We study the deterministic first-order oracle complexity of smooth nonconvex-concave minimax optimization over a bounded convex dual domain. Let $\ell$ denote the joint smoothness constant, $D_{\mathcal{Y}}$ the diameter of the dual domain, and $\Delta$ the initial gap. We prove that every deterministic first-order algorithm requires $\Omega(\ell^2D_{\mathcal{Y}}\Delta/\epsilon^3)$ oracle queries in the worst case to find an $\epsilon$-optimization-stationary point whenever $\epsilon\lesssim\min\{\ell D_{\mathcal{Y}},\sqrt{\ell\Delta}\}$. We then develop Tracked-FOAM, a first-order method that attains a matching upper bound, removing the logarithmic factor from previous upper bounds. Together, these results establish the optimal dependence on all problem parameters in the stated regime.
It is proved that every deterministic first-order method requires $\Omega(\ell\Delta\kappa/\epsilon^2)$ oracle queries in the worst case to find $x$ satisfying $\Phi(0)-\inf_x\Phi(x)$ and that the linear dependence on $\kappa$ is unavoidable for deterministic first-order methods.
It is proved that every deterministic first-order algorithm requires a first-order oracle that returns both the function value and the full subdifferential at every query point, and establishes the optimal deterministic oracle complexity.
Jia-Jin Li, Si-Yu Pan· 3 citations
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