adjoint mismatch – Optimization Online

Convergence Results for Primal-Dual Algorithms in the Presence of Adjoint Mismatch

Published: 2022/04/17

Convex Optimization, Nonsmooth Optimization adjoint mismatch, convergence analysis, convex optimization, CT reconstruction, fixed point theory, forward-backward splitting, primal-dual algorithms, Tseng’s splitting

Most optimization problems arising in imaging science involve high-dimensional linear operators and their adjoints. In the implementations of these operators, approximations may be introduced for various practical considerations (e.g., memory limitation, computational cost, convergence speed), leading to an adjoint mismatch. This occurs for the X-ray tomographic inverse problems found in Computed Tomography (CT), where the … Read more

Convergence of Proximal Gradient Algorithm in the Presence of Adjoint Mismatch

Published: 2020/10/08, Updated: 2021/01/14

Émilie Chouzenoux

Jean-Christophe Pesquet

Cyril Riddel

Marion Savanier

Yves Trousset

Convex Optimization, Nonsmooth Optimization adjoint mismatch, computed tomography, convergence analysis, convex optimization, fixed point methods, forward-backward algorithm, image reconstruction

We consider the proximal gradient algorithm for solving penalized least-squares minimization problems arising in data science. This first-order algorithm is attractive due to its flexibility and minimal memory requirements allowing to tackle large-scale minimization problems involving non-smooth penalties. However, for problems such as X-ray computed tomography, the applicability of the algorithm is dominated by the … Read more