A reflected forward-backward splitting method for monotone inclusions involving Lipschitzian operators
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Abstract (arXiv)
The proximal extrapolated gradient method citeMalitsky18a is an extension of the projected reflected gradient method citeMalitsky15. Both methods were proposed for solving the classic variational inequalities. In this paper, we investigate the projected reflected gradient method, in the general setting, for solving monotone inclusions involving Lipschitzian operators. As a result, we obtain a simple method for finding a zero point of the sum of two monotone operators where one of them is Lipschizian. We also show that one can improve the range of the stepsize of this method for the case when the Lipschitzian operator is restricted to be cocoercive. A nice combination of this method and the forward-backward splitting was proposed. As a result, we obtain a new splitting method for finding a zero point of the sum of three operators ( maximally monotone + monotone Lipschitzian + cocoercive). Application to composite monotone inclusions are demonstrated.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Aug 2019.
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Citing papers per year: 2023: 2; 2024: 1.
3 papers.
- 2023Sublinear Convergence Rates of Extragradient-Type Methods: A Survey on Classical and Recent Developmentscited by 5
- 2024An Inexact Halpern Iteration with Application to Distributionally Robust Optimizationcited by 2
- 2023Extragradient-Type Methods with O (1/k) Last-Iterate Convergence Rates for Co-Hypomonotone Inclusionscited by 0
- 2024An Inexact Halpern Iteration with Application to Distributionally Robust Optimization8 Feb 2024
- 2023Sublinear Convergence Rates of Extragradient-Type Methods: A Survey on Classical and Recent Developments30 Mar 2023
- 2023Extragradient-Type Methods with O (1/k) Last-Iterate Convergence Rates for Co-Hypomonotone Inclusions8 Feb 2023