Supervised learning with artificial selection

Masafumi Hagiwara, Masao Nakagawa

研究成果: Paper査読

4 被引用数 (Scopus)

抄録

Summary form only given, as follows. Supervised learning with artificial selection is proposed as a way to escape from local minima. The concept of artificial selection is reasonable for nature. In the authors' method, the 'worst' hidden unit is detected, and then all the weights connected to the detected hidden unit are reset to small random values. According to simulations, only half the trials using conventional backpropagation converge, whereas all of the trials using the proposed method converge, and quickly do so.

本文言語English
ページ数1
出版ステータスPublished - 1989 12 1
イベントIJCNN International Joint Conference on Neural Networks - Washington, DC, USA
継続期間: 1989 6 181989 6 22

Other

OtherIJCNN International Joint Conference on Neural Networks
CityWashington, DC, USA
Period89/6/1889/6/22

ASJC Scopus subject areas

  • 工学(全般)

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