Irreducibility of nonsmooth state-space models with an application to CMA-ES - Centre de mathématiques appliquées (CMAP)
Pré-Publication, Document De Travail Année : 2024

Irreducibility of nonsmooth state-space models with an application to CMA-ES

Résumé

We analyze a stochastic process resulting from the normalization of states in the zeroth-order optimization method CMA-ES. On a specific class of minimization problems where the objective function is scaling-invariant, this process defines a time-homogeneous Markov chain whose convergence at a geometric rate can imply the linear convergence of CMA-ES. However, the analysis of the intricate updates for this process constitute a great mathematical challenge. We establish that this Markov chain is an irreducible and aperiodic T-chain. These contributions represent a first major step for the convergence analysis towards a stationary distribution. We rely for this analysis on conditions for the irreducibility of nonsmooth state-space models on manifolds. To obtain our results, we extend these conditions to address the irreducibility in different hyperparameter settings that define different Markov chains, and to include nonsmooth state spaces.
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Dates et versions

hal-04713675 , version 1 (29-09-2024)
hal-04713675 , version 2 (30-09-2024)

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Armand Gissler, Shan-Conrad Wolf, Anne Auger, Nikolaus Hansen. Irreducibility of nonsmooth state-space models with an application to CMA-ES. 2024. ⟨hal-04713675v2⟩
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