4 papers
Fast Spawn\&Prune (FS\&P): Global convergence of stochastic conic particle gradient descent via birth/death process
Yohann De Castro, Sébastien Gadat, Clément Marteau
We investigate the global optimization of the objective function arising in continuous sparse regression, specifically the Beurling LASSO (BLASSO), over the space of measures. Whil…
Gaussian Mixture Model with unknown diagonal covariances via continuous sparse regularization
Romane Giard, Yohann de Castro, Clément Marteau
This paper addresses the statistical estimation of Gaussian Mixture Models (GMMs) with unknown diagonal covariances from independent and identically distributed samples. We employ…
Generalization Bounds of Surrogate Policies for Combinatorial Optimization Problems
Pierre-Cyril Aubin-Frankowski, Yohann De Castro, Axel Parmentier +1
Many real-world decision problems require solving, again and again, combinatorial optimization instances drawn from a common distribution. A recent line of structured learning meth…
Second Maximum of a Gaussian Random Field and Exact (t-)Spacing test
Jean-Marc Azaïs, Federico Dalmao, Yohann De Castro
In this article, we introduce the novel concept of the second maximum of a Gaussian random field on a Riemannian submanifold. This second maximum serves as a powerful tool for char…