A Fisher-Rao gradient flow for entropic mean-field min-max games
Abstract: Gradient flows play a substantial role in addressing many machine learning problems. We examine the convergence in continuous-time of a Fisher-Rao (Mean-Field Birth-Death) gradient flow in the context of solving convex-concave min-max games with entropy regularization. We propose appropriate Lyapunov functions to demonstrate convergence with explicit rates to the unique mixed Nash equilibrium.
Submission Length: Regular submission (no more than 12 pages of main content)
Changes Since Last Submission: Revised version incorporating the reviewers' comments.
Assigned Action Editor: ~Stephen_Becker1
Submission Number: 2723
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