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Randomized SVD Approximations for Spectral Co-Clustering of Word-Document Matrices
Spectral co-clustering is a useful tool for discovering latent structure in word-document matrices, but its reliance on singular value decomposition (SVD) can make standard formulations expensive on high-dimensional data. This paper presents two randomized approximations for normalized spectral co-c
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