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Abstract Details

Activity Number: 176
Type: Contributed
Date/Time: Monday, July 30, 2012 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Learning and Data Mining
Abstract - #305159
Title: Biclustering Based on Sparse Robust Singular Value Decomposition
Author(s): Lingsong Zhang*+
Companies: Purdue University
Address: Department of Statistics, West Lafayette, IN, , USA
Keywords: biclustering ; singular value decomposition ; sparsity ; variable selection ; principal component analysis ; dimension reduction

Motivated by bi-clustering problems in presence of outliers, a sparse robust singular value decomposition method is developed. The robustness mitigates the outlying effects, and the sparsity improves the interpretability. An efficient algorithm is provided. Extensive simulations and real examples are used to illustrate the usefulness of the new method.

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