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A Note on Nonconvex Minimax Theorem with Separable Homogeneous Polynomials

机译:具有可分齐次多项式的非凸Minimax定理的一个注记。

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摘要

The minimax theorem for a convex-concave bifunction is a fundamental theorem in optimization and convex analysis, and has a lot of applications in economics. In the last two decades, a nonconvex extension of this minimax theorem has been well studied under various generalized convexity assumptions. In this note, by exploiting the hidden convexity (joint range convexity) of separable homogeneous polynomials, we establish a nonconvex minimax theorem involving separable homogeneous polynomials. Our result complements the existing study of nonconvex minimax theorem by obtaining easily verifiable conditions for the nonconvex minimax theorem to hold.
机译:凸凹双函数的极小极大定理是优化和凸分析的基本定理,在经济学中有许多应用。在最近的二十年中,在各种广义凸假设下,已经很好地研究了该极小极大定理的非凸扩展。在本说明中,通过利用可分离的齐次多项式的隐藏凸度(关节范围凸度),我们建立了包含可分离的齐次多项式的非凸极小极大定理。我们的结果通过获得易于证明的非凸最小极大定理成立的条件,补充了非凸最小极大定理的现有研究。

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