Efficient Algorithms for Multidimensional Segmented Regression

24 Mar 2020Ilias DiakonikolasJerry LiAnastasia Voloshinov

We study the fundamental problem of fixed design {\em multidimensional segmented regression}: Given noisy samples from a function $f$, promised to be piecewise linear on an unknown set of $k$ rectangles, we want to recover $f$ up to a desired accuracy in mean-squared error. We provide the first sample and computationally efficient algorithm for this problem in any fixed dimension... (read more)

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