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基于范例的无监督学习的解耦方法A Decoupled Approach to Exemplar-based Unsupervised Learning |
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| 课程网址: | http://videolectures.net/icml08_nowozin_dae/ |
| 主讲教师: | Sebastian Nowozin |
| 开课单位: | 马克斯普朗克研究所 |
| 开课时间: | 2008-08-05 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | A recent trend in exemplar based unsupervised learning is to formulate the learning problem as a convex optimization problem. Convexity is achieved by restricting the set of possible prototypes to training exemplars. In particular, this has been done for clustering, vector quantization and mixture model density estimation. In this paper we propose a novel algorithm that is theoretically and practically superior to these convex formulations. This is possible by posing the unsupervised learning problem as a single convex "master problem" with non-convex subproblems. We show that for the above learning tasks the subproblems are extremely well-behaved and can be solved efficiently. |
| 关 键 词: | 无监督学习; 凸优化; 密度估计 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-04-19：lxf |
| 阅读次数: | 83 |