Running summarizing tools on a new article

Check the paper below, then start its synthesis.

Polynomial Preconditioning for Accelerated Convergence of Proximal Algorithms including FISTA

Siddharth Iyer, Frank Ong, Kawin Setsompop

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scienti

DOI: 10.58530/2022/3483 (Computer Science)

Abstract: This work aims to accelerate the convergence of proximal gradient algorithms (like FISTA) by designing a preconditioner using polynomials that targets the eigenvalue spectrum of the forward linear model to enable faster convergence. The preconditioner does not assume any explicit structure and can be applied to various imaging applications. The efficacy of the preconditioner is validated on four varied imaging applications, where it seen to achieve 2-4x faster convergence.

Published on 03 Aug. 2023