An Algorigtm for Singular Value Decomposition of Matrices in Blocks
For practitioners with memory constraints, this method enables SVD of large matrices without exceeding block size limits.
The paper proposes two block-based algorithms for singular value decomposition that avoid handling matrices larger than the largest block, tested on a 17780x3204 document-term matrix divided into blocks with the largest block being 215x215.
Two methods to decompose block matrices analogous to Singular Matrix Decomposition are proposed, one yielding the so called economy decomposition, and other yielding the full decomposition. This method is devised to avoid handling matrices bigger than the biggest blocks, so it is particularly appropriate when a limitation on the size of matrices exists. The method is tested on a document-term matrix (17780x3204) divided in 4 blocks, the upper-left corner being 215x215.