图 书 馆
公司转让中自底向上的搜索和学习Bottom-Up Search and Transfer Learning in SRL |
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| 课程网址: | http://videolectures.net/ilpmlgsrl09_mooney_bustl/ |
| 主讲教师: | Mooney Raymond J |
| 开课单位: | 德克萨斯大学 |
| 开课时间: | 2009-09-18 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | This talk addresses two important issues motivated by of our recent research in SRL. First, is the value of data-driven, "bottom-up" search in learning the structure of SRL models. Bottom-up induction has a long history in traditional ILP; however, its use in SRL has been somewhat limited. We review recent results on several structure-learning methods for Markov Logic Networks (MLNs) that highlight the value of bottom-up search. Second, is the value of transfer learning in reducing the data and computational demands of SRL. By inducing a predicate mapping between seemingly disparate domains, effective SRL models can be efficiently learned from very small amounts of in-domain training data. For example, by transferring a model learned from data about a CS department, we have induced reasonably accurate models for IMDB movie data given training data about only a single person. |
| 关 键 词: | SRL模型结构; 搜索价值; 自主学习模型 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-08：yumf |
| 阅读次数: | 39 |