Exemplar-based Robust Coherent Biclustering

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Exemplar-based Robust Coherent Biclustering
The biclustering, co-clustering, or subspace clustering problem involves simultaneously grouping the rows and columns of a data matrix to uncover biclusters or sub-matrices of the data matrix that optimize a desired objective function. In coherent biclustering, the objective function contains a coherence measure of the biclusters. We introduce a novel formulation of the coherent biclustering problem and use it to derive two algorithms. The first algorithm is based on loopy message passing; and the second relies on a greedy strategy yielding an algorithm that is significantly faster than the first. A distinguishing feature of these algorithms is that they identify an exemplar or a prototypical member of each bicluster. We note the interference from background elements in biclustering, and offer a means to circumvent such interference using additional regularization. Our experiments with synthetic as well as real-world datasets show that our algorithms are competitive with the curre...
Kewei Tu, Xixiu Ouyang, Dingyi Han, Vasant Honavar
Added 17 Sep 2011
Updated 17 Sep 2011
Type Journal
Year 2011
Where SDM
Authors Kewei Tu, Xixiu Ouyang, Dingyi Han, Vasant Honavar
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