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Min-Max Optimization Over Hypercubes Proven PPAD-Hard

By PulseAugur Editorial · [2 sources] ·

Researchers have established that finding approximate stationary points for min-max optimization problems involving quadratic polynomials over a hypercube is PPAD-hard. This complexity holds even for multilinear polynomials with limited variable occurrences and inverse polynomial approximation factors. Consequently, this work presents the first PPAD-hardness results for two-team zero-sum polymatrix games. AI

RANK_REASON The cluster contains an academic paper detailing theoretical complexity results. [lever_c_demoted from research: ic=2 ai=0.4]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Alexandros Hollender ·

    The Complexity of Min-Max Optimization for Quadratic Polynomials

    arXiv:2606.17000v1 Announce Type: cross 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 …

  2. arXiv cs.LG TIER_1 English(EN) · Alexandros Hollender ·

    The Complexity of Min-Max Optimization for Quadratic Polynomials

    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…

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