A Projective Splitting Method for Monotone Inclusions: Iteration-Complexity and Application to Composite Optimization

Majela Pentón Machado () and Mauricio Romero Sicre ()
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Majela Pentón Machado: Universidade Federal da Bahia
Mauricio Romero Sicre: Universidade Federal da Bahia

Journal of Optimization Theory and Applications, 2023, vol. 198, issue 2, No 5, 552-587

Abstract: Abstract We propose an inexact projective splitting method to solve the problem of finding a zero of a sum of maximal monotone operators. We perform convergence and complexity analyses of the method by viewing it as a special instance of an inexact proximal point method proposed by Solodov and Svaiter in 2001, for which pointwise and ergodic complexity results have been studied recently by Sicre. Also, for this latter method, we establish convergence rates and complexity bounds for strongly monotone inclusions, from where we obtain linear convergence for our projective splitting method under strong monotonicity and cocoercivity assumptions. We apply the proposed projective splitting scheme to composite convex optimization problems and establish pointwise and ergodic function value convergence rates, extending a recent work of Johnstone and Eckstein.

Keywords: Monotone inclusion problems; Hybrid proximal extragradient methods; Splitting algorithms; Iteration-complexity; Convex optimization; 49M27; 47H05; 90C60 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10957-023-02214-3

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