activity
20222025
most citedComparison of an Apocalypse-Free and an Apocalypse-Prone First-Order Low-Rank Optimization Algorithm

2 citations · 2 across the 2 of their papers we have counts for

collaborators

7 papers

math.OC2025

The tangent cone to the real determinantal variety: various expressions and a proof

Guillaume Olikier, Petar Mlinarić, P. -A. Absil +1

The set of real matrices of upper-bounded rank is a real algebraic variety called the real generic determinantal variety. An explicit description of the tangent cone to that variet…

stat.ME2025

Eigengap Sparsity for Covariance Parsimony

Tom Szwagier, Guillaume Olikier, Xavier Pennec

Covariance estimation is a central problem in statistics. An important issue is that there are rarely enough samples to accurately estimate the coefficients in di…

math.OC2024

Computing Bouligand stationary points efficiently in low-rank optimization

Guillaume Olikier, P. -A. Absil

This paper considers the problem of minimizing a differentiable function with locally Lipschitz continuous gradient on the algebraic variety of all -by- real matrices of rank…

math.OC2024

Projected gradient descent accumulates at Bouligand stationary points

Guillaume Olikier, Irène Waldspurger

This paper considers the projected gradient descent (PGD) algorithm for the problem of minimizing a continuously differentiable function on a nonempty closed subset of a Euclidean…

math.OC2024

Retractions on closed sets

Guillaume Olikier

On a manifold or a closed subset of a Euclidean vector space, a retraction enables to move in the direction of a tangent vector while staying on the set. Retractions are a versatil…

math.OC2023

Rank Estimation for Third-Order Tensor Completion in the Tensor-Train Format

Charlotte Vermeylen, Guillaume Olikier, P. -A. Absil +1

We propose a numerical method to obtain an adequate value for the upper bound on the rank for the tensor completion problem on the variety of third-order tensors of bounded tensor-…