Multi-level neural networks

Chulhee Lee, Jinwook Go

Research output: Contribution to conferencePaper

Abstract

One of the challenges the neural network faces today is that the network lacks memory capability. Typically, it is a very time-consuming process to train a neural network for a given problem. However, when a new problem is presented, the neural network has to go through the learning process again without any benefit from the previous learning process. In order to address this problem, we propose a new architecture of neural networks that have the capability to remember past experiences and utilize them to solve a new problem faster and more efficiently. The proposed neural network consists of a primary neural network and a number of control neural networks. Preliminary experiments provide some promising results.

Original languageEnglish
Pages1150-1153
Number of pages4
Publication statusPublished - 1999 Dec 1
EventInternational Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA
Duration: 1999 Jul 101999 Jul 16

Other

OtherInternational Joint Conference on Neural Networks (IJCNN'99)
CityWashington, DC, USA
Period99/7/1099/7/16

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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  • Cite this

    Lee, C., & Go, J. (1999). Multi-level neural networks. 1150-1153. Paper presented at International Joint Conference on Neural Networks (IJCNN'99), Washington, DC, USA, .