Math @ Duke

Publications [#235524] of Pankaj K. Agarwal
Papers Published
 Agarwal, PK; Phillips, JM; Sadri, B, Lipschitz unimodal and isotonic regression on paths and trees,
Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6034 LNCS
(2010),
pp. 384396, ISSN 03029743 [doi]
(last updated on 2018/10/16)
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 nearlinear time algorithms. © 2010 SpringerVerlag.


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