Fast, Provable Algorithms for Isotonic Regression in all L_p-norms

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• github.com/sachdevasushant/Isotonic
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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 _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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