Multi-branch structure of layered neural networks

T. Yamashita, K. Hirasawa, Takayuki Furuzuki, J. Murata

研究成果: Conference contribution

10 被引用数 (Scopus)

抄録

In this paper, a multi-branch structure of neural networks is studied to make their size compact. The multi-branch structure has shown improved performance against conventional neural networks. As a result, it has been proved that the number of nodes of networks and the computational cost for training networks can be reduced. In addition, it could be said that proposed multi-branch networks are special cases of higher order neural networks, however, they obtain higher order effect easier without suffering the parameter explosion problem.

本文言語English
ホスト出版物のタイトルICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age
出版社Institute of Electrical and Electronics Engineers Inc.
ページ243-247
ページ数5
1
ISBN(印刷版)9810475241, 9789810475246
DOI
出版ステータスPublished - 2002
外部発表はい
イベント9th International Conference on Neural Information Processing, ICONIP 2002 - Singapore, Singapore
継続期間: 2002 11 182002 11 22

Other

Other9th International Conference on Neural Information Processing, ICONIP 2002
CountrySingapore
CitySingapore
Period02/11/1802/11/22

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

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