Improved upper bound of Õ(ε^{-4/(3p+1)}) p-th order oracle complexity for convex-concave minimax problems via Monteiro-Svaiter acceleration, with matching lower bound Ω(ε^{-2/(3p-1)}).
The extragradient method for finding saddle points and other problems.Matecon, 12:747–756
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Negative momentum enables global convergence in convex-concave min-max optimization and accelerated rates in the strongly-convex-strongly-concave setting.
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Solving Convex-Concave Problems with $\tilde{\mathcal{O}}(\epsilon^{-4/(3p+1)})$ $p$th-Order Oracle Complexity
Improved upper bound of Õ(ε^{-4/(3p+1)}) p-th order oracle complexity for convex-concave minimax problems via Monteiro-Svaiter acceleration, with matching lower bound Ω(ε^{-2/(3p-1)}).
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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.