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» A More Effective Linear Kernelization for Cluster Editing
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CIKM
2006
Springer
13 years 9 months ago
Adaptive non-linear clustering in data streams
Data stream clustering has emerged as a challenging and interesting problem over the past few years. Due to the evolving nature, and one-pass restriction imposed by the data strea...
Ankur Jain, Zhihua Zhang, Edward Y. Chang
RIVF
2008
13 years 6 months ago
Simple but effective methods for combining kernels in computational biology
Complex biological data generated from various experiments are stored in diverse data types in multiple datasets. By appropriately representing each biological dataset as a kernel ...
Hiroaki Tanabe, Tu Bao Ho, Canh Hao Nguyen, Saori ...
ICML
2008
IEEE
14 years 6 months ago
Active kernel learning
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A variety of kernel learning algorithms have been prop...
Steven C. H. Hoi, Rong Jin
BMCBI
2008
159views more  BMCBI 2008»
13 years 5 months ago
Estimation and testing for the effect of a genetic pathway on a disease outcome using logistic kernel machine regression via log
Background: Growing interest on biological pathways has called for new statistical methods for modeling and testing a genetic pathway effect on a health outcome. The fact that gen...
Dawei Liu, Debashis Ghosh, Xihong Lin
TCS
2010
13 years 3 months ago
Clustering with partial information
The Correlation Clustering problem, also known as the Cluster Editing problem, seeks to edit a given graph by adding and deleting edges to obtain a collection of disconnected cliq...
Hans L. Bodlaender, Michael R. Fellows, Pinar Hegg...