| 作成者 |
|
|
|
| 本文言語 |
|
| 出版者 |
|
|
|
| 発行日 |
|
| 収録物名 |
|
| 巻 |
|
| 号 |
|
| 開始ページ |
|
| 終了ページ |
|
| 出版タイプ |
|
| アクセス権 |
|
| Crossref DOI |
|
| 概要 |
Network lasso is a method for solving a multi-task learning problem through the regularized maximum likelihood method. Network lasso is characterized by setting a different model for each sample. The ...relationships among the models are represented by relational coefficients. A crucial issue in network lasso is determining appropriate values for the relational coefficients. In this paper, we propose a Bayesian approach to solve multi-task learning problems by network lasso. This approach allows us to objectively determine the relational coefficients by Bayesian estimation. The effectiveness of our proposed method is demonstrated in a simulation study and a real data analysis.続きを見る
|
Mendeley出力
