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ICPR
2006
IEEE
15 years 11 months ago
Exploiting the Geometry of Gene Expression Patterns for Unsupervised Learning
Typical gene expression clustering algorithms are restricted to a specific underlying pattern model while overlooking the possibility that other information carrying patterns may ...
Rave Harpaz, Robert M. Haralick
ICANN
2007
Springer
15 years 4 months ago
Split-Merge Incremental LEarning (SMILE) of Mixture Models
In this article we present an incremental method for building a mixture model. Given the desired number of clusters K ≥ 2, we start with a two-component mixture and we optimize t...
Konstantinos Blekas, Isaac E. Lagaris
IDA
2002
Springer
14 years 10 months ago
Evolutionary model selection in unsupervised learning
Feature subset selection is important not only for the insight gained from determining relevant modeling variables but also for the improved understandability, scalability, and pos...
YongSeog Kim, W. Nick Street, Filippo Menczer
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
15 years 10 months ago
Unsupervised learning on k-partite graphs
Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the resear...
Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip...
ICML
2009
IEEE
15 years 11 months ago
A least squares formulation for a class of generalized eigenvalue problems in machine learning
Many machine learning algorithms can be formulated as a generalized eigenvalue problem. One major limitation of such formulation is that the generalized eigenvalue problem is comp...
Liang Sun, Shuiwang Ji, Jieping Ye