图 书 馆
结构化和非一致输出的多视图学习Multi-View Learning over Structured and Non-Identical Outputs |
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| 课程网址: | http://videolectures.net/uai08_ganchev_mvl/ |
| 主讲教师: | Kuzman Ganchev |
| 开课单位: | 宾夕法尼亚大学 |
| 开课时间: | 2008-07-11 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In many machine learning problems, labeled training data is limited but unlabeled data is ample. Some of these problems have instances that can be factored into multiple views, each of which is nearly sufficient in determining the correct labels. In this paper we present a new algorithm for probabilistic multi-view learning which uses the idea of stochastic agreement between views as regularization. Our algorithm works on structured and unstructured problems and easily generalizes to partial agreement scenarios. For the full agreement case, our algorithm minimizes the Bhattacharyya distance between the models of each view, and performs better than CoBoosting and two-view Perceptron on several flat and structured classification problems. |
| 关 键 词: | 计算机科学; 算法; 机器学习 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-11-17：cwx |
| 阅读次数: | 65 |