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- W2336187369 abstract "Non-negative matrix factorization (NMF) is a widely used tool for exploratory data analysis in many disciplines. In this paper, we describe an approach to NMF based on random projections and give a geometric analysis of a prototypical algorithm. Our main result shows the proto-algorithm requires $bar{kappa}klog k$ optimizations to find all the extreme columns of the matrix, where $k$ is the number of extreme columns, and $bar{kappa}$ is a geometric condition number. We show empirically that the proto-algorithm is robust to noise and well-suited to modern distributed computing architectures." @default.
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- W2336187369 date "2014-05-16" @default.
- W2336187369 modified "2023-09-27" @default.
- W2336187369 title "Random projections for non-negative matrix factorization" @default.
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