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Abstract Details
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Activity Number:
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176
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Learning and Data Mining
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| Abstract - #305159 |
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Title:
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Biclustering Based on Sparse Robust Singular Value Decomposition
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Author(s):
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Lingsong Zhang*+
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Companies:
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Purdue University
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Address:
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Department of Statistics, West Lafayette, IN, , USA
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Keywords:
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biclustering ;
singular value decomposition ;
sparsity ;
variable selection ;
principal component analysis ;
dimension reduction
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Abstract:
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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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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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