📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

Semi-Stochastic Gradient Descent Methods (2017)

First Author: Konecný J

Attributed to: Numerical Algorithms and Intelligent Software for the Evolving HPC Platform funded by EPSRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.3389/fams.2017.00009

Publication URI: http://dx.doi.org/10.3389/fams.2017.00009

Type: Journal Article/Review

Parent Publication: Frontiers in Applied Mathematics and Statistics