图 书 馆
无监督学习Unsupervised learning |
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| 课程网址: | http://videolectures.net/ssll09_schuurmans_unle/ |
| 主讲教师: | Dale Schuurmans |
| 开课单位: | 艾伯塔大学 |
| 开课时间: | 2009-04-01 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The first part of his tutorial will discuss un-supervised, semi-supervised and partially-supervised learning. Convex relaxations will be presented for un-supervised and semi-supervised training of support vector machines, max-margin Markov networks, log-linear models and Bayesian networks. The concept of partially-supervised training will then be introduced, with convex relaxations developed for training multi-layer perceptrons and deep networks. Relationships of these methods to classical training algorithms (EM, Viterbi-EM, and self-supervised training) will be discussed. Limitations of convex relaxations will also be considered. The tutorial will then present methods for scaling up such training algorithms. Finally, some simple approximation bounds will be introduced, along with a rudimentary generalization theory for self-supervised training. |
| 关 键 词: | 计算机科学; 机器学习; 无监督学习 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-12：yumf |
| 阅读次数: | 67 |