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Arxiv
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Min-Max Optimisation for Nonconvex-Nonconcave Functions Using a Random Zeroth-Order Extragradient Algorithm
- This study explores the performance of the ZO-EG scheme for min-max optimization problems with NonConvex-NonConcave (NC-NC) objective functions.
- The study considers both unconstrained and constrained, differentiable and non-differentiable settings.
- For the unconstrained problem, the ZO-EG algorithm is proven to converge to the neighborhood of an ε-stationary point of the NC-NC objective function.
- For the constrained problem, the study introduces the concept of proximal variational inequalities and provides analogous results to the unconstrained case.
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