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The Complexity of Min-Max Optimization for Quadratic Polynomials
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An AI research paper on The Complexity of Min-Max Optimization for Quadratic Polynomials.
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Original abstract
We prove that computing approximate stationary points of min-max optimization over the hypercube is PPAD-hard for quadratic polynomials. This holds even when the polynomials are multilinear, each variable appears in at most three monomials, and the approximation factor is inverse polynomial. As a direct consequence, we obtain the first PPAD-hardness results for two-team zero-sum polymatrix games.
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