Randomized Low-Rank Approximation of Kernel Matrices
Three randomized low-rank approximation algorithms written from scratch in Python and compared with the exact SVD on synthetic and boundary integral kernel matrices. The SRHT sketch has fewer operations than the Gaussian one, but it was slower and used much more memory in my tests.