On the convergence rate of the Halpern-iteration

Author:

Lieder FelixORCID

Abstract

AbstractIn this work, we give a tight estimate of the rate of convergence for the Halpern-iteration for approximating a fixed point of a nonexpansive mapping in a Hilbert space. Specifically, using semidefinite programming and duality we prove that the norm of the residuals is upper bounded by the distance of the initial iterate to the closest fixed point divided by the number of iterations plus one.

Funder

Heinrich-Heine-Universität Düsseldorf

Publisher

Springer Science and Business Media LLC

Subject

Control and Optimization

Reference18 articles.

1. Cominetti, R., Soto, J.A., Vaisman, J.: On the rate of convergence of Krasnoselskii–Mann iterations and their connection with sums of Bernoullis. Isr. J. Math. 199(2), 757–772 (2014)

2. Gu, G., Yang, J.: Optimal nonergodic sublinear convergence rate of proximal point algorithm for maximal monotone inclusion problems (2019). arXiv preprint arXiv:1904.05495

3. Gu, G., Yang, J.: On the optimal linear convergence factor of the relaxed proximal point algorithm for monotone inclusion problems (2019). arXiv preprint arXiv:1905.04537

4. Gu, G., Yang, J.: On the optimal ergodic sublinear convergence rate of the relaxed proximal point algorithm for variational inequalities (2019). arXiv preprint arXiv:1905.06030

5. Halpern, B.: Fixed points of nonexpanding maps. Bull. Am. Math. Soc. 73(6), 957–961 (1967)

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