Low-rank compression of matrices and tensors is a huge and growing business. Closely related is low-rank compression of multivariate functions, a technique used in Chebfun2 and Chebfun3. Not all functions can be compressed, so the question becomes, which ones? Here we focus on two kinds of functions for which compression is effective: those with some alignment with the coordinate axes, and those dominated by small regions of localized complexity.
- Numerical Analysis Group Internal Seminar