Relaxation Method of Convolutional Neural Networks for Natural Language Processing

2019
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Authors: Ryo Iwasaki; Taku Hasegawa; Naoki Mori; Keinosuke Matsumoto
Published in: Distributed Computing and Artificial Intelligence, 15th International Conference
Publisher: Springer International Publishing

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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.

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Title: Relaxation Method of Convolutional Neural Networks for Natural Language Processing
Authors: Ryo Iwasaki
Taku Hasegawa
Naoki Mori
Keinosuke Matsumoto
Publisher: Springer International Publishing
Book: Distributed Computing and Artificial Intelligence, 15th International Conference
Print ISBN: 978-3-319-94648-1

Electronic ISBN: 978-3-319-94649-8

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-319-94649-8_23

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