The singular value decomposition (SVD) is among the most ubiquitous matrix factorizations. Specifically, it is a cornerstone algorithm for data analysis, dimensionality reduction and data compression. However, despite modern computer power, massive datasets pose a computational challenge for traditional SVD algorithms. We present the R package rsvd, which enables the fast computation of the SVD...
