### 抜粋

In order to avoid overfitting in neural learning, a regularization term is added to the loss function to be minimized. It is naturMly derived from the Bayesian standpoint. The present paper studies how to determine the regularization constant from the points of view of the empirical Bayes approach, the maximum description length (MDL) approach, and the network information criterion (NIC) approach. The asymptotic statistical analysis is given to elucidate their differences. These approaches are tightly connected with the method of model selection. The superiority of the NIC is shown from this analysis.

元の言語 | English |
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ホスト出版物のタイトル | Biological and Artificial Computation |

ホスト出版物のサブタイトル | From Neuroscience to Technology - International Work-Conference on Artificial and Natural Neural Networks, IWANN 1997, Proceedings |

出版者 | Springer Verlag |

ページ | 284-293 |

ページ数 | 10 |

ISBN（印刷物） | 3540630473, 9783540630470 |

出版物ステータス | Published - 1997 1 1 |

外部発表 | Yes |

イベント | 4th International Work-Conference on Artificial and Natural Neural Networks, IWANN 1997 - Lanzarote, Canary Islands, Spain 継続期間: 1997 6 4 → 1997 6 6 |

### 出版物シリーズ

名前 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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巻 | 1240 LNCS |

ISSN（印刷物） | 0302-9743 |

ISSN（電子版） | 1611-3349 |

### Conference

Conference | 4th International Work-Conference on Artificial and Natural Neural Networks, IWANN 1997 |
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国 | Spain |

市 | Lanzarote, Canary Islands |

期間 | 97/6/4 → 97/6/6 |

### ASJC Scopus subject areas

- Theoretical Computer Science
- Computer Science(all)

## フィンガープリント Statistical analysis of regularization constant from bayes, MDL and NIC Points of view' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

## これを引用

Amari, S. I., & Murata, N. (1997). Statistical analysis of regularization constant from bayes, MDL and NIC Points of view. ：

*Biological and Artificial Computation: From Neuroscience to Technology - International Work-Conference on Artificial and Natural Neural Networks, IWANN 1997, Proceedings*(pp. 284-293). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 1240 LNCS). Springer Verlag.