Understanding FISTA's weak convergence: A step-by-step introduction to the 2025 milestone
Heinz H. Bauschke, Walaa M. Moursi
TL;DR
The paper proves the weak convergence of FISTA iterates for minimizing $F(x)=f(x)+g(x)$ in a real Hilbert space, a milestone achieved in 2025 by independent teams. It weaves an accessible, self-contained exposition around boundedness, cluster-point analysis, and auxiliary sequences, culminating in a structured proof that leverages the BCCH Lemma and Salzo sequences. The work connects finite-sample rate results, continuous-time perspectives, and recent developments to deliver a teaching-friendly account, including optional bonus material and a convex feasibility example with a non-unique minimizer. The findings solidify the theoretical foundations of FISTA in infinite-dimensional settings and enhance its reliability for practical, accelerated proximal-gradient optimization.
Abstract
Beck and Teboulle's FISTA for finding the minimizer of the sum of two convex functions is one of the most important algorithms of the past decades. While function value convergence of the iterates was known, the actual convergence of the iterates remained elusive until October 2025 when Jang and Ryu, as well as Boţ, Fadili, and Nguyen proved weak convergence. In this paper, we provide a gentle self-contained introduction to the proof of their remarkable result.
