English

Solving Non-Convex Non-Concave Min-Max Games Under Polyak-{\L}ojasiewicz Condition

Optimization and Control 2018-12-11 v1 Computer Science and Game Theory Machine Learning

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\varepsilon--first order stationary point of the problem in O~(ε2)\widetilde{\mathcal{O}}(\varepsilon^{-2}) iterations.

Keywords

Cite

@article{arxiv.1812.02878,
  title  = {Solving Non-Convex Non-Concave Min-Max Games Under Polyak-{\L}ojasiewicz Condition},
  author = {Maziar Sanjabi and Meisam Razaviyayn and Jason D. Lee},
  journal= {arXiv preprint arXiv:1812.02878},
  year   = {2018}
}
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