Release Time:2019-03-11  Hits:

Indexed by: Journal Article

Date of Publication: 2014-03-27

Journal: International Workshop of Extreme Learning Machines (ELM)

Included Journals: Scopus、CPCI-S、EI、SCIE

Volume: 128

Page Number: 113-118

ISSN: 0925-2312

Key Words: DPFNN; ELM; L-1/2 regularizer

Abstract: A learning scheme based on Extreme Learning Machine (ELM) and Lip regularization is proposed for a double parallel feedforward neural network. ELM has been widely used as a fast learning method for feedforward networks with a single hidden layer. A key problem for ELM is the choice of the (minimum) number of the hidden nodes. To resolve this problem, we propose to combine the L-1/2 regularization method, that becomes popular in recent years in informatics, with ELM. It is shown in our experiments that the involvement of the L-1/2 regularizer in DPFNN with ELM results in less hidden nodes but equally good performance. (C) 2013 Elsevier B.V. All rights reserved.