通过多视角的子空间学习跨语言文本分类Cross Language Text Classification via Multi-view Subspace Learning |
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课程网址: | http://videolectures.net/nipsworkshops2012_guo_subspace_learning/ |
主讲教师: | Yuhong Guo |
开课单位: | 天普大学 |
开课时间: | 2013-01-11 |
课程语种: | 英语 |
中文简介: | 跨语言分类是多语言学习中的一项重要任务,旨在降低每种语言的不同分类模型训练的标记成本。本文提出了一种新的跨语言文本分类子空间共正则多视图学习方法。对一组跨语言文本分类任务的实证研究表明,该方法始终优于许多归纳方法、域自适应方法和多视图学习方法。 |
课程简介: | Cross language classification is an important task in multilingual learning, aiming for reducing the labeling cost of training a different classification model for each individual language. In this paper we develop a novel subspace co-regularized multi-view learning method for cross language text classification. The empirical study on a set of cross language text classification tasks shows the proposed method consistently outperforms a number of inductive methods, domain adaptation methods, and multi-view learning methods. |
关 键 词: | 跨语言分类; 子空间; 多视图; 分类模型 |
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: | 47 |