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» Approximation Algorithms for Clustering Problems
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BMCBI
2007
173views more  BMCBI 2007»
15 years 7 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
ICDM
2008
IEEE
185views Data Mining» more  ICDM 2008»
16 years 2 months ago
Clustering Uncertain Data Using Voronoi Diagrams
We study the problem of clustering uncertain objects whose locations are described by probability density functions (pdf). We show that the UK-means algorithm, which generalises t...
Ben Kao, Sau Dan Lee, David W. Cheung, Wai-Shing H...
SETN
2004
Springer
16 years 29 days ago
Incremental Mixture Learning for Clustering Discrete Data
Abstract. This paper elaborates on an efficient approach for clustering discrete data by incrementally building multinomial mixture models through likelihood maximization using the...
Konstantinos Blekas, Aristidis Likas
WSCG
2004
174views more  WSCG 2004»
15 years 9 months ago
Objects and Occlusion from Motion Labeling
The problem of segmenting color video sequences is addressed. Boundary motion and occlusion relations expressed by labeling rules are argued to be of key importance for segmentati...
Albert Akhriev, Alexander Bonch-Osmolovsky, Alexan...
GECCO
2004
Springer
16 years 1 months ago
Real-Coded Bayesian Optimization Algorithm: Bringing the Strength of BOA into the Continuous World
This paper describes a continuous estimation of distribution algorithm (EDA) to solve decomposable, real-valued optimization problems quickly, accurately, and reliably. This is the...
Chang Wook Ahn, Rudrapatna S. Ramakrishna, David E...