图 书 馆
马尔可夫逻辑网络的在线结构学习Online Structure Learning for Markov Logic Networks |
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| 课程网址: | http://videolectures.net/ecmlpkdd2011_mooney_networks/ |
| 主讲教师: | Raymond J. Mooney |
| 开课单位: | 德克萨斯大学 |
| 开课时间: | 2011-11-29 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Most existing learning methods for Markov Logic Networks (MLNs) use batch training, which becomes computationally expensive and eventually infeasible for large datasets with thousands of training examples which may not even all fit in main memory. To address this issue, previous work has used online learning to train MLNs. However, they all assume that the model's structure (set of logical clauses) is given, and only learn the model's parameters. However, the input structure is usually incomplete, so it should also be updated. In this work, we present OSL--the first algorithm that performs both online structure and parameter learning for MLNs. Experimental results on two realworld datasets for natural-language field segmentation show that OSL outperforms systems that cannot revise structure. |
| 关 键 词: | 马尔可夫的流程; 计算机科学; 机器学习; 在线学习 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-08：yumf |
| 阅读次数: | 60 |