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» An objective approach to cluster validation
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ECCV
2008
Springer
15 years 11 months ago
Unsupervised Structure Learning: Hierarchical Recursive Composition, Suspicious Coincidence and Competitive Exclusion
Abstract. We describe a new method for unsupervised structure learning of a hierarchical compositional model (HCM) for deformable objects. The learning is unsupervised in the sense...
Long Zhu, Chenxi Lin, Haoda Huang, Yuanhao Chen, A...
POS
1990
Springer
15 years 1 months ago
Semantic Clustering
Appropriate clustering of objects into pages in secondary memory is crucial to achieving good performance in a persistent object store. We present a new approach, termed semantic ...
Karen Shannon, Richard T. Snodgrass
ICDE
2012
IEEE
208views Database» more  ICDE 2012»
13 years 11 days 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...
WIMOB
2008
IEEE
15 years 4 months ago
Rate Allocation with Lifetime Maximization and Fairness for Data Aggregation in Sensor Networks
—We consider the rate allocation problem for data aggregation in wireless sensor networks with two objectives: 1) maximizing the lifetime of a local aggregation cluster and, 2) a...
Shouwen Lai, Binoy Ravindran, Hyeonjoong Cho
BMCBI
2011
14 years 5 months ago
A novel approach to the clustering of microarray data via nonparametric density estimation
Background: Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to di...
Riccardo De Bin, Davide Risso