Multilayer feedforward networks are universal approximators
Neural Networks
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Ensemble and modular approaches for face detection: a comparison
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Boosting the margin: A new explanation for the effectiveness of voting methods
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
An approach to guaranteeing generalisation in neural networks
Neural Networks
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A new method to maximize the margin of MLP classifier in classification problems is described. Thismethod is based on a new cost function which minimizes the variance ofthe mean squared error. We show that with this cost function the generalizationperformance increase. This method is tested and compared with the standard mean square errorand is applied to a face detection problem.