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Dropout vs. batch normalization: an empirical study of their impact to deep learning

Published Online: 2020-01-22

Published Print: 2020-05

Authors

Garbin, Christian

Zhu, Xingquan https://orcid.org/0000-0003-4129-9611
Marques, Oge
Funding

Funding for this research was provided by:

National Science Foundation (IIS-1763452)

National Science Foundation (CNS-1828181)
License Information

Text and Data Mining valid from 2020-01-22

Version of Record valid from 2020-01-22
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Article History

Received: 26 April 2019

Revised: 3 September 2019

Accepted: 7 November 2019

First Online: 22 January 2020

Document is current