A Parameter-Free Zeroth-Order Method with Covariance Matrix Adaptation and Effective Dimension

Excerpt

arXiv:2609.38561v1 Announce Type: cross Abstract: Zeroth-order optimization methods are essential for solving black-box problems where gradient information is unavailable or expensive to compute. This paper presents POEM-CMA, a novel parameter-free stochastic zeroth-order algorithm that extends the recent POEM method by integrating covariance matrix alignment and the notion of effective dimension. In contrast to traditional zeroth-order approaches that rely on isotropic random directions, POEM-C