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Tao-Li Zheng

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Preprint Sep 2026

Optimal Deterministic First-Order Oracle Complexity for Nonconvex-Concave Minimax Optimization

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.

Si-Yu Pan, Tao-Li Zheng, Jia-Jin Li · 0 citations
Preprint Jul 2026

Last-Iterate Convergence of Single-Loop Stochastic Methods for Constrained Convex-Concave Minimax Problems

This paper establishes last-iterate convergence of stochastic first-order methods for constrained smooth convex--concave minimax optimization under the standard bounded-variance stochastic oracle and establishes two types of convergence guarantees.

Tao-Li Zheng, Jiajin Li, Anthony Man-Cho So · 1 citation · ⚡1

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