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» Approximation schemes for clustering problems
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NIPS
2007
15 years 1 months ago
Convex Clustering with Exemplar-Based Models
Clustering is often formulated as the maximum likelihood estimation of a mixture model that explains the data. The EM algorithm widely used to solve the resulting optimization pro...
Danial Lashkari, Polina Golland
TIP
2002
116views more  TIP 2002»
14 years 11 months ago
Adaptive approximate nearest neighbor search for fractal image compression
Fractal image encoding is a computationally intensive method of compression due to its need to find the best match between image sub-blocks by repeatedly searching a large virtual...
Chong Sze Tong, Man Wong
EMMCVPR
2005
Springer
15 years 5 months ago
Optimizing the Cauchy-Schwarz PDF Distance for Information Theoretic, Non-parametric Clustering
This paper addresses the problem of efficient information theoretic, non-parametric data clustering. We develop a procedure for adapting the cluster memberships of the data pattern...
Robert Jenssen, Deniz Erdogmus, Kenneth E. Hild II...
CORR
2010
Springer
137views Education» more  CORR 2010»
14 years 12 months ago
Local algorithms in (weakly) coloured graphs
A local algorithm is a distributed algorithm that completes after a constant number of synchronous communication rounds. We present local approximation algorithms for the minimum ...
Matti Åstrand, Valentin Polishchuk, Joel Ryb...
COMPGEOM
2000
ACM
15 years 4 months ago
When crossings count - approximating the minimum spanning tree
We present an (1+ε)-approximation algorithm for computing the minimum-spanning tree of points in a planar arrangement of lines, where the metric is the number of crossings betwee...
Sariel Har-Peled, Piotr Indyk