scholarly journals Boosting Unsupervised Competitive Learning Ensembles

Author(s):  
Emilio Corchado ◽  
Bruno Baruque ◽  
Hujun Yin

1994 ◽  
Vol 6 (2) ◽  
pp. 255-269 ◽  
Author(s):  
Geoffrey J. Goodhill ◽  
Harry G. Barrow

The effect of different kinds of weight normalization on the outcome of a simple competitive learning rule is analyzed. It is shown that there are important differences in the representation formed depending on whether the constraint is enforced by dividing each weight by the same amount (“divisive enforcement”) or subtracting a fixed amount from each weight (“subtractive enforcement”). For the divisive cases weight vectors spread out over the space so as to evenly represent “typical” inputs, whereas for the subtractive cases the weight vectors tend to the axes of the space, so as to represent “extreme” inputs. The consequences of these differences are examined.



1994 ◽  
Vol 32 (6) ◽  
pp. 5-15 ◽  
Author(s):  
Suzanne Miller Hosley ◽  
Agnes T.W. Lau ◽  
Ferdinand K. Levy ◽  
Doreen S.K. Tan






PLoS ONE ◽  
2018 ◽  
Vol 13 (3) ◽  
pp. e0194096 ◽  
Author(s):  
Alfredo Corell ◽  
Luisa M. Regueras ◽  
Elena Verdú ◽  
María J. Verdú ◽  
Juan P. de Castro


Author(s):  
Jongwan Kim ◽  
Jesung Ahn ◽  
Chong Sang Kim ◽  
Heeyeung Hwang ◽  
Seongwon Cho




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