Global convergence rate analysis of unconstrained optimization methods based on probabilistic models

We present global convergence rates for a line-search method which is based on random first-order models and directions whose quality is ensured only with certain probability. We show that in terms of the order of the accuracy, the evaluation complexity of such a method is the same as its counterpar...

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Bibliografiska uppgifter
Huvudupphovsmän: Cartis, C, Scheinberg, K
Materialtyp: Journal article
Publicerad: Springer Berlin Heidelberg 2017

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