Abstract Details
Activity Number:
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504
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Type:
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Contributed
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Date/Time:
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Wednesday, August 12, 2015 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistical Learning and Data Mining
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Abstract #316444
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Title:
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Graph-Guided Matrix Completion
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Author(s):
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Eric Chi* and Arvind Rao and Christopher Harshaw and Ashok Veeraraghavan and Salman Asif and Richard Baraniuk
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Companies:
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Rice University and MD Anderson Cancer Center and Rice University and Rice University and Rice University and Rice University
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Keywords:
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Matrix Completion ;
Graph Laplacian ;
Prediction ;
Regularization ;
Drug-Protein Interaction ;
Convex Optimization
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Abstract:
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We present a novel method for performing matrix completion with side information on row-by-row similarities and column-by-column similarities. Our approach generalizes recent proposals for matrix estimation with smoothness constraints with respect to row and column graphs. We present a novel estimation procedure based on solving a convex optimization problem. We present simulation results and an application to in silico drug-protein interaction prediction.
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Authors who are presenting talks have a * after their name.
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