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内核测试过程The Kernel Beta Process |
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| 课程网址: | http://videolectures.net/nips2011_carlson_kernel/ |
| 主讲教师: | David E Carlson |
| 开课单位: | 杜克大学 |
| 开课时间: | 2012-01-19 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | A new Lévy process prior is proposed for an uncountable collection of covariatedependent feature-learning measures; the model is called the kernel beta process (KBP). Available covariates are handled efficiently via the kernel construction, with covariates assumed observed with each data sample (“customer”), and latent covariates learned for each feature (“dish”). Each customer selects dishes from an infinite buffet, in a manner analogous to the beta process, with the added constraint that a customer first decides probabilistically whether to “consider” a dish, based on the distance in covariate space between the customer and dish. If a customer does consider a particular dish, that dish is then selected probabilistically as in the beta process. The beta process is recovered as a limiting case of the KBP. An efficient Gibbs sampler is developed for computations, and state-of-the-art results are presented for image processing and music analysis tasks. |
| 关 键 词: | 协变量; 潜在变异; 图像处理 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-07-26：cwx |
| 阅读次数: | 26 |