A convergence rate of the proximal point algorithm in Banach spaces. (3rd June 2018)

• Record Type: Journal Article
• Authors: Matsushita, Shin-ya
• Is Part Of: Optimization. Volume 67:Number 6(2018)
• Page Start: 881
• Page End: 888
• Publication Date: 2018-06-03
• Subjects: Proximal point algorithm -- convergence rate -- convex minimization problem -- Banach space -- alternating projections -- averaged projections; Mathematical optimization -- Periodicals; 519.7
• DOI: 10.1080/02331934.2018.1432609
• Languages: English
• ISSNs: 0233-1934

Abstract

Abstract: We consider the convergence rate of the proximal point algorithm (PPA) for finding a minimizer of proper lower semicontinuous convex functions. In the Hilbert space setting, Güler showed that the big- O rate of the PPA can be improved to little- o when the sequence generated by the algorithm converges strongly to a minimizer. In this paper, we establish little- o rate of the PPA in Banach spaces without requiring this assumption. Then we apply the result to give new results on the convergence rate for sequences of alternating and averaged projections.