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不确定数据下的几何计算

Geometric Computing over Uncertain Data
课程网址: http://videolectures.net/algo2012_suri_geometric_computing/  
主讲教师: Subhash Suri
开课单位: 加利福尼亚大学
开课时间: 2012-10-02
课程语种: 英语
中文简介:
凸包、Delaunay三角剖分或最小生成树(MST)等几何结构是多维数据推理的基本工具。当底层数据点只有部分确定性时,这些结构会发生什么?例如,一组已知存在一定概率的点的MST的期望成本是多少?或者,在一组不确定点中,距离最近的一对在距离L以内的概率是多少?本文探讨了数据不确定性对基本几何问题复杂性的影响。
课程简介: Geometric structures such as the convex hull, Delaunay triangulation, or minimum spanning tree (MST) are fundamental tools for reasoning about multi-dimensional data. What happens to these structures when the underlying data points are known with only partial certainty? For instance, what is the expected cost of the MST of a set of points, each known to be alive with some probability? Or, in a set of uncertain points, how likely is it that the closest pair is within distance L? This talk explores the effects of data uncertainty on the complexity of basic geometric problems.
关 键 词: 不确定数据; 几何计算; 三角剖分
课程来源: 视频讲座网
最后编审: 2021-01-30:nkq
阅读次数: 58