ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1812.02878
6
35

Solving Non-Convex Non-Concave Min-Max Games Under Polyak-Łojasiewicz Condition

7 December 2018
Maziar Sanjabi
Meisam Razaviyayn
J. Lee
ArXivPDFHTML
Abstract

In this short note, we consider the problem of solving a min-max zero-sum game. This problem has been extensively studied in the convex-concave regime where the global solution can be computed efficiently. Recently, there have also been developments for finding the first order stationary points of the game when one of the player's objective is concave or (weakly) concave. This work focuses on the non-convex non-concave regime where the objective of one of the players satisfies Polyak-{\L}ojasiewicz (PL) Condition. For such a game, we show that a simple multi-step gradient descent-ascent algorithm finds an ε\varepsilonε--first order stationary point of the problem in O~(ε−2)\widetilde{\mathcal{O}}(\varepsilon^{-2})O(ε−2) iterations.

View on arXiv
Comments on this paper