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Randomized SVD Approximations for Spectral Co-Clustering of Word-Document Matrices

This story is from 2026-09-18. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.19243v1 Announce Type: new Abstract: 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 rando…

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  1. 2026-09-18 04:00 · arXiv cs.LG
    Randomized SVD Approximations for Spectral Co-Clustering of Word-Document Matrices

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