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ISAAC
2009
Springer
175views Algorithms» more  ISAAC 2009»
14 years 4 months ago
Worst-Case and Smoothed Analysis of k-Means Clustering with Bregman Divergences
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Bodo Manthey, Heiko Röglin
CLUSTER
2007
IEEE
14 years 4 months ago
The challenges and rewards of petascale clusters
-Jul 2 - Santa Clara Conv Ctr - abstracts by 4/30 Asilomar Conference on Signals, Systems, and Computers due by June 1 [more] - Nov 1-4, 2009 - Asilomar Conf Grounds, Pacific Grove...
Mark Seager
CHI
2009
ACM
13 years 8 months ago
Semantically structured tag clouds: an empirical evaluation of clustered presentation approaches
Tag clouds have become a frequently used interaction technique in the web. Recently several approaches to present tag clouds with the tags semantically clustered have been propose...
Johann Schrammel, Michael Leitner, Manfred Tscheli...
CIBCB
2009
IEEE
13 years 8 months ago
Shape modeling and clustering of white matter fiber tracts using fourier descriptors
Reliable shape modeling and clustering of white matter fiber tracts is essential for clinical and anatomical studies that use diffusion tensor imaging (DTI) tractography techniques...
Xuwei Liang, Qi Zhuang, Ning Cao, Jun Zhang
ICCV
2009
IEEE
13 years 8 months ago
The Normalized Subspace Inclusion: Robust clustering of motion subspaces
Perceiving dynamic scenes of rigid bodies, through affine projections of moving 3D point clouds, boils down to clustering the rigid motion subspaces supported by the points' ...
Nuno Pinho da Silva, João Paulo Costeira