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Main Author: Salzo, Saverio
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2511.12665
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author Salzo, Saverio
author_facet Salzo, Saverio
contents Very recently, the papers "Point Convergence of Nesterov's Accelerated Gradient Method: An AI-Assisted Proof" by Jang and Ryu, and "The Iterates of Nesterov's Accelerated Algorithm Converge in the Critical Regimes" by Bot, Fadili, and Nguyen simultaneously have resolved a long-standing open problem concerning Nesterov's accelerated gradient method. These works show that the iterates of the algorithm (known in its composite form as FISTA) indeed converge to an optimal solution. In this work, we extend these results and prove that, in infinite dimensional Hilbert spaces, the iterates of such an algorithm still converge (in the weak sense) even when the proximity operator and the gradient are computed inexactly, with the latter possibly stochastic.
format Preprint
id arxiv_https___arxiv_org_abs_2511_12665
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The iterates of FISTA convergence even under inexact computations and stochastic gradients
Salzo, Saverio
Optimization and Control
65K05, 90C25, 90C15, 49M27
Very recently, the papers "Point Convergence of Nesterov's Accelerated Gradient Method: An AI-Assisted Proof" by Jang and Ryu, and "The Iterates of Nesterov's Accelerated Algorithm Converge in the Critical Regimes" by Bot, Fadili, and Nguyen simultaneously have resolved a long-standing open problem concerning Nesterov's accelerated gradient method. These works show that the iterates of the algorithm (known in its composite form as FISTA) indeed converge to an optimal solution. In this work, we extend these results and prove that, in infinite dimensional Hilbert spaces, the iterates of such an algorithm still converge (in the weak sense) even when the proximity operator and the gradient are computed inexactly, with the latter possibly stochastic.
title The iterates of FISTA convergence even under inexact computations and stochastic gradients
topic Optimization and Control
65K05, 90C25, 90C15, 49M27
url https://arxiv.org/abs/2511.12665