@Article{JCM-36-3,
author = {Mutný, Mojmír and Richtárik, Peter},
title = {Parallel Stochastic Newton Method},
journal = {Journal of Computational Mathematics},
year = {2018},
volume = {36},
number = {3},
pages = {404--425},
abstract = {<p style="text-align: justify;">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.</p>},
issn = {1991-7139},
doi = {https://doi.org/10.4208/jcm.1708-m2017-0113},
url = {https://global-sci.com/article/84475/parallel-stochastic-newton-method}
}