Abstract
In this paper we present high-speed algorithms for solving unconstrained convex optimization problem. It is shown that the algorithms based on the projection onto the graph of ε-subdifferential mapping possess superlinear rate of convergence which exceeds theoretical limit for the techniques which use first-order oracles. The results are mainly of theoretical significance but may pave the ways for the implementable methods with good practical rate of convergence.
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References
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© 1992 Springer-Verlag Berlin Heidelberg
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Nurminski, E.A. (1992). Superlinear Convergence in Convex Nondifferentiable Optimization. In: Oettli, W., Pallaschke, D. (eds) Advances in Optimization. Lecture Notes in Economics and Mathematical Systems, vol 382. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-51682-5_18
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DOI: https://doi.org/10.1007/978-3-642-51682-5_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-55446-2
Online ISBN: 978-3-642-51682-5
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