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A Fixed-Point of View on Gradient Methods for Big Data

Year of publication

2017

Authors

Jung, Alexander

Organizations and authors

Aalto University

Jung Alex

Publication type

Publication format

Article

Parent publication type

Journal

Article type

Original article

Audience

Scientific

Peer-reviewed

Peer-Reviewed

MINEDU's publication type classification code

A1 Journal article (refereed), original research

Publication channel information

Journal

Frontiers in Applied Mathematics and Statistics

Publisher

Frontiers Research Foundation

Volume

3

Pages

1-11

ISSN

Publication forum

Publication forum level

1

Open access

Open access in the publisher’s service

Yes

Open access of publication channel

Fully open publication channel

Self-archived

Yes

Other information

Fields of science

Computer and information sciences

Keywords

Big data; contraction mapping; Convex optimization; fixed point theory; gradient descent; heavy balls; Machine learning

Internationality of the publisher

International

Language

English

International co-publication

No

Co-publication with a company

No

DOI

10.3389/fams.2017.00018

The publication is included in the Ministry of Education and Culture’s Publication data collection

Yes