Improving the Performance of Neural Networks in Regression Tasks Using Drawering

Speaker(s)

Konrad Żołna

Affiliation

Uniwersytet Jagielloński

Date

April 21, 2017, 3:30 p.m.

Room

room 5820

Seminar

Research Seminar of the Logic Group: Approximate reasoning in data mining

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The method presented extends a given regression neural network to make its performance improve. The modification affects the learning procedure only, hence the extension may be easily omitted during evaluation without any change in prediction. It means that the modified model may be evaluated as quickly as the original one but tends to perform better. This improvement is possible because the modification gives better expressive power, provides better behaved gradients and works as a regularization. The knowledge gained by the temporarily extended neural network is contained in the parameters shared with the original neural network. The only cost is an increase in learning time.

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