8 citations · 15 across the 25 of their papers we have counts for
4 papers · 1 filter
Subsampled Nonmonotone Spectral Gradient Methods
Stefania Bellavia, Nataša Krklec Jerinkić, Greta Malaspina
This paper deals with subsampled spectral gradient methods for minimizing finite sum. Subsample function and gradient approximations are employed in order to reduce the overall com…
Subsampled Inexact Newton methods for minimizing large sums of convex functions
Stefania Bellavia, Natasa Krejic, Natasa Krklec Jerinkic
This paper deals with the minimization of large sum of convex functions by Inexact Newton (IN) methods employing subsampled functions, gradients and Hessian approximations. The Con…
Adaptive Regularization Algorithms with Inexact Evaluations for Nonconvex Optimization
S. Bellavia, G. Gurioli, B. Morini +1
A regularization algorithm using inexact function values and inexact derivatives is proposed and its evaluation complexity analyzed. This algorithm is applicable to unconstrained p…
Adaptive Cubic Regularization Methods with Dynamic Inexact Hessian Information and Applications to Finite-Sum Minimization
Stefania Bellavia, Gianmarco Gurioli, Benedetta Morini
We consider the Adaptive Regularization with Cubics approach for solving nonconvex optimization problems and propose a new variant based on inexact Hessian information chosen dynam…