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AAAI
2007
15 years 1 days ago
Clustering with Local and Global Regularization
Clustering is an old research topic in data mining and machine learning communities. Most of the traditional clustering methods can be categorized local or global ones. In this pa...
Fei Wang, Changshui Zhang, Tao Li
ICASSP
2011
IEEE
14 years 1 months ago
Outlier-aware robust clustering
Clustering is a basic task in a variety of machine learning applications. Partitioning a set of input vectors into compact, wellseparated subsets can be severely affected by the p...
Pedro A. Forero, Vassilis Kekatos, Georgios B. Gia...
ICDM
2003
IEEE
158views Data Mining» more  ICDM 2003»
15 years 3 months ago
Combining Multiple Weak Clusterings
A data set can be clustered in many ways depending on the clustering algorithm employed, parameter settings used and other factors. Can multiple clusterings be combined so that th...
Alexander P. Topchy, Anil K. Jain, William F. Punc...
IPMI
2007
Springer
15 years 10 months ago
Probabilistic Clustering and Quantitative Analysis of White Matter Fiber Tracts
A novel framework for joint clustering and point-by-point mapping of white matter fiber pathways is presented. Accurate clustering of the trajectories into fiber bundles requires p...
Mahnaz Maddah, William M. Wells III, Simon K. Warf...
CEC
2008
IEEE
15 years 4 months ago
A Quantum-inspired Genetic Algorithm for data clustering
—The conventional K-Means clustering algorithm must know the number of clusters in advance and the clustering result is sensitive to the selection of the initial cluster centroid...
Jing Xiao, YuPing Yan, Ying Lin, Ling Yuan, Jun Zh...