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快速欧氏最小生成树算法,分析,和应用程序

Fast Euclidean Minimum Spanning Tree: Algorithm, Analysis, and Applications
课程网址: http://videolectures.net/kdd2010_march_fem/  
主讲教师: William March
开课单位: 乔治亚理工学院
开课时间: 2010-10-01
课程语种: 英语
中文简介:
欧几里德最小生成树问题在广泛的领域中有应用,并且已经开发了许多有效的算法来解决它。我们提出了一种新的,快速的,通用的EMST算法,其动机是对天文数据的聚类和分析。大规模的天文调查,包括斯隆数字巡天,以及早期宇宙的大型模拟,如千年模拟,可以包含数百万个点并填充数TB的存储空间。传统的EMST方法以二次方式进行扩展,而更先进的方法缺乏严格的运行时保证。我们提出了一种新的双树算法,用于有效地计算EMST,使用自适应算法分析来证明迄今为止EMST问题的最紧密(也可能是最佳)运行时限,并证明了我们的方法在天文数据集上的可扩展性。
课程简介: The Euclidean Minimum Spanning Tree problem has applications in a wide range of fields, and many efficient algorithms have been developed to solve it. We present a new, fast, general EMST algorithm, motivated by the clustering and analysis of astronomical data. Large-scale astronomical surveys, including the Sloan Digital Sky Survey, and large simulations of the early universe, such as the Millennium Simulation, can contain millions of points and fill terabytes of storage. Traditional EMST methods scale quadratically, and more advanced methods lack rigorous runtime guarantees. We present a new dual-tree algorithm for efficiently computing the EMST, use adaptive algorithm analysis to prove the tightest (and possibly optimal) runtime bound for the EMST problem to-date, and demonstrate the scalability of our method on astronomical data sets.
关 键 词: 欧几里德最小生成树问题; EMST算法; 对偶树算法
课程来源: 视频讲座网
最后编审: 2020-05-21:王淑红(课程编辑志愿者)
阅读次数: 408