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» A framework to uncover multiple alternative clusterings
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ECML
2006
Springer
13 years 8 months ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...
EVOW
2005
Springer
13 years 10 months ago
Order Preserving Clustering over Multiple Time Course Experiments
Abstract. Clustering still represents the most commonly used technique to analyze gene expression data—be it classical clustering approaches that aim at finding biologically rel...
Stefan Bleuler, Eckart Zitzler
BIBE
2007
IEEE
125views Bioinformatics» more  BIBE 2007»
13 years 11 months ago
Large-scale Discovery of Regulatory Motifs Involved in Alternative Splicing
Alternative splicing is a highly important process in many eukaryotic organisms, but surprisingly little is known about its regulation. Often, this process involves cis-regulatory ...
Sihui Zhao, Jihye Kim, Steffen Heber
SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
13 years 6 months ago
Simultaneous Unsupervised Learning of Disparate Clusterings
Most clustering algorithms produce a single clustering for a given data set even when the data can be clustered naturally in multiple ways. In this paper, we address the difficult...
Prateek Jain, Raghu Meka, Inderjit S. Dhillon
PKDD
2010
Springer
166views Data Mining» more  PKDD 2010»
13 years 3 months ago
A Cluster-Level Semi-supervision Model for Interactive Clustering
Abstract. Semi-supervised clustering models, that incorporate user provided constraints to yield meaningful clusters, have recently become a popular area of research. In this paper...
Avinava Dubey, Indrajit Bhattacharya, Shantanu God...