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» On the Complexity of Ordinal Clustering
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DCC
2009
IEEE
14 years 9 months ago
Clustered Reversible-KLT for Progressive Lossy-to-Lossless 3d Image Coding
The RKLT is a lossless approximation to the KLT, and has been recently employed for progressive lossy-to-lossless coding of hyperspectral images. Both yield very good coding perfo...
Ian Blanes, Joan Serra-Sagristà
SDM
2009
SIAM
193views Data Mining» more  SDM 2009»
14 years 6 months ago
Agglomerative Mean-Shift Clustering via Query Set Compression.
Mean-Shift (MS) is a powerful non-parametric clustering method. Although good accuracy can be achieved, its computational cost is particularly expensive even on moderate data sets...
Xiaotong Yuan, Bao-Gang Hu, Ran He
ALT
2009
Springer
14 years 5 months ago
Approximation Algorithms for Tensor Clustering
Abstract. We present the first (to our knowledge) approximation algorithm for tensor clustering—a powerful generalization to basic 1D clustering. Tensors are increasingly common...
Stefanie Jegelka, Suvrit Sra, Arindam Banerjee
BPM
2009
Springer
175views Business» more  BPM 2009»
14 years 3 months ago
Understanding Spaghetti Models with Sequence Clustering for ProM
The goal of process mining is to discover process models from event logs. However, for processes that are not well structured and have a lot of diverse behavior, existing process m...
Gabriel M. Veiga, Diogo R. Ferreira
CVPR
2000
IEEE
14 years 1 months ago
Perceptual Grouping and Segmentation by Stochastic Clustering
We use cluster analysis as a unifying principle for problems from low, middle and high level vision. The clustering problem is viewed as graph partitioning, where nodes represent ...
Yoram Gdalyahu, Noam Shental, Daphna Weinshall