118 search results - page 5 / 24 » Fast Algorithms for Constant Approximation k-Means Clusterin... |
SDM
2009
SIAM
15 years 6 months ago
2009
SIAM
In this paper, we propose GAD (General Activity Detection) for fast clustering on large scale data. Within this framework we design a set of algorithms for different scenarios: (...
SBBD
2000
14 years 10 months ago
2000
Dimensionalitycurse and dimensionalityreduction are two issues that have retained highinterest for data mining, machine learning, multimedia indexing, and clustering. We present a...
EDBT
2004
ACM
15 years 9 months ago
2004
ACM
We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property...
190
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SDM
2011
SIAM
14 years 9 days ago
2011
SIAM
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
107
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CATS
2006
14 years 11 months ago
2006
We consider the following clustering problems: given a general undirected graph, partition its vertices into disjoint clusters such that each cluster forms a clique and the number...