统计转换、热核和预期距离][Statistical Translation, Heat Kernels, and Expected Distances]

统计转换、热核和预期距离 Statistical Translation, Heat Kernels, and Expected Distances


课程网址:	http://videolectures.net/lce06_lebanon_sthke/
主讲教师:	Guy Lebanon
开课单位:	普渡大学
开课时间:	2007-02-25
课程语种:	英语
中文简介:	诸如文本和图像之类的高维结构化数据通常在统计建模中很难理解和错误表示。标准直方图表示具有高方差并且通常表现不佳。我们探索统计翻译，流形和图形上的热核以及预期距离之间的新颖联系。这些连接为文本文档的无监督度量学习提供了新的框架。实验表明，所产生的距离通常优于其更标准的对应物。
课程简介:	High dimensional structured data such as text and images is often poorly understood and misrepresented in statistical modeling. The standard histogram representation suffers from high variance and performs poorly in general. We explore novel connections between statistical translation, heat kernels on manifolds and graphs, and expected distances. These connections provide a new framework for unsupervised metric learning for text documents. Experiments indicate that the resulting distances are generally superior to their more standard counterparts.
关键词:	结构化数据; 统计建模; 无监督度量
课程来源:	视频讲座网
最后编审:	2019-05-12：lxf
阅读次数:	72

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