Some algorithms with guaranteed accuracy for 2-clustering problems with given center of one cluster

Alexander Kel'Manov; Vladimir Khandeev

doi:10.1109/SIBIRCON.2017.8109844

Some algorithms with guaranteed accuracy for 2-clustering problems with given center of one cluster

Alexander Kel'Manov, Vladimir Khandeev

Theoretical Cybernetics Section

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Abstract

We consider the problem of 2-partitioning a finite set of points in Euclidean space minimizing the sum of squared distances between cluster elements and the corresponding cluster centers. It is assumed that the center of one of the desired clusters is the origin, while the center of the other cluster is unknown and determined as the mean value over cluster elements. In this work, we present a short survey on the results for this problem.

Original language	English
Title of host publication	Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	91-93
Number of pages	3
ISBN (Electronic)	9781538615966
DOIs	https://doi.org/10.1109/SIBIRCON.2017.8109844
Publication status	Published - 14 Nov 2017
Event	2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017 - Novosibirsk, Russian Federation Duration: 18 Sep 2017 → 22 Sep 2017

Conference

Conference	2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017
Country	Russian Federation
City	Novosibirsk
Period	18.09.2017 → 22.09.2017

Keywords

Clusterization
Data analysis
Efficient algorithms with performance guarantees
Intractable problems
Pattern recognition

Access to Document

10.1109/SIBIRCON.2017.8109844

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Kel'Manov, A., & Khandeev, V. (2017). Some algorithms with guaranteed accuracy for 2-clustering problems with given center of one cluster. In Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017 (pp. 91-93). [8109844] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIBIRCON.2017.8109844

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title = "Some algorithms with guaranteed accuracy for 2-clustering problems with given center of one cluster",

abstract = "We consider the problem of 2-partitioning a finite set of points in Euclidean space minimizing the sum of squared distances between cluster elements and the corresponding cluster centers. It is assumed that the center of one of the desired clusters is the origin, while the center of the other cluster is unknown and determined as the mean value over cluster elements. In this work, we present a short survey on the results for this problem.",

keywords = "Clusterization, Data analysis, Efficient algorithms with performance guarantees, Intractable problems, Pattern recognition",

author = "Alexander Kel'Manov and Vladimir Khandeev",

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doi = "10.1109/SIBIRCON.2017.8109844",

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Kel'Manov, A & Khandeev, V 2017, Some algorithms with guaranteed accuracy for 2-clustering problems with given center of one cluster. in Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017., 8109844, Institute of Electrical and Electronics Engineers Inc., pp. 91-93, 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017, Novosibirsk, Russian Federation, 18.09.2017. https://doi.org/10.1109/SIBIRCON.2017.8109844

Some algorithms with guaranteed accuracy for 2-clustering problems with given center of one cluster. / Kel'Manov, Alexander; Khandeev, Vladimir.

Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 91-93 8109844.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

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AB - We consider the problem of 2-partitioning a finite set of points in Euclidean space minimizing the sum of squared distances between cluster elements and the corresponding cluster centers. It is assumed that the center of one of the desired clusters is the origin, while the center of the other cluster is unknown and determined as the mean value over cluster elements. In this work, we present a short survey on the results for this problem.

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