307eb8ee16198da891c521eca21464c1-Supplemental.pdf

We follow the notation of [20, 22] with the exception that we use X for the data matrix rather than A, with new data X+ of dimension n b rather than m l. Here, we focus on the updates of the left singular subspace spanned. Details for the right singular subspace are similar and covered in the original works. Matrix sizes are listed for convenience in Table 2. Table 2: Matrix dimensions for incremental SVD. The goal of the algorithm is to maintain an approximation of the data up to the present moment as X QRW> (8) with Q and W orthogonal but R not necessarily diagonal.