Effect of initial values in simple perception

Author

Raudys, Sarunas ; Amari, Shun-Ichi

Author_Institution

Inst. of Math. & Inf., Vilnius Univ., Lithuania

Volume

2

fYear

1998

fDate

4-9 May 1998

Firstpage

1530

Abstract

The initial value of the network weight vector can contain a large amount of information. One of the possibilities to use this information is to utilise a weighted combination of initial and final values of the weights. An alternative is the early stopping. To utilise an information contained in the initial weight vector Wˆ₀ one needs to know the accuracy of determination of Wˆ₀ and Wˆ ₁, a final weight. The analytical expression of an optimal weighting factor greatly depends on the parameter estimation schema as well as on the learning-set size. Utilisation of the additional validation-set is a universal method

Keywords

feedforward neural nets; initial value problems; learning (artificial intelligence); maximum likelihood estimation; statistical analysis; feedforward neural nets; initial value; initial weight vector; learning-set; maximum likelihood method; optimal weighting factor; parameter estimation; universal method; weight initialisation; Costs; Covariance matrix; Gaussian distribution; Gaussian noise; Maximum likelihood estimation; Parameter estimation; Predictive models; Statistical analysis; Statistics; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on

Conference_Location

Anchorage, AK

ISSN

1098-7576

Print_ISBN

0-7803-4859-1

Type

conf

DOI

10.1109/IJCNN.1998.686004

Filename

686004