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ICCV
2005
IEEE
15 years 9 months ago
A Unifying Approach to Hard and Probabilistic Clustering
We derive the clustering problem from first principles showing that the goal of achieving a probabilistic, or ”hard”, multi class clustering result is equivalent to the algeb...
Ron Zass, Amnon Shashua
BIODATAMINING
2008
96views more  BIODATAMINING 2008»
15 years 4 months ago
Fast approximate hierarchical clustering using similarity heuristics
Background: Agglomerative hierarchical clustering (AHC) is a common unsupervised data analysis technique used in several biological applications. Standard AHC methods require that...
Meelis Kull, Jaak Vilo
ASPDAC
1999
ACM
132views Hardware» more  ASPDAC 1999»
15 years 8 months ago
Faster and Better Spectral Algorithms for Multi-Way Partitioning
In this paper, two faster and better spectral algorithms are presented for the multi-way circuit partitioning problem with the objective of minimizing the Scaled Cost. As pointed ...
Jan-Yang Chang, Yu-Chen Liu, Ting-Chi Wang
STOC
2001
ACM
138views Algorithms» more  STOC 2001»
16 years 4 months ago
Fast computation of low rank matrix
Given a matrix A, it is often desirable to find a good approximation to A that has low rank. We introduce a simple technique for accelerating the computation of such approximation...
Dimitris Achlioptas, Frank McSherry
SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
14 years 7 months ago
Clustered low rank approximation of graphs in information science applications
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...
Berkant Savas, Inderjit S. Dhillon