Block-coordinate descent methods and identification of active constraints in huge-scale optimization

• Grant number: 14/14228-6
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: November 01, 2014
• End date: April 30, 2018
• Field of knowledge: Physical Sciences and Mathematics - Mathematics - Applied Mathematics
• Agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
• Principal Investigator: Sandra Augusta Santos
• Grantee: Ronaldo Lopes
• Host Institution: Instituto de Matemática, Estatística e Computação Científica (IMECC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 13/05475-7 - Computational methods in optimization, AP.TEM

Abstract

This research project aims to develop a thorough analysis of the block-coordinate descent methods for huge-scale convex minimization. A major purpose is to detect and exploit the identification properties of such a class of methods in problems with simple constraints. Another goal is to employ spectral elements in the identified subspace, to accomplish an efficient and robust method. The computational investigation will support the theoretical analysis and vice-versa. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

LOPES, R.; SANTOS, S. A.; SILVA, P. J. S.. Accelerating block coordinate descent methods with identification strategies. COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, v. 72, n. 3, p. 609-640, APR 2019. (14/14228-6, 13/05475-7, 13/07375-0)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

LOPES, Ronaldo. Block-coordinate descent methods and active-set identification for huge-scale problems. 2018. Doctoral Thesis - Universidade Estadual de Campinas (UNICAMP). Instituto de Matemática, Estatística e Computação Científica Campinas, SP.