Convergence Analysis of Stochastic Saddle Point Mirror Descent Algorithm: A Projected Dynamical Viewpoint

Saddle point problems, ubiquitous in optimization, extend beyond game theory to diverse domains like power networks and reinforcement learning. We present novel approaches to tackle saddle point problem, with a focus on continuous-time contexts. A continuous time dynamics is proposed to tackle saddl...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE transactions on automatic control S. 1 - 16
Hauptverfasser:	Paul, Anik Kumar, Mahindrakar, Arun D, Kalaimani, Rachel K
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 2025
Schlagworte:	Almost sure convergence Approximation algorithms Asymptotic stability Convergence Dynamical systems Heuristic algorithms mirror descent algorithm Mirrors Optimization projected dynamical system Signal processing algorithms Smoothing methods Vectors
ISSN:	0018-9286, 1558-2523
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!