Izvestiya of Saratov University.

Mathematics. Mechanics. Informatics

ISSN 1816-9791 (Print)
ISSN 2541-9005 (Online)


For citation:

Gudkov A. A., Mironov S. V., Faizliev A. R. On the Convergence of a Greedy Algorithm for the Solution of the Problem for the Construction of Monotone Regression. Izvestiya of Saratov University. Mathematics. Mechanics. Informatics, 2017, vol. 17, iss. 4, pp. 431-440. DOI: 10.18500/1816-9791-2017-17-4-431-440, EDN: ZXJPNJ

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Published online: 
28.11.2017
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ZXJPNJ

On the Convergence of a Greedy Algorithm for the Solution of the Problem for the Construction of Monotone Regression

Autors: 
Gudkov Alexandr A., Saratov State University
Mironov Sergei Vladimirovich, Saratov State University
Faizliev Alexey R., Saratov State University
Abstract: 

The paper presents greedy algorithms that use the Frank-Woolf-type approach for finding a sparse monotonic regression. The problem of finding monotonic regression arises in smoothing an empirical data, in problems of dynamic programming, mathematical statistics and in many other applied problems. The problem is to find a non-decreasing sequence of points with the lowest error of approximation to the given set of points on the plane. The problem of constructing monotonic regression can be formulated as a convex programming problem with linear constraints and is NP-hard problem. The paper also contains estimates of the rate of convergence for the presented greedy algorithms.

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Received: 
20.07.2017
Accepted: 
10.11.2017
Published: 
05.12.2017
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