17 citations · 48 across the 20 of their papers we have counts for
Showing math.OCShow all
2 papers · 1 filter
math.OC2026
Riemannian Gradient Descent for Gaussian Mixture Models with unknown diagonal covariances
Romane Giard, Yohann De Castro, Roland Denis +1
This paper investigates the numerical resolution of the Beurling-LASSO (BLASSO), a convex optimization framework that promotes sparsity in the space of measures. We consider its ap…
math.OC2023★ 1 cited
FastPart: Over-Parameterized Stochastic Gradient Descent for Sparse optimisation on Measures
Yohann De Castro, Sébastien Gadat, Clément Marteau
This paper presents a novel algorithm that leverages Stochastic Gradient Descent strategies in conjunction with Random Features to augment the scalability of Conic Particle Gradien…