图 书 馆
基于多特征表示或内核的监督和局部降维Supervised and Localized Dimensionality Reduction from Multiple Feature Representations or Kernels |
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| 课程网址: | http://videolectures.net/nipsworkshops2010_alpaydin_sld/ |
| 主讲教师: | Ethem Alpaydin |
| 开课单位: | 博阿齐奇大学 |
| 开课时间: | 2011-01-12 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We propose a supervised and localized dimensionality reduction method that combines multiple feature representations or kernels. Each feature representation or kernel is used where it is suitable through a parametric gating model in a supervised manner for efficient dimensionality reduction and classification, and local projection matrices are learned for each feature representation or kernel. The kernel machine parameters, the local projection matrices, and the gating model parameters are optimized using an alternating optimization procedure composed of kernel machine training and gradient-descent updates. Empirical results on benchmark data sets validate the method in terms of classification accuracy, smoothness of the solution, and ease of visualization. |
| 关 键 词: | 局部降维; 内核; 局部投影矩阵 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-09-07：lxf |
| 阅读次数: | 37 |