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English version: Journal of Applied and Industrial Mathematics, 2020, 14:3, 490-502 |
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Volume 27, No 3, 2020, P. 88-108 UDC 519.8
Keywords: graph, clustering, NP-hard problem, approximation algorithm, guaranteed approximation ratio. DOI: 10.33048/daio.2020.27.680 Viktor P. Il’ev 1,2 Received January 10, 2020 References[1] N. Bansal, A. Blum, and S. Chawla, Correlation clustering, Mach. Learn. 56 (1–3), 89–113 (2004).[2] T. Coleman, J. Saunderson, and A. Wirth, A local-search 2-approximation for 2-correlation-clustering, in Algorithms – ESA 2008 (Proc. 16th Annu. Eur. Symp., Karlsruhe, Germany, Sept. 15–17, 2008) (Springer, Heidelberg, 2008), pp. 308–319 (Lect. Notes Comput. Sci., Vol. 5193). [3] R. Shamir, R. Sharan, and D. Tsur, Cluster graph modification problems, Discrete Appl. Math. 144 (1–2), 173–182 (2004). [4] C. T. Zahn, Approximating symmetric relations by equivalence relations, J. Soc. Ind. Appl. Math. 12 (4), 840–847 (1964). [5] V. P. Il’ev and G. Š. Fridman, On the problem of approximation by graphs with a fixed number of components, Dokl. AN SSSR 264 (3), 533–538 (1982) [Russian] [Soviet Math. Dokl. 25 (3), 666–670 (1982)]. [6] A. A. Ageev, V. P. Il’ev, A. V. Kononov, and A. S. Talevnin, Computational complexity of the graph approximation problem, Diskretn. Anal. Issled. Oper., Ser. 1, 13 (1), 3–11 (2006) [Russian] [J. Appl. Ind. Math. 1 (1), 1–8 (2007)]. [7] I. Giotis and V. Guruswami, Correlation clustering with a fixed number of clusters, Theory Comput. 2 (1), 249–266 (2006). [8] O. Chapelle, B. Schölkopf, and A. Zein, Semi-Supervised Learning (MIT Press, Cambridge, MA, 2006). [9] E. Bair, Semi-supervised clustering methods, Wiley Interdiscip. Rev., Comput. Stat. 5 (5), 349–361 (2013). |
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