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» Discovering Classification from Data of Multiple Sources
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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
BMCBI
2005
150views more  BMCBI 2005»
13 years 7 months ago
Discover protein sequence signatures from protein-protein interaction data
Background: The development of high-throughput technologies such as yeast two-hybrid systems and mass spectrometry technologies has made it possible to generate large protein-prot...
Jianwen Fang, Ryan J. Haasl, Yinghua Dong, Gerald ...
IJON
2002
128views more  IJON 2002»
13 years 7 months ago
Extraction of a source from multichannel data using sparse decomposition
It was discovered recently that sparse decomposition by signal dictionaries results in dramatic improvement of the qualities of blind source separation. We exploit sparse decompos...
Michael Zibulevsky, Yehoshua Y. Zeevi
JCB
2002
104views more  JCB 2002»
13 years 7 months ago
Learning Gene Functional Classifications from Multiple Data Types
Paul Pavlidis, Jason Weston, Jinsong Cai, William ...
GECCO
2004
Springer
102views Optimization» more  GECCO 2004»
14 years 26 days ago
Dynamic and Scalable Evolutionary Data Mining: An Approach Based on a Self-Adaptive Multiple Expression Mechanism
Data mining has recently attracted attention as a set of efficient techniques that can discover patterns from huge data. More recent advancements in collecting massive evolving da...
Olfa Nasraoui, Carlos Rojas, Cesar Cardona