Dimensionality Reduction of Massive Sparse Datasets Using Coresets

NeurIPS 2016 Dan FeldmanMikhail VolkovDaniela Rus

In this paper we present a practical solution with performance guarantees to the problem of dimensionality reduction for very large scale sparse matrices. We show applications of our approach to computing the Principle Component Analysis (PCA) of any $n\times d$ matrix, using one pass over the stream of its rows... (read more)

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