TY - GEN
T1 - Popov Mirror-Prox for solving Variational Inequalities
AU - Chakraborty, Abhishek
AU - Nedic, Angelia
N1 - Publisher Copyright: © 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - We consider the mirror-prox algorithm for solving monotone Variational Inequality (VI) problems. As the mirrorprox algorithm is not practically implementable, except in special instances of VIs (such as affine VIs), we consider its implementation with Popov method updates. We provide convergence rate analysis of our proposed method for a monotone VI with a Lipschitz continuous mapping. We establish a convergence rate of O(1 / t), in terms of the number t of iterations, for the dual gap function. Simulations on a two player matrix game corroborate our findings.
AB - We consider the mirror-prox algorithm for solving monotone Variational Inequality (VI) problems. As the mirrorprox algorithm is not practically implementable, except in special instances of VIs (such as affine VIs), we consider its implementation with Popov method updates. We provide convergence rate analysis of our proposed method for a monotone VI with a Lipschitz continuous mapping. We establish a convergence rate of O(1 / t), in terms of the number t of iterations, for the dual gap function. Simulations on a two player matrix game corroborate our findings.
UR - https://www.scopus.com/pages/publications/86000618911
UR - https://www.scopus.com/pages/publications/86000618911#tab=citedBy
U2 - 10.1109/CDC56724.2024.10886701
DO - 10.1109/CDC56724.2024.10886701
M3 - Conference contribution
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 6963
EP - 6968
BT - 2024 IEEE 63rd Conference on Decision and Control, CDC 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 63rd IEEE Conference on Decision and Control, CDC 2024
Y2 - 16 December 2024 through 19 December 2024
ER -