TY - JOUR
T1 - Parallel Stochastic Newton Method
AU - Mutný , Mojmír
AU - Richtárik , Peter
JO - Journal of Computational Mathematics
VL - 3
SP - 404
EP - 425
PY - 2018
DA - 2018/06
SN - 36
DO - http://doi.org/10.4208/jcm.1708-m2017-0113
UR - https://global-sci.org/intro/article_detail/jcm/12268.html
KW - optimization, parallel methods, Newton's method, stochastic algorithms.
AB - <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>