Tight Ergodic Sublinear Convergence Rate of the Relaxed Proximal Point Algorithm for Monotone Variational Inequalities

This paper considers the relaxed proximal point algorithm for solving monotone variational inequality problems, and our main contribution is the establishment of a tight ergodic sublinear convergence rate. First, the tight or exact worst-case convergence rate is computed using the performance estima...

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Veröffentlicht in:	Journal of optimization theory and applications 2024-07, Vol.202 (1), p.373-387
Hauptverfasser:	Gu, Guoyong, Yang, Junfeng
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applications of Mathematics Calculus of Variations and Optimal Control Optimization Computation Convergence Engineering Lower bounds Mathematics Mathematics and Statistics Operations Research/Decision Theory Optimization Theory of Computation Tightness
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