CMA-ES: A Function Value Free Second Order Optimization Method
Résumé
We give a bird's-eye view introduction to the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) and emphasize relevant design aspects of the algorithm, namely its invariance properties. While CMA-ES is gradient and function value free, we show that using the gradient in CMA-ES is possible and can reduce the number of iterations on unimodal, smooth functions.
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