Extensions to the Proximal Distance Method of Constrained Optimization.

ADMM Majorization minimization convergence steepest descent

Journal

Journal of machine learning research : JMLR
ISSN: 1532-4435
Titre abrégé: J Mach Learn Res
Pays: United States
ID NLM: 101262635

Informations de publication

Date de publication:
2022
Historique:
medline: 1 1 2022
pubmed: 1 1 2022
entrez: 19 5 2023
Statut: ppublish

Résumé

The current paper studies the problem of minimizing a loss

Identifiants

pubmed: 37205013
pmc: PMC10191389
mid: NIHMS1884244
pii:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : NHGRI NIH HHS
ID : R01 HG006139
Pays : United States
Organisme : NIGMS NIH HHS
ID : R35 GM141798
Pays : United States

Références

IEEE Trans Image Process. 2011 Jun;20(6):1517-28
pubmed: 21193375
Math Program. 2014 Aug 1;146:409-436
pubmed: 25392563
J Comput Graph Stat. 2015;24(4):994-1013
pubmed: 27087770
J Mach Learn Res. 2019 Apr;20:
pubmed: 31649491

Auteurs

Alfonso Landeros (A)

Department of Computational Medicine, University of California, Los Angeles CA 90095-1596, USA.

Oscar Hernan Madrid Padilla (OHM)

Department of Statistics, University of California, Los Angeles CA 90095-1554, USA.

Hua Zhou (H)

Departments of Biostatistics and Computational Medicine, University of California, Los Angeles CA 90095-1596, USA.

Kenneth Lange (K)

Departments of Computational Medicine, Human Genetics, and Statistics,University of California, Los Angeles CA 90095-1596, USA.

Classifications MeSH