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NIPS
2007
15 years 6 months ago
Consistent Minimization of Clustering Objective Functions
Clustering is often formulated as a discrete optimization problem. The objective is to find, among all partitions of the data set, the best one according to some quality measure....
Ulrike von Luxburg, Sébastien Bubeck, Stefa...
167
Voted
PAMI
2006
134views more  PAMI 2006»
15 years 5 months ago
A Genetic Algorithm Using Hyper-Quadtrees for Low-Dimensional K-means Clustering
The k-means algorithm is widely used for clustering because of its computational efficiency. Given n points in d-dimensional space and the number of desired clusters k, k-means see...
Michael Laszlo, Sumitra Mukherjee
SIGKDD
2000
95views more  SIGKDD 2000»
15 years 4 months ago
Scalability for Clustering Algorithms Revisited
This paper presents a simple new algorithm that performs k-means clustering in one scan of a dataset, while using a bu er for points from the dataset of xed size. Experiments show...
Fredrik Farnstrom, James Lewis, Charles Elkan
ICC
2011
IEEE
257views Communications» more  ICC 2011»
14 years 4 months ago
Increasing the Lifetime of Roadside Sensor Networks Using Edge-Betweenness Clustering
Abstract—Wireless Sensor Networks are proven highly successful in many areas, including military and security monitoring. In this paper, we propose a method to use the edge–bet...
Joakim Flathagen, Ovidiu Valentin Drugan, Paal E. ...
208
Voted
CVPR
2009
IEEE
17 years 5 days ago
Constrained Clustering via Spectral Regularization
We propose a novel framework for constrained spectral clustering with pairwise constraints which specify whether two objects belong to the same cluster or not. Unlike previous m...
Zhenguo Li (The Chinese University of Hong Kong), ...