Regional Complexity Analysis of Algorithms for Nonconvex Smooth Optimization

24 Aug 2018 Curtis Frank E. Robinson Daniel P.

A strategy is proposed for characterizing the worst-case performance of algorithms for solving nonconvex smooth optimization problems. Contemporary analyses characterize worst-case performance by providing, under certain assumptions on an objective function, an upper bound on the number of iterations (or function or derivative evaluations) required until a pth-order stationarity condition is approximately satisfied... (read more)

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