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用Winnow学习预测后缀树

Learning Prediction Suffix Trees with Winnow
课程网址: http://videolectures.net/icml09_karampatziakis_lpst/  
主讲教师: Nikos Karampatziakis
开课单位: 康奈尔大学
开课时间: 2009-08-26
课程语种: 英语
中文简介:
预测后缀树(PST)是用于建模序列的流行工具,并已成功应用于许多领域,例如压缩和语言建模。在这项工作中,我们将经过充分研究的Winnow算法应用于学习PST的任务。所提出的算法自动增长了树,因此它可以证明与事后确定的任何固定PST保持竞争。同时,我们证明了树的深度只与算法所犯的错误数呈对数增长。最后,我们凭经验证明了它在两个不同任务中的有效性。
课程简介: Prediction suffix trees (PSTs) are a popular tool for modeling sequences and have been successfully applied in many domains such as compression and language modeling. In this work we adapt the well studied Winnow algorithm to the task of learning PSTs. The proposed algorithm automatically grows the tree, so that it provably remains competitive with any fixed PST determined in hindsight. At the same time we prove that the depth of the tree grows only logarithmically with the number of mistakes made by the algorithm. Finally, we empirically demonstrate its effectiveness in two different tasks.
关 键 词: 预测后缀树; 压缩; Winnow算法
课程来源: 视频讲座网
最后编审: 2019-04-23:lxf
阅读次数: 36