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ICCV
2005
IEEE
14 years 1 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»
13 years 7 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»
13 years 11 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»
14 years 7 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»
12 years 10 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