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20222026
most citedCMA-ES with Margin: Lower-Bounding Marginal Probability for Mixed-Integer Black-Box Optimization

48 citations · 57 across the 12 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

math.OC2024

CMA-ES for Discrete and Mixed-Variable Optimization on Sets of Points

Kento Uchida, Ryoki Hamano, Masahiro Nomura +2

Discrete and mixed-variable optimization problems have appeared in several real-world applications. Most of the research on mixed-variable optimization considers a mixture of integ…

cs.NE2024

Tail Bounds on the Runtime of Categorical Compact Genetic Algorithm

Ryoki Hamano, Kento Uchida, Shinichi Shirakawa +2

The majority of theoretical analyses of evolutionary algorithms in the discrete domain focus on binary optimization algorithms, even though black-box optimization on the categorica…

cs.NE2024

Natural Gradient Interpretation of Rank-One Update in CMA-ES

Ryoki Hamano, Shinichi Shirakawa, Masahiro Nomura

The covariance matrix adaptation evolution strategy (CMA-ES) is a stochastic search algorithm using a multivariate normal distribution for continuous black-box optimization. In add…

cs.NE2024

CMA-ES for Safe Optimization

Kento Uchida, Ryoki Hamano, Masahiro Nomura +2

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 saf…

cs.NE2024★ 8 cited

CatCMA : Stochastic Optimization for Mixed-Category Problems

Ryoki Hamano, Shota Saito, Masahiro Nomura +2

Black-box optimization problems often require simultaneously optimizing different types of variables, such as continuous, integer, and categorical variables. Unlike integer variabl…