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» Approximation Algorithms for Clustering Problems
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ICML
2005
IEEE
16 years 7 months ago
Clustering through ranking on manifolds
Clustering aims to find useful hidden structures in data. In this paper we present a new clustering algorithm that builds upon the consistency method (Zhou, et.al., 2003), a semi-...
Markus Breitenbach, Gregory Z. Grudic
AINA
2008
IEEE
16 years 1 months ago
PRODUCE: A Probability-Driven Unequal Clustering Mechanism for Wireless Sensor Networks
There has been proliferation of research on seeking for distributing the energy consumption among nodes in each cluster and between cluster heads to extend the network lifetime. H...
Jung-Hwan Kim, Sajjad Hussain Chauhdary, WenCheng ...
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MICCAI
1999
Springer
15 years 11 months ago
Statistical Segmentation of fMRI Activations Using Contextual Clustering
Abstract. A central problem in the analysis of functional magnetic resonance imaging (fMRI) data is the reliable detection and segmentation of activated areas. Often this goal is a...
Eero Salli, Ari Visa, Hannu J. Aronen, Antti Korve...
SODA
2007
ACM
145views Algorithms» more  SODA 2007»
15 years 8 months ago
Aggregation of partial rankings, p-ratings and top-m lists
We study the problem of aggregating partial rankings. This problem is motivated by applications such as meta-searching and information retrieval, search engine spam fighting, e-c...
Nir Ailon
CEC
2009
IEEE
16 years 1 months ago
A clustering particle swarm optimizer for dynamic optimization
Abstract—In the real world, many applications are nonstationary optimization problems. This requires that optimization algorithms need to not only find the global optimal soluti...
Changhe Li, Shengxiang Yang