4 papers
Fully Convergent Projection-based Methods with Momentum under Nonconvex Geometric
Matteo Lapucci, Diego Scuppa
Nonlinear optimization problems with complicated, nonconvex, yet geometrically structured constraints can be tackled by projected-gradient methods: under weak regularity assumption…
Projected Gradient Methods with Momentum
Matteo Lapucci, Giampaolo Liuzzi, Stefano Lucidi +2
We focus on the optimization problem with smooth, possibly nonconvex objectives and a convex constraint set for which the Euclidean projection operation is practically available. F…
Nonconvex optimization methods for ground states in disordered continuous-spin models
Ramgopal Agrawal, Lorenzo Ciarpaglini, Pierluigi Mansueto +4
This work explores the global optimization problem of finding lowest-energy configurations in disordered continuous-spin models from statistical physics, with a particular focus on…
Riemannian Gradient Method with Momentum
Filippo Leggio, Diego Scuppa
In this paper, we consider the problem of minimizing a smooth function on a Riemannian manifold and present a Riemannian gradient method with momentum. The proposed algorithm repre…