Clustered SVD strategies in latent semantic indexing
Information Processing and Management: an International Journal
Clustered SVD strategies in latent semantic indexing
Information Processing and Management: an International Journal
DLPR: a distributed locality preserving dimension reduction algorithm
IDCS'12 Proceedings of the 5th international conference on Internet and Distributed Computing Systems
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In this paper we study truncated SVDs for column-partitioned matrices. In particular, we analyze the relation between the truncated SVDs of a matrix and the truncated SVDs of its submatrices. We give necessary and sufficient conditions under which a truncated SVD of a matrix can be constructed from those of its submatrices. We then present perturbation analysis to show that an approximate truncated SVD can still be computed even if the given necessary and sufficient conditions are only approximately satisfied. We also apply our general results to a class of matrices with the so-called low-rank-plus-shift structure.