谱滤波学习向量场Learning Vector Fields with Spectral Filtering |
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课程网址: | http://videolectures.net/nipsworkshops09_rosasco_lvfsf/ |
主讲教师: | Lorenzo Rosasco |
开课单位: | 麻省理工学院 |
开课时间: | 2010-01-19 |
课程语种: | 英语 |
中文简介: | 我们提出了一类用于向量值学习的正则化核方法,它基于对核矩阵的谱进行滤波。所考虑的方法包括Tikhonov正则化作为一种特殊情况,以及有趣的替代方案,例如L2增强的向量值扩展。在保留Tikhonov正则化的良好统计特性的同时,一些新算法允许更快的实现,因为它们仅需要矩阵向量乘法。我们讨论了不同方法的计算复杂性,同时考虑了正则化参数选择步骤。我们的分析结果得到了数值实验的支持。 |
课程简介: | We present a class of regularized kernel methods for vector valued learning, which are based on filtering the spectrum of the kernel matrix. The considered methods include Tikhonov regularization as a special case, as well as interesting alternatives such as vector valued extensions of L2 boosting. While preserving the good statistical properties of Tikhonov regularization, some of the new algorithms allows for a much faster implementation since they require only matrix vector multiplications. We discuss the computational complexity of the different methods, taking into account the regularization parameter choice step. The results of our analysis are supported by numerical experiments. |
关 键 词: | 向量值学习; 正则化核方法; 核矩阵 |
课程来源: | 视频讲座网 |
最后编审: | 2019-09-07:lxf |
阅读次数: | 76 |