Negative momentum enables global convergence in convex-concave min-max optimization and accelerated rates in the strongly-convex-strongly-concave setting.
A unified analysis of first-order methods for smooth games via integral quadratic constraints.Journal of Machine Learning Research, 22(103):1–39, 2021
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Negative Momentum for Convex-Concave Optimization
Negative momentum enables global convergence in convex-concave min-max optimization and accelerated rates in the strongly-convex-strongly-concave setting.