Learning apparatus, learning program, and learning method
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United States of America Patent
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Jul 16, 2019
Grant Date -
May 14, 2015
app pub date -
Nov 13, 2014
filing date -
Nov 14, 2013
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Abstract
A learning apparatus performs a learning process for a feed-forward multilayer neural network with supervised learning. The network includes an input layer, an output layer, and at least one hidden layer having at least one probing neuron that does not transfer an output to an uppermost layer side of the network. The learning apparatus includes a learning unit and a layer quantity adjusting unit. The learning unit performs a learning process by calculation of a cost derived by a cost function defined in the multilayer neural network using a training data set for supervised learning. The layer quantity adjusting unit removes at least one uppermost layer from the network based on the cost derived by the output from the probing neuron, and sets, as the output layer, the probing neuron in the uppermost layer of the remaining layers.
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