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Tight Lower Bounds for Stochastic Nonconvex-Strongly-Concave Minimax Optimization
We study the stochastic first-order oracle complexity of finding $ε$-stationary points of the primal function in smooth nonconvex-strongly-concave minimax optimization. For sufficiently small $ε$, we establish lower bounds of $Ω(κLΔσ^2ε^{-4})$ under the bounded-variance assumption and $Ω(κ^{3/2}\bar
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