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21 papers · 1 filter
Low Complexity Regularized Phase Retrieval
Jean-Jacques Godeme, Jalal Fadili
In this paper, we study the phase retrieval problem in the situation where the vector to be recovered has an a priori structure that can encoded into a regularization term. This re…
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…
Stable Phase Retrieval with Mirror Descent
Jean-Jacques Godeme, Jalal Fadili, Claude Amra +1
In this paper, we aim to reconstruct an n-dimensional real vector from m phaseless measurements corrupted by an additive noise. We extend the noiseless framework developed in [15],…
The stochastic Ravine accelerated gradient method with general extrapolation coefficients
Hedy Attouch, Jalal Fadili, Vyacheslav Kungurtsev
In a real Hilbert space domain setting, we study the convergence properties of the stochastic Ravine accelerated gradient method for convex differentiable optimization. We consider…
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…
Accelerated Gradient Dynamics on Riemannian Manifolds: Faster Rate and Trajectory Convergence
Tejas Natu, Camille Castera, Jalal Fadili +1
In order to minimize a differentiable geodesically convex function, we study a second-order dynamical system on Riemannian manifolds with an asymptotically vanishing damping term o…