Accélération de la convergence de quelques méthodes d'optimisation sans contraintes

Despite the difficulty in computing the exact proximity operator for these regularizers, efficient methods have been developed to compute approximate proximity operators in all of

Similar results hold in the partially 1-homogeneous setting, which covers the lifted problems of Section 2.1 when φ is bounded (e.g., sparse deconvolution and neural networks

For equality constrained problems, we proved in this paper second-order global convergence results, and local convergence results, using the theory of Fixed-Point Quasi-Newton

Ce compte-rendu sera pour cette séance le fichier python contenant le code demandé (avant chaque question, on reportera en commentaire le numéro de la question),.. Le nom de

With suitable assumptions on the function ℓ, the random case can be treated with well known stochastic approximation results [1, 5].. Various theoretical works [2, 3, 6] indicate

In this paper we study the convergence properties of the Nesterov’s family of inertial schemes which is a specific case of inertial Gradient Descent algorithm in the context of a

On graph of time, we can see that, for example, for n = 15 time in ms of conjugate gradient method equals 286 and time in ti of steepst descent method equals 271.. After that, we

block multiconvex, block coordinate descent, Kurdyka–Lojasiewicz inequality, Nash equilibrium, nonnegative matrix and tensor factorization, matrix completion, tensor