图 书 馆
助推：分段函数逼近流形为全，半和非监督学习Manifold Boost: Stagewise Function Approximation for Fully-, Semi- and Un-supervised Learning |
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| 课程网址: | http://videolectures.net/icml08_loeff_mbs/ |
| 主讲教师: | Nicolas Loeff |
| 开课单位: | 伊利诺伊大学 |
| 开课时间: | 2008-08-06 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We describe a manifold learning framework that naturally accommodates supervised learning manifold learning, partially supervised learning and unsupervised clustering as particular cases. Our method chooses a function by minimizing loss subject to a manifold regularization penalty. This augmented cost is minimized using a greedy stagewise functional minimization procedure, as in Gradientboost. Each stage of boosting is fast and efficient. We demonstrate our approach using both radial basis function approximations and classification trees. The performance of our method is at the state of the art on standard problems. |
| 关 键 词: | 监督学习; 无监督聚类; 分类树; 径向基函数 |
| 课程来源: | 视频讲座网公开课 |
| 最后编审: | 2020-06-23：liqy |
| 阅读次数: | 36 |