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arXiv · 2605.13806

Min-Max Optimization Requires Exponentially Many Queries

Martino Bernasconi·Matteo Castiglioni·Andrea Celli·Alexandros Hollender
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Abstract

We study the query complexity of min-max optimization of a nonconvex-nonconcave function $f$ over $[0,1]^d \times [0,1]^d$. We show that, given oracle access to $f$ and to its gradient $\nabla f$, any algorithm that finds an $\varepsilon$-approximate stationary point must make a number of queries that is exponential in $1/\varepsilon$ or $d$.

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BibTeXRIS

Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Alexandros Hollender. 2026-05-13. Min-Max Optimization Requires Exponentially Many Queries. https://arxiv.org/abs/2605.13806

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