图 书 馆
基于直推式大型图Large-Scale Graph-based Transductive Inference |
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| 课程网址: | http://videolectures.net/nipsworkshops09_bilmes_lsgb/ |
| 主讲教师: | Jeff A. Bilmes |
| 开课单位: | 华盛顿大学 |
| 开课时间: | 2010-01-19 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We consider the issue of scalability of graph-based semi-supervised learning (SSL) algorithms. In this context, we propose a fast graph node ordering algorithm that improves parallel spatial locality by being cache cognizant. This approach allows for a linear speedup on a shared-memory parallel machine to be achievable, and thus means that graph-based SSL can scale to very large data sets. We use the above algorithm an a multi-threaded implementation to solve a SSL problem on a 120 million node graph in a reasonable amount of time. |
| 关 键 词: | 半监督学习算法; 数据集; 算法 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-02：毛岱琦(课程编辑志愿者) |
| 阅读次数: | 28 |