Scalable Projection-Free Optimization Methods via MultiRadial Duality Theory

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Samakhoana, Thabo, Grimmer, Benjamin
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866909184754188288
author Samakhoana, Thabo
Grimmer, Benjamin
author_facet Samakhoana, Thabo
Grimmer, Benjamin
contents Recent works have developed new projection-free first-order methods based on utilizing linesearches and normal vector computations to maintain feasibility. These oracles can be cheaper than orthogonal projection or linear optimization subroutines but have the drawback of requiring a known strictly feasible point to do these linesearches with respect to. In this work, we develop new theory and algorithms which can operate using these cheaper linesearches while only requiring knowledge of points strictly satisfying each constraint separately. Convergence theory for several resulting ``multiradial'' gradient methods is established. We also provide preliminary numerics showing performance is essentially independent of how one selects the reference points for synthetic quadratically constrained quadratic programs.
format Preprint
id arxiv_https___arxiv_org_abs_2403_13688
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Scalable Projection-Free Optimization Methods via MultiRadial Duality Theory
Samakhoana, Thabo
Grimmer, Benjamin
Optimization and Control
Recent works have developed new projection-free first-order methods based on utilizing linesearches and normal vector computations to maintain feasibility. These oracles can be cheaper than orthogonal projection or linear optimization subroutines but have the drawback of requiring a known strictly feasible point to do these linesearches with respect to. In this work, we develop new theory and algorithms which can operate using these cheaper linesearches while only requiring knowledge of points strictly satisfying each constraint separately. Convergence theory for several resulting ``multiradial'' gradient methods is established. We also provide preliminary numerics showing performance is essentially independent of how one selects the reference points for synthetic quadratically constrained quadratic programs.
title Scalable Projection-Free Optimization Methods via MultiRadial Duality Theory
topic Optimization and Control
url https://arxiv.org/abs/2403.13688