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	An adaptive gradient BYY learning rule for Poisson mixture with automated model selection
	Liu, Jianfeng ; Ma, Jinwen
	2007
关键词	GAUSSIAN MIXTURE ALGORITHM
英文摘要	From the Bayesian Ying-Yang (BYY) harmony learning theory, a harmony function has been developed for finite mixtures with a favorite property that its maximization can make model selection automatically during parameters learning. In this paper, we propose an adaptive gradient learning rule for maximizing the harmony function on Poisson mixtures which are applied more and more extensively in practice, especially for overdispersed data. It is demonstrated by simulation experiments that this adaptive gradient learning rule can determine the number of Poisson distributions during the parameters learning on a sample data set.; Computer Science, Artificial Intelligence; Computer Science, Interdisciplinary Applications; Computer Science, Theory & Methods; EI; CPCI-S(ISTP); 0
语种	英语
出处	EI ; SCI
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/406444]
专题	数学科学学院
推荐引用方式 GB/T 7714	Liu, Jianfeng,Ma, Jinwen. An adaptive gradient BYY learning rule for Poisson mixture with automated model selection. 2007-01-01.

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