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» On K-Means Cluster Preservation Using Quantization Schemes
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ICDM
2009
IEEE
133views Data Mining» more  ICDM 2009»
13 years 11 months ago
On K-Means Cluster Preservation Using Quantization Schemes
This work examines under what conditions compression methodologies can retain the outcome of clustering operations. We focus on the popular k-Means clustering algorithm and we dem...
Deepak S. Turaga, Michail Vlachos, Olivier Versche...
MA
2010
Springer
206views Communications» more  MA 2010»
13 years 3 months ago
Quantization and clustering with Bregman divergences
 This paper deals with the quantization problem of a random variable X taking values in a separable and reexive Banach space, and with the related question of clustering independ...
Aurélie Fischer
HIS
2009
13 years 2 months ago
An Efficient VQ-Based Data Hiding Scheme Using Voronoi Clustering
In this paper, we propose a vector quantization (VQ) -based information hiding scheme that cluster the VQ codeowrds according the codewords' relation on Voronoi Diagram (VD). ...
Ming-Ni Wu, Puu-An Juang, Yu-Chiang Li
ICPR
2004
IEEE
14 years 5 months ago
Human Perception Based Color Image Quantization
We present a new algorithm for color image quantization based on human color perception properties. We construct two kinds of map by analyzing the spatial color distributions to t...
In-So Kweon, Kuk-Jin Yoon
ICCV
2011
IEEE
12 years 4 months ago
Source Constrained Clustering
We consider the problem of quantizing data generated from disparate sources, e.g. subjects performing actions with different styles, movies with particular genre bias, various con...
Ekaterina Taralova, Fernando DelaTorre, Martial He...