Sampling-Based Gradient Regularization for Capturing Long-Term Dependencies in Recurrent Neural Networks

Artem N. Chernodub, Dimitri Nowicki. Sampling-Based Gradient Regularization for Capturing Long-Term Dependencies in Recurrent Neural Networks. In Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu, editors, Neural Information Processing - 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16-21, 2016, Proceedings, Part II. Volume 9948 of Lecture Notes in Computer Science, pages 90-97, 2016. [doi]

Abstract

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