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Sharp Fresh-Gradient Complexity of Nonconvex-Strongly-Concave Minimax Optimization
We characterize the fresh-gradient oracle complexity of smooth nonconvex-strongly-concave minimax optimization, with matching upper and lower bounds up to logarithmic factors. Let $Φ(x)=\max_y f(x,y)$, where $f$ is jointly $L$-smooth and $μ$-strongly concave in $y$ on unconstrained Euclidean domains
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