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DILS
2004
Springer
13 years 10 months ago
Heterogeneous Data Integration with the Consensus Clustering Formalism
Meaningfully integrating massive multi-experimental genomic data sets is becoming critical for the understanding of gene function. We have recently proposed methodologies for integ...
Vladimir Filkov, Steven Skiena
ICTAI
2003
IEEE
13 years 10 months ago
Integrating Microarray Data by Consensus Clustering
With the exploding volume of microarray experiments comes increasing interest in mining repositories of such data. Meaningfully combining results from varied experiments on an equ...
Vladimir Filkov, Steven Skiena
ICDM
2007
IEEE
149views Data Mining» more  ICDM 2007»
13 years 11 months ago
Solving Consensus and Semi-supervised Clustering Problems Using Nonnegative Matrix Factorization
Consensus clustering and semi-supervised clustering are important extensions of the standard clustering paradigm. Consensus clustering (also known as aggregation of clustering) ca...
Tao Li, Chris H. Q. Ding, Michael I. Jordan
BIBE
2008
IEEE
160views Bioinformatics» more  BIBE 2008»
13 years 12 months ago
Parallel integration of heterogeneous genome-wide data sources
— Heterogeneous genome-wide data sources capture information on various aspects of complex biological systems. For instance, transcriptome, interactome and phenome-level informat...
Derek Greene, Kenneth Bryan, Padraig Cunningham
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 6 months ago
Heterogeneous source consensus learning via decision propagation and negotiation
Nowadays, enormous amounts of data are continuously generated not only in massive scale, but also from different, sometimes conflicting, views. Therefore, it is important to conso...
Jing Gao, Wei Fan, Yizhou Sun, Jiawei Han