PARALLEL STOCHASTIC NEWTON METHOD

Mojmir Mutny, Peter Richtarik

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

We propose a parallel stochastic Newton method (PSN) for minimizing unconstrained smooth convex functions. We analyze the method in the strongly convex case, and give conditions under which acceleration can be expected when compared to its serial counterpart. We show how PSN can be applied to the large quadratic function minimization in general, and empirical risk minimization problems. We demonstrate the practical efficiency of the method through numerical experiments and models of simple matrix classes.
Original languageEnglish (US)
Pages (from-to)404-425
Number of pages22
JournalJOURNAL OF COMPUTATIONAL MATHEMATICS
Volume36
Issue number3
DOIs
StatePublished - 2018

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