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An Accelerated Exact Algorithm for the One-Dimensional M-Variance Problem. / Kel’manov, A. V.; Ruzankin, P. S.

In: Pattern Recognition and Image Analysis, Vol. 29, No. 4, 01.10.2019, p. 573-576.

Research output: Contribution to journal › Article › peer-review

Harvard

Kel’manov, AV & Ruzankin, PS 2019, 'An Accelerated Exact Algorithm for the One-Dimensional M-Variance Problem', Pattern Recognition and Image Analysis, vol. 29, no. 4, pp. 573-576. https://doi.org/10.1134/S1054661819040072

APA

Kel’manov, A. V., & Ruzankin, P. S. (2019). An Accelerated Exact Algorithm for the One-Dimensional M-Variance Problem. Pattern Recognition and Image Analysis, 29(4), 573-576. https://doi.org/10.1134/S1054661819040072

Vancouver

Kel’manov AV, Ruzankin PS. An Accelerated Exact Algorithm for the One-Dimensional M-Variance Problem. Pattern Recognition and Image Analysis. 2019 Oct 1;29(4):573-576. doi: 10.1134/S1054661819040072

Author

Kel’manov, A. V. ; Ruzankin, P. S. / An Accelerated Exact Algorithm for the One-Dimensional M-Variance Problem. In: Pattern Recognition and Image Analysis. 2019 ; Vol. 29, No. 4. pp. 573-576.

BibTeX

@article{e52b99e7a65948d3a03908eb22e3ba43,
title = "An Accelerated Exact Algorithm for the One-Dimensional M-Variance Problem",
abstract = "Abstract: The known quadratic NP-hard (in the strong sense) M-variance problem is considered. It arises in the following typical problem of data analysis: in a set of N objects determined by their characteristics (features), find a subset of M elements close to each other. For the one-dimensional case, an accelerated exact algorithm with complexity (Formula presented.)(N logN) is proposed.",
keywords = "$NP$-hard problem, accelerated exact algorithm, Euclidean space, one-dimensional case, quadratic scattering, subset search",
author = "Kel{\textquoteright}manov, {A. V.} and Ruzankin, {P. S.}",
year = "2019",
month = oct,
day = "1",
doi = "10.1134/S1054661819040072",
language = "English",
volume = "29",
pages = "573--576",
journal = "Pattern Recognition and Image Analysis",
issn = "1054-6618",
publisher = "Maik Nauka Publishing / Springer SBM",
number = "4",

}

RIS

TY - JOUR

T1 - An Accelerated Exact Algorithm for the One-Dimensional M-Variance Problem

AU - Kel’manov, A. V.

AU - Ruzankin, P. S.

PY - 2019/10/1

Y1 - 2019/10/1

N2 - Abstract: The known quadratic NP-hard (in the strong sense) M-variance problem is considered. It arises in the following typical problem of data analysis: in a set of N objects determined by their characteristics (features), find a subset of M elements close to each other. For the one-dimensional case, an accelerated exact algorithm with complexity (Formula presented.)(N logN) is proposed.

AB - Abstract: The known quadratic NP-hard (in the strong sense) M-variance problem is considered. It arises in the following typical problem of data analysis: in a set of N objects determined by their characteristics (features), find a subset of M elements close to each other. For the one-dimensional case, an accelerated exact algorithm with complexity (Formula presented.)(N logN) is proposed.

KW - $NP$-hard problem

KW - accelerated exact algorithm

KW - Euclidean space

KW - one-dimensional case

KW - quadratic scattering

KW - subset search

UR - http://www.scopus.com/inward/record.url?scp=85077075713&partnerID=8YFLogxK

U2 - 10.1134/S1054661819040072

DO - 10.1134/S1054661819040072

M3 - Article

AN - SCOPUS:85077075713

VL - 29

SP - 573

EP - 576

JO - Pattern Recognition and Image Analysis

JF - Pattern Recognition and Image Analysis

SN - 1054-6618

IS - 4

ER -

ID: 22999396