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ECCV
2008
Springer
16 years 8 months ago
Quick Shift and Kernel Methods for Mode Seeking
We show that the complexity of the recently introduced medoid-shift algorithm in clustering N points is O(N2 ), with a small constant, if the underlying distance is Euclidean. This...
Andrea Vedaldi, Stefano Soatto
KDD
2004
ACM
164views Data Mining» more  KDD 2004»
16 years 7 months ago
Cluster-based concept invention for statistical relational learning
We use clustering to derive new relations which augment database schema used in automatic generation of predictive features in statistical relational learning. Clustering improves...
Alexandrin Popescul, Lyle H. Ungar
WEBDB
2004
Springer
191views Database» more  WEBDB 2004»
16 years 1 days ago
Visualizing and Discovering Web Navigational Patterns
Web site structures are complex to analyze. Cross-referencing the web structure with navigational behaviour adds to the complexity of the analysis. However, this convoluted analys...
Jiyang Chen, Lisheng Sun, Osmar R. Zaïane, Ra...
DCC
2009
IEEE
16 years 7 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»
16 years 3 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