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A New Sparse Learning Machine
Year: 2016
Abstract:
Many algorithms have been proposed so far for pruning and sparse approximation of feedforward neural networks with random weights in order to obtain compact networks which are fast and robust on various datasets. One ...
Universal Approximation by Using the Correntropy Objective Function
Year: 2017
Abstract:
Several objective functions have been proposed in the
literature to adjust the input parameters of a node in constructive
networks. Furthermore, many researchers have focused on the universal
approximation ...