Multi-branch structure of layered neural networks

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Print)9810475241, 9789810475246
Publication statusPublished - 2002
Externally publishedYes
Event9th International Conference on Neural Information Processing, ICONIP 2002 - Singapore, Singapore
Duration: 2002 Nov 182002 Nov 22


Other9th International Conference on Neural Information Processing, ICONIP 2002

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing


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