DocumentCode :
1810345
Title :
Incremental learning using sensitivity analysis
Author :
Engelbrecht, AP ; Cloete, I.
Author_Institution :
Pretoria Univ., South Africa
Volume :
2
fYear :
1999
fDate :
36342
Firstpage :
1350
Abstract :
A new incremental learning algorithm for function approximation problems is presented where the neural network learner dynamically selects during training the most informative patterns from a candidate training set. The incremental learning algorithm uses its current knowledge about the function to be approximated, in the form of output sensitivity information, to incrementally grow the training set with patterns that have the highest influence on the learning objective
Keywords :
function approximation; learning (artificial intelligence); neural nets; sensitivity analysis; function approximation; incremental learning; neural network; output sensitivity information; sensitivity analysis; Africa; Algorithm design and analysis; Approximation algorithms; Convergence; Function approximation; Information analysis; Information technology; Neural networks; Pattern analysis; Sensitivity analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
ISSN :
1098-7576
Print_ISBN :
0-7803-5529-6
Type :
conf
DOI :
10.1109/IJCNN.1999.831159
Filename :
831159
Link To Document :
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