Min-Max 优化 (Optimization) Requires Exponentially Many Queries
Min-Max Optimization Requires Exponentially Many Queries
作者
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Martino Bernasconi | Matteo Castiglioni | Andrea Celli | Alexandros Hollender
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2026
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-
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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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