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ICDE
2012
IEEE
208views Database» more  ICDE 2012»
11 years 10 months ago
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data
—Traditional clustering algorithms identify just a single clustering of the data. Today’s complex data, however, allow multiple interpretations leading to several valid groupin...
Emmanuel Müller, Stephan Günnemann, Ines...
WEBI
2010
Springer
13 years 5 months ago
Image Set Classification Using Multi-layer Multiple Instance Learning with Application to Cannabis Website Classification
We propose using multi-layer multiple instance learning (MMIL) for image set classification and applying it to the task of cannabis website classification. We treat each image as a...
Nianhua Xie, Haibin Ling, Weiming Hu
SIGKDD
2010
126views more  SIGKDD 2010»
13 years 2 months ago
MultiClust 2010: discovering, summarizing and using multiple clusterings
Traditional clustering focuses on finding a single best clustering solution from data. However, given a single data set, one could interpret it in different ways. This is particul...
Xiaoli Z. Fern, Ian Davidson, Jennifer G. Dy
TEC
2010
171views more  TEC 2010»
13 years 2 months ago
A Clustering Particle Swarm Optimizer for Locating and Tracking Multiple Optima in Dynamic Environments
In the real world, many optimization problems are dynamic. This requires an optimization algorithm to not only find the global optimal solution under a specific environment but als...
Shengxiang Yang, Changhe Li
ICDM
2007
IEEE
159views Data Mining» more  ICDM 2007»
14 years 2 months ago
Incremental Subspace Clustering over Multiple Data Streams
Data streams are often locally correlated, with a subset of streams exhibiting coherent patterns over a subset of time points. Subspace clustering can discover clusters of objects...
Qi Zhang, Jinze Liu, Wei Wang 0010