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ICML
2010
IEEE

Finding Planted Partitions in Nearly Linear Time using Arrested Spectral Clustering

8 years 4 months ago
Finding Planted Partitions in Nearly Linear Time using Arrested Spectral Clustering
We describe an algorithm for clustering using a similarity graph. The algorithm (a) runs in O(n log3 n + m log n) time on graphs with n vertices and m edges, and (b) with high probability, finds all "large enough" clusters in a random graph generated according to the planted partition model. We provide lower bounds that imply that our "large enough" constraint cannot be improved much, even using a computationally unbounded algorithm. We describe some experiments running the algorithm and a few related algorithms on random graphs with partitions generated using a Chinese Restaurant Processes, and some results of applying the algorithm to cluster DBLP titles.
Nader H. Bshouty, Philip M. Long
Added 09 Nov 2010
Updated 09 Nov 2010
Type Conference
Year 2010
Where ICML
Authors Nader H. Bshouty, Philip M. Long
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