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Indexed by:期刊论文

Date of Publication:2014-03-27

Journal:International Workshop of Extreme Learning Machines (ELM)

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

Volume:128

Page Number:113-118

ISSN No.: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.