A Concise Lyapunov Analysis of Nesterov's Accelerated Gradient Method
Not on the map. Why?
Abstract (arXiv)
Convergence analysis of Nesterov's accelerated gradient method has attracted significant attention over the past decades. While extensive work has explored its theoretical properties and elucidated the intuition behind its acceleration, a simple and direct proof of its convergence rates is still lacking. We provide a concise Lyapunov analysis of the convergence rates of Nesterov's accelerated gradient method for both general convex and strongly convex functions.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 17 references that are in the map. First posted on arXiv 24 Feb 2025.
Builds on
7 of 17 references.
References · 7
- 2016Optimization Methods for Large-Scale Machine Learningcited by 1,150
- 2015A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insightscited by 206
- 2014Analysis and Design of Optimization Algorithms via Integral Quadratic Constraintscited by 105
- 2021Acceleration Methodscited by 48
- 2020On the Convergence of Nesterov's Accelerated Gradient Method in Stochastic Settingscited by 27
- 2017Dissipativity Theory for Nesterov's Accelerated Methodcited by 22
- 2022Analysis of Gradient Descent with Varying Step Sizes using Integral Quadratic Constraintscited by 1
Built on by
Not cited yet.