Abstract
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 language | English |
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Title of host publication | ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 243-247 |
Number of pages | 5 |
Volume | 1 |
ISBN (Print) | 9810475241, 9789810475246 |
DOIs | |
Publication status | Published - 2002 |
Externally published | Yes |
Event | 9th International Conference on Neural Information Processing, ICONIP 2002 - Singapore, Singapore Duration: 2002 Nov 18 → 2002 Nov 22 |
Other
Other | 9th International Conference on Neural Information Processing, ICONIP 2002 |
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Country/Territory | Singapore |
City | Singapore |
Period | 02/11/18 → 02/11/22 |
ASJC Scopus subject areas
- Computer Networks and Communications
- Information Systems
- Signal Processing