2017 Annual Meeting/2017-07-27--2017-07-30 - Improvement to the Box Constraint Handling Method for the CMA-ES and its Generalization to Linear Constraints
Sakamoto Naoki; Akimoto Yohei
APSCIT 2017 Annual Meeting/2017-07-27--2017-07-30 - Covariance Matrix Adaptation Evolution Strategy for High Dimensional Search Space
Akimoto Yohei
APSCIT 2017 Annual Meeting/2017-07-27--2017-07-30 - Dynamic Optimization of Neural Network Structures Using Probabilistic Modeling
Shirakawa Shinichi; Iwata Yasushi; Akimoto Yohei
AAAI Conference on Artificial Intelligence/2018-02-02--2018-02-07
- Benchmarking the Novel CMA-ES Restart Strategy Using the Search History on the BBOB Noiseless Testbed