Fast, Provable Algorithms for Isotonic Regression in all L_p-normsDownload PDFOpen Website

2015 (modified: 11 Nov 2022)NIPS 2015Readers: Everyone
Abstract: Given a directed acyclic graph $G,$ and a set of values $y$ on the vertices, the Isotonic Regression of $y$ is a vector $x$ that respects the partial order described by $G,$ and minimizes $\|x-y\|,$ for a specified norm. This paper gives improved algorithms for computing the Isotonic Regression for all weighted $\ell_{p}$-norms with rigorous performance guarantees. Our algorithms are quite practical, and their variants can be implemented to run fast in practice.
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