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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
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