Relaxation method of convolutional neural networks for natural language processing

2Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Deep learning has developed into one of the most powerful methods in the machine learning field. In particular, convolutional neural networks (CNNs) have been applied not only to image recognition tasks but also to natural language processing (NLP). To reuse older deep learning models, transfer learning techniques have been widely used in the image recognition field. However, there has been little research on transfer learning in NLP. In this paper, we propose a novel transfer learning model based on a relaxation method of CNNs for NLP. The effectiveness of the proposed method is verified using computer simulations, taking a film review score recognition task as an example.

Cite

CITATION STYLE

APA

Iwasaki, R., Hasegawa, T., Mori, N., & Matsumoto, K. (2019). Relaxation method of convolutional neural networks for natural language processing. In Advances in Intelligent Systems and Computing (Vol. 800, pp. 188–195). Springer Verlag. https://doi.org/10.1007/978-3-319-94649-8_23

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free