An EM algorithm for learning sparse and overcomplete representations

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	An EM algorithm for learning sparse and overcomplete representations
	Zhong, MJ ; Tang, HW ; Chen, HJ ; Tang, YY
摘要	An expectation-maximization (EM) algorithm for learning sparse and overcomplete representations is presented in this paper. We show that the estimation of the conditional moments of the posterior distribution can be accomplished by maximum a posteriori estimation. The approximate conditional moments,enable the development of an EM algorithm for learning the overcomplete basis vectors and inferring the most probable basis coefficients. (C) 2003 Elsevier B.V. All rights reserved.
关键词	overcomplete representations EM algorithm maximum a posteriori
	2004-03-01
语种	英语
发表期刊	NEUROCOMPUTING
ISSN	0925-2312
卷号	57 页码:469-476
期刊论文类型	Article
收录类别	SCI
WOS记录号	WOS:000220670700027
引用统计	被引频次：10[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.psych.ac.cn/handle/311026/14017
专题	中国科学院心理研究所回溯数据库(1956-2010)
作者单位	1.Dalian Univ Technol, Inst Neuroinformat, Dept Foreign Languages, Dalian 116023, Peoples R China 2.Dalian Univ Technol, Inst Computat Biol & Bioinformat, Dalian 116023, Peoples R China 3.Chinese Acad Sci, Lab Visual Informat Proc, Beijing 100101, Peoples R China 4.Chinese Acad Sci, Key Lab Mental Hlth, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Zhong, MJ,Tang, HW,Chen, HJ,et al. An EM algorithm for learning sparse and overcomplete representations[J]. NEUROCOMPUTING,2004,57:469-476.
APA	Zhong, MJ,Tang, HW,Chen, HJ,&Tang, YY.(2004).An EM algorithm for learning sparse and overcomplete representations.NEUROCOMPUTING,57,469-476.
MLA	Zhong, MJ,et al."An EM algorithm for learning sparse and overcomplete representations".NEUROCOMPUTING 57(2004):469-476.