10 papers · 1 filter
Fast Stochastic Second-Order Adagrad for Nonconvex Bound-Constrained Optimization
S. Bellavia, S. Gratton, B. Morini +1
ADAGB2, a generalization of the Adagrad algorithm for stochastic optimization is introduced, which is also applicable to bound-constrained problems and capable of using second-orde…
An objective-function-free algorithm for general smooth constrained optimization
S. Bellavia, S. Gratton, B. Morini +1
A new algorithm for smooth constrained optimization is proposed that never computes the value of the problem's objective function and that handles both equality and inequality cons…
Fully stochastic trust-region methods with Barzilai-Borwein steplengths
Stefania Bellavia, Benedetta Morini, Mahsa Yousefi
We investigate stochastic gradient methods and stochastic counterparts of the Barzilai-Borwein steplengths and their application to finite-sum minimization problems. Our proposal i…
A variable dimension sketching strategy for nonlinear least-squares
Stefania Bellavia, Greta Malaspina, Benedetta Morini
We present a stochastic inexact Gauss-Newton method for the solution of nonlinear least-squares. To reduce the computational cost with respect to the classical method, at each iter…
A discrete Consensus-Based Global Optimization Method with Noisy Objective Function
Stefania Bellavia, Greta Malaspina
Consensus based optimization is a derivative-free particles-based method for the solution of global optimization problems. Several versions of the method have been proposed in the…
An optimally fast objective-function-free minimization algorithm using random subspaces
S. Bellavia, S. Gratton, B. Morini +1
An algorithm for unconstrained non-convex optimization is described, which does not evaluate the objective function and in which minimization is carried out, at each iteration, wit…