DocumentCode
303232
Title
The probability distribution of parameters learned with the EM algorithm
Author
Ikeda, Kazushi ; Xu, Lei
Author_Institution
Dept. of Electr. & Comput. Eng., Kanazawa Univ., Japan
Volume
1
fYear
1996
fDate
3-6 Jun 1996
Firstpage
306
Abstract
Recently, the expectation maximisation (EM) algorithm has been applied to a lot of problems of estimating parameters and learning and there are some theoretical analyses, however, prediction error is not mentioned yet. We are trying to evaluate the learning error when a machine learns with the EM algorithm and the probability distribution of the estimated parameters is mentioned here as the first step for the learning curve
Keywords
learning (artificial intelligence); neural nets; optimisation; parameter estimation; probability; EM algorithm; expectation maximisation algorithm; learning; neural networks; parameter estimation; prediction error; probability distribution; Algorithm design and analysis; Error analysis; Machine learning; Machine learning algorithms; Manifolds; Maximum likelihood estimation; Neural networks; Parameter estimation; Probability distribution; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1996., IEEE International Conference on
Conference_Location
Washington, DC
Print_ISBN
0-7803-3210-5
Type
conf
DOI
10.1109/ICNN.1996.548909
Filename
548909
Link To Document