activity
20172021
most citedRate of convergence of the Nesterov accelerated gradient method in the subcritical case

1 citations · 2 across the 6 of their papers we have counts for

collaborators

7 papers

math.OC2021

Damped inertial dynamics with vanishing Tikhonov regularization: strong asymptotic convergence towards the minimum norm solution

Hedy Attouch, Aicha Balhag, Zaki Chbani +1

In a Hilbert space, we provide a fast dynamic approach to the hierarchical minimization problem which consists in finding the minimum norm solution of a convex minimization problem…

math.OC2021

Convergence of iterates for first-order optimization algorithms with inertia and Hessian driven damping

Hedy Attouch, Zaki Chbani, Jalal Fadili +1

In a Hilbert space setting, for convex optimization, we show the convergence of the iterates to optimal solutions for a class of accelerated first-order algorithms. They can be int…

math.OC20211 cited

Fast convergence of dynamical ADMM via time scaling of damped inertial dynamics

Hedy Attouch, Zaki Chbani, Jalal Fadili +1

In this paper, we propose in a Hilbertian setting a second-order time-continuous dynamic system with fast convergence guarantees to solve structured convex minimization problems wi…

math.OC2020

Fast convex optimization via inertial dynamics combining viscous and Hessian-driven damping with time rescaling

Hedy Attouch, Aicha Balhag, Zaki Chbani +1

In a Hilbert setting, we develop fast methods for convex unconstrained optimization. We rely on the asymptotic behavior of an inertial system combining geometric damping with tempo…

math.OC2020

Fast convex optimization via a third-order in time evolution equation: TOGES-V an improved version of TOGES

Hedy Attouch, Zaki Chbani, Hassan Riahi

In a Hilbert space setting H, for convex optimization, we analyze the fast convergence properties as t tends to infinity of the trajectories generated by a third-order in time evol…

math.OC2019

First-order optimization algorithms via inertial systems with Hessian driven damping

Hedy Attouch, Zaki Chbani, Jalal Fadili +1

In a Hilbert space setting, for convex optimization, we analyze the convergence rate of a class of first-order algorithms involving inertial features. They can be interpreted as di…