83 search results - page 7 / 17 » Neural Network Learning: Testing Bounds on Sample Complexity |
MICAI
2010
Springer
2010
Springer
Combining Neural Networks Based on Dempster-Shafer Theory for Classifying Data with Imperfect Labels
13 years 5 months ago
This paper addresses the supervised learning in which the class membership of training data are subject to uncertainty. This problem is tackled in the framework of the Dempster-Sha...
IJCAI
2007
13 years 9 months ago
2007
Although necessary, learning to discover new solutions is often long and difficult, even for supposedly simple tasks such as counting. On the other hand, learning by imitation pr...
GECCO
2008
Springer
13 years 8 months ago
2008
Springer
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
TEC
2012
11 years 10 months ago
2012
Recently, the generalization framework in co-evolutionary learning has been theoretically formulated and demonstrated in the context of game-playing. Generalization performance of...
PR
2007
13 years 7 months ago
2007
In this paper, we propose a new constructive method, based on cooperative coevolution, for designing automatically the structure of a neural network for classification. Our appro...