DocumentCode
324545
Title
Learning with Lotto-type competition
Author
Luk, Andrew ; Lien, Sandra
Author_Institution
St. B&P Neural Investments Pty. Ltd., Wesleigh, NSW, Australia
Volume
2
fYear
1998
fDate
4-9 May 1998
Firstpage
1143
Abstract
Classical winner-takes-all competitive learning can be modified such that not only the winner is rewarded but also all the losers are penalised. The idea is similar to a simplified Lotto system where all losers are divested of their bets. Experimental results indicate that convergence occurs only if parameters are suitably set
Keywords
convergence; neural nets; unsupervised learning; Lotto-type competition; competitive learning; convergence; neural networks; winner-takes-all learning; Algorithm design and analysis; Australia; Cameras; Clustering algorithms; Convergence; Investments; TV; Time series analysis;
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.1998.685933
Filename
685933
Link To Document