Clustering of Nonnegative Data and an Application to Matrix Completion

• URL: http://arxiv.org/abs/2009.01279v1
• Date: Wed, 2 Sep 2020 18:24:47 GMT
• Title: Clustering of Nonnegative Data and an Application to Matrix Completion
• Authors: C. Strohmeier, D. Needell
• Abstract summary: We analyze its performance in relation to a certain measure of correlation between said subspaces. We use our clustering algorithm to develop a matrix completion algorithm which can outperform standard matrix completion algorithms on data matrices satisfying certain natural conditions.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we propose a simple algorithm to cluster nonnegative data lying in disjoint subspaces. We analyze its performance in relation to a certain measure of correlation between said subspaces. We use our clustering algorithm to develop a matrix completion algorithm which can outperform standard matrix completion algorithms on data matrices satisfying certain natural conditions.

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