6 papers
An SDE Perspective on Stochastic Inertial Gradient Dynamics with Time-Dependent Viscosity and Geometric Damping
Rodrigo Maulen-Soto, Jalal Fadili, Hedy Attouch +1
Our approach is part of the close link between continuous dissipative dynamical systems and optimization algorithms. We aim to solve convex minimization problems by means of stocha…
Tikhonov Regularization for Stochastic Non-Smooth Convex Optimization in Hilbert Spaces
Rodrigo Maulen-Soto, Jalal Fadili, Hedy Attouch
To solve convex optimization problems with a noisy gradient input, we analyze the global behavior of subgradient-like flows under stochastic errors. The objective function is compo…
Recovering Nesterov accelerated dynamics from Heavy Ball dynamics via time rescaling
Hedy Attouch, Radu Ioan Bot, David Alexander Hulett +1
In a real Hilbert space, we consider two classical problems: the global minimization of a smooth and convex function (i.e., a convex optimization problem) and finding the zeros…
Stochastic Inertial Dynamics Via Time Scaling and Averaging
Rodrigo Maulen-Soto, Jalal Fadili, Hedy Attouch +1
Our work is part of the close link between continuous-time dissipative dynamical systems and optimization algorithms, and more precisely here, in the stochastic setting. We aim to…
Fast convex optimization via closed-loop time scaling of gradient dynamics
Hedy Attouch, Radu Ioan Bot, Dang-Khoa Nguyen
In a Hilbert setting, for convex differentiable optimization, we develop a general framework for adaptive accelerated gradient methods. They are based on damped inertial dynamics w…
Stochastic Monotone Inclusion with Closed Loop Distributions
Hamza Ennaji, Jalal Fadili, Hedy Attouch
In this paper, we study in a Hilbertian setting, first and second-order monotone inclusions related to stochastic optimization problems with decision dependent distributions. The s…