Neural network regularization and ensembling using multi-objective evolutionary algorithms

@article{Jin2004NeuralNR,
  title={Neural network regularization and ensembling using multi-objective evolutionary algorithms},
  author={Yaochu Jin and Tatsuya Okabe and Bernhard Sendhoff},
  journal={Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)},
  year={2004},
  volume={1},
  pages={1-8 Vol.1}
}
Regularization is an essential technique to improve generalization of neural networks. Traditionally, regularization is conducted by including an additional term in the cost function of a learning algorithm. One main drawback of these regularization techniques is that a hyperparameter that determines to which extension the regularization influences the learning algorithm must be determined beforehand. This paper addresses the neural network regularization problem from a multi-objective… CONTINUE READING
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