A Pratical Guide to Randomized Matrix Computations with MATLAB Implementations
This is a very useful paper for whom wants to implements the randomized algorithm in MATLAB and is easy to follow and understand.
In this paper, several matrix sketching methods are first introduced. Then application of least square regression and rank k svd are introduced.
What confused me now is that for SPSD matrix sketching, it seems that for the methods of matrix inversion and eigenvalue decomposition given in the paper, the matrix needs to be SPSD. What if the matrix is not SPSD when I want to implement randomized algorithm to compute the inversion and eigenvalue decomposition?
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