Kernel-Based Multilayer Extreme Learning Machines for Representation Learning

Recently, multilayer extreme learning machine (ML-ELM) was applied to stacked autoencoder (SAE) for representation learning. In contrast to traditional SAE, the training time of ML-ELM is significantly reduced from hours to seconds with high accuracy. However, ML-ELM suffers from several drawbacks:...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems Jg. 29; H. 3; S. 757 - 762
Hauptverfasser:	Wong, Chi Man, Vong, Chi Man, Wong, Pak Kin, Cao, Jiuwen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.03.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Benchmark testing Benchmarks Datasets Kernel Kernel learning Learning Learning algorithms Learning systems Manuals multilayer extreme learning machine (ML-ELM) Neural networks Nonhomogeneous media Reconstruction representation learning Representations stacked autoencoder (SAE) Training Tuning
ISSN:	2162-237X, 2162-2388
Online-Zugang:	Volltext
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