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Robust Learning Algorithm Based on Iterative Least Median of Squares
2012
Neural Processing Letters
Outliers and gross errors in training data sets can seriously deteriorate the performance of traditional supervised feedforward neural networks learning algorithms. This is why several learning methods, to some extent robust to outliers, have been proposed. In this paper we present a new robust learning algorithm based on the iterative Least Median of Squares, that outperforms some existing solutions in its accuracy or speed. We demonstrate how to minimise new non-differentiable performance
doi:10.1007/s11063-012-9227-z
fatcat:ynxqinc7rbbgxcyayjvr5fhnc4