Accelerated Gradient Descent by Concatenation of Stepsize Schedules

Fuente: arXiv
Guardado en:
Detalles Bibliográficos
Autores principales: Zhang, Zehao, Jiang, Rujun
Formato: Preprint
Publicado: 2024
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866908833890172928
author Zhang, Zehao
Jiang, Rujun
author_facet Zhang, Zehao
Jiang, Rujun
contents This work considers stepsize schedules for gradient descent on smooth convex objectives. We extend the existing literature and propose a unified technique for constructing stepsizes with analytic bounds for an arbitrary number of iterations. This technique constructs new stepsize schedules by concatenating two stepsize schedules with fewer steps. Using this approach, we introduce two new families of stepsize schedules, achieving a convergence rate of $O(n^{-\log_2(\sqrt 2+1)})$ with state-of-the-art constants for the objective value and gradient norm of the last iterate, respectively. Furthermore, our analytically derived stepsize schedules either match or surpass the existing best numerically computed stepsize schedules.
format Preprint
id arxiv_https___arxiv_org_abs_2410_12395
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Accelerated Gradient Descent by Concatenation of Stepsize Schedules
Zhang, Zehao
Jiang, Rujun
Optimization and Control
This work considers stepsize schedules for gradient descent on smooth convex objectives. We extend the existing literature and propose a unified technique for constructing stepsizes with analytic bounds for an arbitrary number of iterations. This technique constructs new stepsize schedules by concatenating two stepsize schedules with fewer steps. Using this approach, we introduce two new families of stepsize schedules, achieving a convergence rate of $O(n^{-\log_2(\sqrt 2+1)})$ with state-of-the-art constants for the objective value and gradient norm of the last iterate, respectively. Furthermore, our analytically derived stepsize schedules either match or surpass the existing best numerically computed stepsize schedules.
title Accelerated Gradient Descent by Concatenation of Stepsize Schedules
topic Optimization and Control
url https://arxiv.org/abs/2410.12395