Results 11 to 20 of about 17,544 (260)
Covariance matrix adaptation for the rapid illumination of behavior space [PDF]
Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 2020 Accepted to GECCO ...
Matthew C. Fontaine +3 more
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Contextual Covariance Matrix Adaptation Evolutionary Strategies [PDF]
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017 Many stochastic search algorithms are designed to optimize a fixed objective function to learn a task, i.e., if the objective function changes slightly, for example, due to a change in the situation or context of the task, relearning is required to adapt to the new context.
Abbas Abdolmaleki +4 more
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Application of Covariance Matrix Adaptation-Evolution Strategy to Optimal Portfolio [PDF]
International Journal of Industrial Electronics, Control and Optimization, 2019 Capital portfolio management is considered an important issue in the field of economics and its main subject is about the scientific management of combination choice of assets that meet the specific investment objectives.
S. Amir Ghoreishi, Hamid Khaloozadeh
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Optimization of a Photonic Crystal Nanocavity Using Covariance Matrix Adaptation Evolution Strategy
IEEE Photonics Journal, 2022 H0-type photonic crystal nanocavities hold high quality factors Q and quite small cavity mode volumes. This study finds their ultrahigh Q structures, which allow stable operation as a nanolaser even with fabrication-induced disordering.
Kohei Takahashi, Toshihiko Baba
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Diagonal Acceleration for Covariance Matrix Adaptation Evolution Strategies [PDF]
Evolutionary Computation, 2020 We introduce an acceleration for covariance matrix adaptation evolution strategies (CMA-ES) by means of adaptive diagonal decoding (dd-CMA). This diagonal acceleration endows the default CMA-ES with the advantages of separable CMA-ES without inheriting its drawbacks.
Youhei Akimoto, Nikolaus Hansen
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An improved hyperparameter optimization framework for AutoML systems using evolutionary algorithms
Scientific Reports, 2023 For any machine learning model, finding the optimal hyperparameter setting has a direct and significant impact on the model’s performance. In this paper, we discuss different types of hyperparameter optimization techniques.
Amala Mary Vincent, P. Jidesh
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CMA-PSO Algorithm for Fuzzy Cloud Resource Scheduling
Journal of Harbin University of Science and Technology, 2022 Aiming at the multiobjective cloud resource scheduling problem, with the goal of optimizing the total completion time and total execution cost of the task, a fuzzy cloud resource scheduling model is established using the method of fuzzy mathematics ...
LI Cheng-yan, SONG Yue, MA Jin-tao
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An adaptive ES with a ranking based constraint handling strategy [PDF]
Yugoslav Journal of Operations Research, 2014 To solve a constrained optimization problem, equality constraints can be used to eliminate a problem variable. If it is not feasible, the relations imposed implicitly by the constraints can still be exploited.
Kusakci Ali Osman, Can Mehmet
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IEEE Access, 2023 Uncertainties caused by material variation can significantly impair the characteristics of devices. Therefore, it is important to design devices whose performance is not significantly damaged even when material variations occur. Robust optimization seeks
Akito Maruo, Hajime Igarashi
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Self-adaptive surrogate-assisted covariance matrix adaptation evolution strategy [PDF]
Proceedings of the 14th annual conference on Genetic and evolutionary computation, 2012 Genetic and Evolutionary Computation Conference (GECCO 2012) (2012)
Loshchilov, Ilya +2 more
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