Results 41 to 50 of about 5,249 (165)

A novel hybrid algorithm based on Stochastic Fractal Search Algorithm and CMA-ES

Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 2023
In this study, a novel hybridization approach, which is called CMASFS and is based on the covariance matrix adaptation evolution strategy (CMA-ES) and the stochastic fractal search (SFS) algorithms.
Serdar Paçacı, Okan Bingöl, Uğur Güvenç   +2 more
doaj   +1 more source

CMA-ES for Safe Optimization

Proceedings of the Genetic and Evolutionary Computation Conference
In several real-world applications in medical and control engineering, there are unsafe solutions whose evaluations involve inherent risk. This optimization setting is known as safe optimization and formulated as a specialized type of constrained optimization problem with constraints for safety functions. Safe optimization requires performing efficient
Kento Uchida, Ryoki Hamano, Masahiro Nomura, Shota Saito, Shinichi Shirakawa   +4 more
openaire   +2 more sources

Warm Starting CMA-ES for Hyperparameter Optimization

Proceedings of the AAAI Conference on Artificial Intelligence, 2021
Hyperparameter optimization (HPO), formulated as black-box optimization (BBO), is recognized as essential for automation and high performance of machine learning approaches. The CMA-ES is a promising BBO approach with a high degree of parallelism, and has been applied to HPO tasks, often under parallel implementation, and shown superior performance to ...
Masahiro Nomura, Shuhei Watanabe, Youhei Akimoto, Yoshihiko Ozaki, Masaki Onishi   +4 more
openaire   +3 more sources

Allergic symptoms and sensitisation in adolescents with cows' milk allergy and atopic eczema in infancy

Immunity, Inflammation and Disease, 2020
Background The association between atopic sensitisation, atopic eczema (AE) and asthma is known, but distinct roles of allergies on long‐term health are unestablished.
Sonja Piippo, Mirva Viljanen, Erkki Savilahti, Mikael Kuitunen   +3 more
doaj   +1 more source

Knowledge-Based Perturbation LaF-CMA-ES for Multimodal Optimization

Applied Sciences
Multimodal optimization presents a significant challenge in optimization problems due to the existence of multiple attraction basins. Balancing exploration and exploitation is essential for the efficiency of algorithms designed to solve these problems ...
Huan Liu, Lijing Qin, Zhao Zhou
doaj   +1 more source

Benchmarking IPOP-CMA-ES-TPA and IPOP-CMA-ES-MSR on the BBOB Noiseless Testbed [PDF]

Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, 2015
We benchmark IPOP-CMA-ES, a restart Covariance Matrix Adaptation Evolution Strategy with increasing population size, with two step-size adaptation mechanisms, Two-Point Step-Size Adapation (TPA) and Median Success Rule (MSR), on the BBOB noiseless testbed.
openaire   +1 more source

Not All Parents Are Equal for MO-CMA-ES [PDF]

, 2011
The Steady State variants of the Multi-Objective Covariance Matrix Adaptation Evolution Strategy (SS-MO-CMA-ES) generate one offspring from a uniformly selected parent. Some other parental selection operators for SS-MO-CMA-ES are investigated in this paper. These operators involve the definition of multi-objective rewards, estimating the expectation of
Loshchilov, Ilya, Schoenauer, Marc, Sebag, Michèle   +2 more
openaire   +3 more sources

An Asynchronous Implementation of the Limited Memory CMA-ES [PDF]

2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA), 2015
We present our asynchronous implementation of the LM-CMA-ES algorithm, which is a modern evolution strategy for solving complex large-scale continuous optimization problems. Our implementation brings the best results when the number of cores is relatively high and the computational complexity of the fitness function is also high.
Viktor Arkhipov, Maxim Buzdalov 0001, Anatoly Shalyto 0001   +2 more
openaire   +2 more sources

Robust Covariance Matrix Adaptation Evolution Strategy: Optimal Design of Magnetic Devices Considering Material Variation

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
doaj   +1 more source

An Evolutional Topology Optimization Method Based on Kernel Level Set Function

IEEE Access
Topology optimizations involving evolutionary algorithms are promising approaches to solve practical engineering design problems, since their use of derivation-free algorithms makes them applicable to any design problem.
Takahiro Sato, Kota Watanabe, Hajime Igarashi   +2 more
doaj   +1 more source