Clustering of Nonnegative Data and an Application to Matrix Completion

C. Strohmeier; D. Needell

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arXiv · 2009.01279

Clustering of Nonnegative Data and an Application to Matrix Completion

C. Strohmeier·D. Needell

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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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C. Strohmeier, D. Needell. 2020-09-02. Clustering of Nonnegative Data and an Application to Matrix Completion. https://arxiv.org/abs/2009.01279

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