Denoising Laplacian multi-layer extreme learning machine | |
Zhang, Nan1,3; Ding, Shifei1,2,3; Shi, Zhongzhi2 | |
刊名 | NEUROCOMPUTING
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2016 | |
卷号 | 171页码:1066-1074 |
关键词 | Extreme learning machine Semi-supervised learning Deep learning Denoising Manifold regularization |
ISSN号 | 0925-2312 |
DOI | 10.1016/j.neucom.2015.07.058 |
英文摘要 | Most of semi-supervised learning algorithms based on manifold regularization framework are surface learning algorithms, such as semi-supervised ELM (SS-ELM) and Laplacian smooth twin support vector machine (Lap-STSVM). Multi-layer extreme learning machine (ML-ELM) stacks extreme learning machine based auto encoder (ELM-AE) to create a multi-layer neural network. ML-ELM not only approximates the complicated function but also achieves fast training time. The outputs of ELM-AE are the same as inputs, which cannot guarantee the effectiveness of the learning feature representations. We put forward extreme learning machine based denoising auto encoder (ELM-DAE) which introduces local denoising criterion into ELM-AE and is used as the basic component for Denoising ML-ELM. Resembling ML-ELM, Denoising ML-ELM stacks ELM-DAE to create a deep network. And then we introduce manifold regularization into the model of Denoising ML-ELM and propose denoising Laplacian ML-ELM (Denoising Lap-ML-ELM). Denoising Lap-ML-ELM is more efficient than SS-ELM in classification and does not need to spend too much time. Experimental results show that Denoising ML-ELM and Denoising Lap-ML-ELM are effective learning algorithms. (C) 2015 Elsevier B.V. All rights reserved. |
资助项目 | National Natural Science Foundation of China[61379101] ; National Key Basic Research Program of China[2013CB329502] |
WOS研究方向 | Computer Science |
语种 | 英语 |
出版者 | ELSEVIER SCIENCE BV |
WOS记录号 | WOS:000364883900105 |
内容类型 | 期刊论文 |
源URL | [http://119.78.100.204/handle/2XEOYT63/9188] ![]() |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Ding, Shifei |
作者单位 | 1.China Univ Min & Technol, Jiangsu Key Lab Mine Mech & Elect Equipment, Xuzhou 221116, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 3.China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 221116, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang, Nan,Ding, Shifei,Shi, Zhongzhi. Denoising Laplacian multi-layer extreme learning machine[J]. NEUROCOMPUTING,2016,171:1066-1074. |
APA | Zhang, Nan,Ding, Shifei,&Shi, Zhongzhi.(2016).Denoising Laplacian multi-layer extreme learning machine.NEUROCOMPUTING,171,1066-1074. |
MLA | Zhang, Nan,et al."Denoising Laplacian multi-layer extreme learning machine".NEUROCOMPUTING 171(2016):1066-1074. |
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