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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Accelerating block coordinate descent methods with identification strategies

Full text
Author(s):
Lopes, R. [1] ; Santos, S. A. [1] ; Silva, P. J. S. [1]
Total Authors: 3
Affiliation:
[1] Univ Estadual Campinas, Inst Math, Rua Sergio Buarque de Holanda 651, BR-13083859 Campinas, SP - Brazil
Total Affiliations: 1
Document type: Journal article
Source: COMPUTATIONAL OPTIMIZATION AND APPLICATIONS; v. 72, n. 3, p. 609-640, APR 2019.
Web of Science Citations: 0
Abstract

This work is about active set identification strategies aimed at accelerating block-coordinate descent methods (BCDM) applied to large-scale problems. We start by devising an identification function tailored for bound-constrained composite minimization together with an associated version of the BCDM, called Active BCDM, that is also globally convergent. The identification function gives rise to an efficient practical strategy for Lasso and 1-regularized logistic regression. The computational performance of Active BCDM is contextualized using comparative sets of experiments that are based on the solution of problems with data from deterministic instances from the literature. These results have been compared with those of well-established and state-of-the-art methods that are particularly suited for the classes of applications under consideration. Active BCDM has proved useful in achieving fast results due to its identification strategy. Besides that, an extra second-order step was used, with favorable cost-benefit. (AU)

FAPESP's process: 14/14228-6 - Block-coordinate descent methods and identification of active constraints in huge-scale optimization
Grantee:Ronaldo Lopes
Support Opportunities: Scholarships in Brazil - Doctorate
FAPESP's process: 13/05475-7 - Computational methods in optimization
Grantee:Sandra Augusta Santos
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:Francisco Louzada Neto
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC