286 citations · 374 across the 36 of their papers we have counts for
5 papers · 2 filters
Accelerated gradient methods with strong convergence to the minimum norm minimizer: a dynamic approach combining time scaling, averaging, and Tikhonov regularization
Hedy Attouch, Zaki Chbani, Hassan Riahi
In a Hilbert framework, for convex differentiable optimization, we consider accelerated gradient methods obtained by combining temporal scaling and averaging techniques with Tikhon…
Fast convex optimization via time scale and averaging of the steepest descent
Hedy Attouch, Radu Ioan Bot, Dang-Khoa Nguyen
In a Hilbert setting, we develop a gradient-based dynamic approach for fast solving convex optimization problems. By applying time scaling, averaging, and perturbation techniques t…
An SDE perspective on stochastic convex optimization
Rodrigo Maulen-Soto, Jalal Fadili, Hedy Attouch
We analyze the global and local behavior of gradient-like flows under stochastic errors towards the aim of solving convex optimization problems with noisy gradient input. We first…
Accelerated gradient methods combining Tikhonov regularization with geometric damping driven by the Hessian
Hedy Attouch, Aicha Balhag, Zaki Chbani +1
In a Hilbert setting, for convex differentiable optimization, we consider accelerated gradient dynamics combining Tikhonov regularization with Hessian-driven damping. The Tikhonov…
From the Ravine method to the Nesterov method and vice versa: a dynamical system perspective
H. Attouch, J. Fadili
We revisit the Ravine method of Gelfand and Tsetlin from a dynamical system perspective, study its convergence properties, and highlight its similarities and differences with the N…