Jan 20, 2020 · The “Distribution Optimization” algorithm well separated the three Gaussian modes, however, the Bayesian decision limits slightly differed from ...
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Jul 12, 2014 · This paper proposes a novel finite Gaussian mixture model to study the population dynamics of evolutionary algorithms on continuous ...
This study is aimed at developing a framework capable of addressing this new line of research in the field of evolutionary computation. We used the Gaussian ...
Jul 12, 2014 · ABSTRACT. This paper proposes a novel finite Gaussian mixture model to study the population dynamics of evolutionary algorithms.
Jan 20, 2020 · There, the proposed algorithm successfully separated the modes, providing a basis for meaningful group separation while fitting the data ...
Dec 1, 2022 · A new hybrid evolutionary algorithm (EA) for Gaussian mixture model-based clustering is proposed. The EA is a steady-state method that, ...
In order to address this issue we propose in this paper a new evolutionary clustering algorithm based on Gaussian Mixture Model. Specifically, the algorithm ...
Apr 1, 2022 · Abstract:This paper presents a novel approach for guiding a Generative Adversarial Network trained on the FashionGen dataset to generate ...
This paper describes the Evolutionary Create & Eliminate for Expectation Maximization algorithm (ECE-EM) for learning finite Gaussian Mixture Models (GMMs).
In the paper the problem of learning of Gaussian mixture models (GMMs) is considered. A new approach based on hybridization of a self-adaptive version of ...