Paper · arXiv
Min-Max Optimization Requires Exponentially Many Queries
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 $d$.
| Authors | Martino Bernasconi, Matteo Castiglioni, Andrea Celli et al. |
|---|---|
| Primary category | cs.DS |
| Published | 13 May 2026 |
| Last updated at source | 13 May 2026 |
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