A new envelope function for nonsmooth DC optimization

Andreas Themelis, Ben Hermans, Panagiotis Patrinos

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

Difference-of-convex (DC) optimization problems are shown to be equivalent to the minimization of a Lipschitz-differentiable envelope. A gradient method on this surrogate function yields a novel (sub)gradient-free proximal algorithm which is inherently parallelizable and can handle fully nonsmooth formulations. Newton-type methods such as L-BFGS are directly applicable with a classical linesearch. Our analysis reveals a deep kinship between the novel DC envelope and the forward-backward envelope, the former being a smooth and convexity-preserving nonlinear reparametrization of the latter.

本文言語英語
ホスト出版物のタイトル2020 59th IEEE Conference on Decision and Control, CDC 2020
出版社Institute of Electrical and Electronics Engineers Inc.
ページ4697-4702
ページ数6
ISBN(電子版)9781728174471
DOI
出版ステータス出版済み - 12 14 2020
外部発表はい
イベント59th IEEE Conference on Decision and Control, CDC 2020 - Virtual, Jeju Island, 大韓民国
継続期間: 12 14 202012 18 2020

出版物シリーズ

名前Proceedings of the IEEE Conference on Decision and Control
2020-December
ISSN(印刷版)0743-1546

会議

会議59th IEEE Conference on Decision and Control, CDC 2020
Country大韓民国
CityVirtual, Jeju Island
Period12/14/2012/18/20

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modelling and Simulation
  • Control and Optimization

フィンガープリント 「A new envelope function for nonsmooth DC optimization」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル