PEPit: computer-assisted worst-case analyses of first-order optimization methods in Python

  • PEPit is a python package aiming at simplifying the access to worst-case analy- ses of a large family of first-order optimization methods possibly involving gradient, projection, proximal, or linear optimization oracles, along with their approximate, or Bregman variants. In short, PEPit is a package enabling computer-assisted worst- case analyses of first-order optimization methods. The key underlying idea is to cast the problem of performing a worst-case analysis, often referred to as a perfor- mance estimation problem (PEP), as a semidefinite program (SDP) which can be solved numerically. To do that, the package users are only required to write first-order methods nearly as they would have implemented them. The package then takes care of the SDP modeling parts, and the worst-case analysis is performed numerically via standard solvers.

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Metadaten
Author:Baptiste Goujaud, Céline Moucer, François Glineur, Julien M. Hendrickx, Adrien B. Taylor, Aymeric Dieuleveut
DOI:https://doi.org/10.1007/s12532-024-00259-7
ISSN:1867-2949
Parent Title (English):Mathematical Programming Computation
Publisher:Springer Science and Business Media LLC
Document Type:Article
Language:English
Year of Completion:2024
Volume:16
Issue:3
Page Number:31
First Page:337
Last Page:367
Mathematical Programming Computation :MPC 2024 - Issue 3
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