现代大数据的现代非参数统计Modern Nonparametric Statistics on Modern Big Data |
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课程网址: | http://videolectures.net/nipsworkshops2012_gray_statistics/ |
主讲教师: | Alexander Gray |
开课单位: | 乔治亚理工学院 |
开课时间: | 2013-01-16 |
课程语种: | 英语 |
中文简介: | 现代数据在对象数量和维度数量方面都在增长。虽然在统计意义上,大量数据使得非参数方法完全合适,但是它们的计算成本使得从业者通常认为在这种情况下它们是不可能的。我将回顾一些非参数方法的常见概念类,包括经典和现代变体,然后回顾最近的算法进展,这可以使非参数方法易于处理 |
课程简介: | Modern data is increasing very large in terms of both the number of objects and the number of dimensions. While in a statistical sense massive amounts of data make nonparametric methods entirely appropriate, their computational cost has made practitioners typically conclude that they are not possible in such scenarios. I will review a few common conceptual classes of nonparametric methods, including both classical and modern variants, then review recent algorithmic advances which can make nonparametric methods tractable |
关 键 词: | 非参数方法; 计算成本; 现代数据 |
课程来源: | 视频讲座网 |
最后编审: | 2019-09-08:lxf |
阅读次数: | 49 |