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LATIN
2010
Springer

Lipschitz Unimodal and Isotonic Regression on Paths and Trees

13 years 10 months ago
Lipschitz Unimodal and Isotonic Regression on Paths and Trees
Abstract. We describe algorithms for finding the regression of t, a sequence of values, to the closest sequence s by mean squared error, so that s is always increasing (isotonicity) and so the values of two consecutive points do not increase by too much (Lipschitz). The isotonicity constraint can be replaced with a unimodular constraint, for exactly one local maximum in s. These algorithm are generalized from sequences of values to trees of values. For each we describe near-linear time algorithms.
Pankaj K. Agarwal, Jeff M. Phillips, Bardia Sadri
Added 18 May 2010
Updated 18 May 2010
Type Conference
Year 2010
Where LATIN
Authors Pankaj K. Agarwal, Jeff M. Phillips, Bardia Sadri
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