A sparse extreme learning machine framework by continuous optimization algorithms and its application in pattern recognition

Extreme learning machine (ELM) has demonstrated great potential in machine learning owing to its simplicity, rapidity and good generalization performance. In this investigation, based on least-squares estimate (LSE) and least absolute deviation (LAD), we propose four sparse ELM formulations with zer...

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Vydáno v:	Engineering applications of artificial intelligence Ročník 53; s. 176 - 189
Hlavní autoři:	Yang, Liming, Zhang, Siyun
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.08.2016
Témata:	Algorithms Approximation DC programming Deviation Estimates Exact penalty technique Extreme learning machine Hardness of licorice seeds Least absolute deviation Neural networks Optimization Support vector machines Zero-norm DC programming Zero-norm Extreme learning machine Hardness of licorice seeds Exact penalty technique Least absolute deviation
ISSN:	0952-1976, 1873-6769
On-line přístup:	Získat plný text
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