WEKO3
インデックスリンク
アイテム
An adaptive penalty-based learning extension for backpropagation and its variants
http://hdl.handle.net/2297/18164
http://hdl.handle.net/2297/181644347460f-8669-4f36-a972-b5371e272d7d
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
TE-PR-NAKAYAMA-K-6427.pdf (191.9 kB)
|
|
| Item type | 会議発表論文 / Conference Paper(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2017-10-03 | |||||
| タイトル | ||||||
| タイトル | An adaptive penalty-based learning extension for backpropagation and its variants | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||
| 資源タイプ | conference paper | |||||
| 著者 |
Boris, Jansen
× Boris, Jansen× Nakayama, Kenji |
|||||
| 提供者所属 | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | 金沢大学理工研究域 電子情報学系 | |||||
| 書誌情報 |
IEEE International Conference on Neural Networks - Conference Proceedings p. 6427-6432, 発行日 2006-07-01 |
|||||
| 出版者 | ||||||
| 出版者 | IEEE = Institute of Electrical and Electronics Engineers | |||||
| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | Over the years, many improvements and refinements of the backpropagation learning algorithm have been reported. In this paper, a new adaptive penalty-based learning extension for the backpropagation learning algorithm and its variants is proposed. The new method initially puts pressure on artificial neural networks in order to get all outputs for all training patterns into the correct half of the output range, instead of mainly focusing on minimizing the difference between the target and actual output values. The technique is easy to implement and computationally inexpensive. In this study, the new approach has been applied to the backpropagation learning algorithm as well as the RPROP learning algorithm and simulations have been performed. The superiority of the new proposed method is demonstrated. By applying the extension, the number of successful runs can be greatly increased and the average number of epochs to convergence can be well reduced on various problem instances. Furthermore, the change of the penalty values during training has been studied and its observation shows the active role the penalties play within the learning process. © 2006 IEEE. | |||||
| 著者版フラグ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
| シリーズ | ||||||
| 関連名称 | 1716563 | |||||
