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CVPR
2003
IEEE
16 years 7 months ago
Clustering Appearances of Objects Under Varying Illumination Conditions
We introduce two appearance-based methods for clustering a set of images of 3-D objects, acquired under varying illumination conditions, into disjoint subsets corresponding to ind...
Jeffrey Ho, Ming-Hsuan Yang, Jongwoo Lim, Kuang-Ch...
ICDM
2009
IEEE
117views Data Mining» more  ICDM 2009»
15 years 11 months ago
Clustering with Multiple Graphs
—In graph-based learning models, entities are often represented as vertices in an undirected graph with weighted edges describing the relationships between entities. In many real...
Wei Tang, Zhengdong Lu, Inderjit S. Dhillon
ISAAC
2009
Springer
175views Algorithms» more  ISAAC 2009»
15 years 11 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
WMPI
2004
ACM
15 years 10 months ago
Cache organizations for clustered microarchitectures
Clustered microarchitectures are an effective organization to deal with the problem of wire delays and complexity by partitioning some of the processor resources. The organization ...
José González, Fernando Latorre, Ant...
IPPS
2003
IEEE
15 years 10 months ago
Design and Evaluation of a Parallel HOP Clustering Algorithm for Cosmological Simulation
Clustering, or unsupervised classification, has many uses in fields that depend on grouping results from large amount of data, an example being the N-body cosmological simulation ...
Ying Liu, Wei-keng Liao, Alok N. Choudhary