An adaptive BYY harmony learning algorithm and its relation to rewarding and penalizing competitive learning mechanism

Author

Ma, Jinwen ; Wang, Taijun ; Xu, Lei

Author_Institution

Dept. of Inf. Sci., Peking Univ., Beijing, China

Volume

2

fYear

2002

fDate

26-30 Aug. 2002

Firstpage

1154

Abstract

Under the Bayesian Ying-Yang (BYY) learning theory, a harmony function has been developed for a BI-architecture of the BYY system related to finite mixture model and its maximization leads to the parameter learning with automated model selection. This paper proposes an adaptive gradient algorithm for the harmony function. It has been further shown by theoretical analysis that the update rule of the algorithm is a kind of rewarding and penalizing competitive learning mechanism.

Keywords

belief networks; gradient methods; optimisation; unsupervised learning; BI-architecture; BYY learning theory; Bayesian Ying-Yang learning theory; adaptive gradient algorithm; automated model selection; competitive learning mechanism; finite mixture model; harmony function; maximization; parameter learning; update rule; Algorithm design and analysis; Artificial neural networks; Bayesian methods; Clustering algorithms; Computer networks; Computer science; Information science; Laboratories; Learning systems; Statistical analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, 2002 6th International Conference on

Print_ISBN

0-7803-7488-6

Type

conf

DOI

10.1109/ICOSP.2002.1179994

Filename

1179994