Title :
An iterative algorithm for BYY learning on Gaussian mixture with automated model selection
Author :
Ma, Jinwen ; Wang, Taijun ; Xu, Lei
Author_Institution :
Dept. of Inf. Sci., Peking Univ., Beijing, China
Abstract :
Under the Bayesian Ying-Yang (BYY) learning theory, a harmony function has been developed for a BI-architecture of the BYY system corresponding to Gaussian mixture model and its maximization leads to the parameter learning with automated model selection. This paper proposes an iterative algorithm to implement the maximization of the harmony function. Furthermore, the iterative algorithm is demonstrated by some simulations.
Keywords :
Gaussian processes; belief networks; iterative methods; learning (artificial intelligence); optimisation; Bayesian Ying-Yang learning theory; Gaussian mixture model; harmony function; iterative algorithm; maximization; Bayesian methods; Computational efficiency; Computer science; Data analysis; Information science; Iterative algorithms; Maximum likelihood estimation; Power system modeling; Statistical analysis;
Conference_Titel :
Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
0-7803-7702-8
DOI :
10.1109/ICNNSP.2003.1279200
