SVD and Optimal Truncation

This video describes how to truncate the singular value decomposition (SVD) for matrix approximation. See paper by Gavish and Donoho “The Optimal Hard Threshold for Singular Values is 4/\sqrt{3}“  These lectures follow Chapter 1 from: “Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control“ by Brunton and Kutz Amazon: