Selective dropout for deep neural networks.
(2016)
Presentation / Conference Contribution
BARROW, E., EASTWOOD, M. and JAYNE, C. 2016. Selective dropout for deep neural networks. In Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M. and Liu, D. (eds.) Neural information processing: Proceedings of the 23rd International conference on neural information processing (ICONIP 2016), 16-21 October 2016, Kyoto, Japan. Lecture notes in computer science, 9949. Cham: Springer [online], pages 519-528. Available from: https://doi.org/10.1007/978-3-319-46675-0_57
Dropout has been proven to be an effective method for reducing overfitting in deep artificial neural networks. We present 3 new alternative methods for performing dropout on a deep neural network which improves the effectiveness of the dropout method... Read More about Selective dropout for deep neural networks..