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20072024
most citedMarkov Chain Analysis of Cumulative Step-size Adaptation on a Linear Constrained Problem

1.8k citations · 2.6k across the 30 of their papers we have counts for

collaborators

33 papers

math.OC2024

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

Armand Gissler, Shan-Conrad Wolf, Anne Auger +1

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 ob…

math.NA2024

Asymptotic estimations of a perturbed symmetric eigenproblem

Armand Gissler, Anne Auger, Nikolaus Hansen

We study ill-conditioned positive definite matrices that are disturbed by the sum of rank-one matrices of a specific form. We provide estimates for the eigenvalues and eigenvec…

math.OC2024

On the irreducibility and convergence of a class of nonsmooth nonlinear state-space models on manifolds and their applications to zeroth-order optimization

Armand Gissler, Alain Durmus, Anne Auger

In this paper, we analyze a large class of general nonlinear state-space models on a state-space X, defined by the recursion , , wh…

math.OC2021

Global linear convergence of Evolution Strategies with recombination on scaling-invariant functions

Cheikh Touré, Anne Auger, Nikolaus Hansen

Evolution Strategies (ES) are stochastic derivative-free optimization algorithms whose most prominent representative, the CMA-ES algorithm, is widely used to solve difficult numeri…

math.OC2021

Scaling-invariant functions versus positively homogeneous functions

Cheikh Touré, Armand Gissler, Anne Auger +1

Scaling-invariant functions preserve the order of points when the points are scaled by the same positive scalar (with respect to a unique reference point). Composites of strictly m…

math.NA2020

Global Linear Convergence of Evolution Strategies on More Than Smooth Strongly Convex Functions

Youhei Akimoto, Anne Auger, Tobias Glasmachers +1

Evolution strategies (ESs) are zeroth-order stochastic black-box optimization heuristics invariant to monotonic transformations of the objective function. They evolve a multivariat…