Minimisation of Polyak-\L{}ojasewicz Functions Using Random Zeroth-Order Oracles

Farzin, Amir Ali, Shames, Iman

arXiv.org Artificial Intelligence 

The application of a zeroth-order scheme for minimising Polyak-\L{}ojasewicz (PL) functions is considered. The framework is based on exploiting a random oracle to estimate the function gradient. The convergence of the algorithm to a global minimum in the unconstrained case and to a neighbourhood of the global minimum in the constrained case along with their corresponding complexity bounds are presented. The theoretical results are demonstrated via numerical examples.

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