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@article{SJVM_2017_20_1_a1, author = {A. E. Galashov and A. V. Kel'manov}, title = {On pseudopolynomial-time solvability of a~quadratic {Euclidean} problem of finding a~family of disjoint subsets}, journal = {Sibirskij \v{z}urnal vy\v{c}islitelʹnoj matematiki}, pages = {15--22}, publisher = {mathdoc}, volume = {20}, number = {1}, year = {2017}, language = {ru}, url = {http://geodesic.mathdoc.fr/item/SJVM_2017_20_1_a1/} }
TY - JOUR AU - A. E. Galashov AU - A. V. Kel'manov TI - On pseudopolynomial-time solvability of a~quadratic Euclidean problem of finding a~family of disjoint subsets JO - Sibirskij žurnal vyčislitelʹnoj matematiki PY - 2017 SP - 15 EP - 22 VL - 20 IS - 1 PB - mathdoc UR - http://geodesic.mathdoc.fr/item/SJVM_2017_20_1_a1/ LA - ru ID - SJVM_2017_20_1_a1 ER -
%0 Journal Article %A A. E. Galashov %A A. V. Kel'manov %T On pseudopolynomial-time solvability of a~quadratic Euclidean problem of finding a~family of disjoint subsets %J Sibirskij žurnal vyčislitelʹnoj matematiki %D 2017 %P 15-22 %V 20 %N 1 %I mathdoc %U http://geodesic.mathdoc.fr/item/SJVM_2017_20_1_a1/ %G ru %F SJVM_2017_20_1_a1
A. E. Galashov; A. V. Kel'manov. On pseudopolynomial-time solvability of a~quadratic Euclidean problem of finding a~family of disjoint subsets. Sibirskij žurnal vyčislitelʹnoj matematiki, Tome 20 (2017) no. 1, pp. 15-22. http://geodesic.mathdoc.fr/item/SJVM_2017_20_1_a1/
[1] Kelmanov A. V., Pyatkin A. V., “NP-polnota nekotorykh zadach vybora podmnozhestva vektorov”, Diskretnyi analiz i issledovanie operatsii, 17:5 (2010), 37–45 | MR | Zbl
[2] Galashov A. E., Kelmanov A. V., “2-priblizhennyi algoritm dlya odnoi zadachi poiska semeistva neperesekayuschikhsya podmnozhestv vektorov”, Avtomatika i telemekhanika, 2014, no. 4, 5–19 | MR | Zbl
[3] Aloise D., Deshpande A., Hansen P., Popat P., “NP-hardness of Euclidean sum-of-squares clustering”, Machine Learning, 75:2 (2009), 245–248 | DOI
[4] Jain A. K., “Data clustering: 50 years beyond K-means”, Pattern Recognition Lett., 31 (2010), 651–666 | DOI
[5] Edwards A. W. F., Cavalli-Sforza L. L., “A method for cluster analysis”, Biometrics, 21 (1965), 362–375 | DOI
[6] MacQueen J. B., “Some methods for classification and analysis of multivariate observations”, Proc. 5th Berkeley Symp. Math. Statist. Probability, v. 1, 1967, 281–297 | MR | Zbl
[7] Garey M. R., Johnson D. S., Computers and Intractability: A Guide to the Theory of NP-Completeness, Freeman, San Francisco, 1979 | MR | Zbl
[8] Kelmanov A. V., Romanchenko S. M., “Priblizhennyi algoritm resheniya odnoi zadachi poiska podmnozhestva vektorov”, Diskretnyi analiz i issledovanie operatsii, 18:1 (2011), 61–69 | MR | Zbl
[9] Kelmanov A. V., Romanchenko S. M., “Psevdopolinomialnye algoritmy dlya nekotorykh trudnoreshaemykh zadach poiska podmnozhestva vektorov i klasternogo analiza”, Avtomatika i telemekhanika, 2012, no. 2, 156–162 | Zbl
[10] Kelmanov A. V., Romanchenko S. M., “FPTAS dlya odnoi zadachi poiska podmnozhestva vektorov”, Diskretnyi analiz i issledovanie operatsii, 21:3 (2014), 41–52 | MR | Zbl
[11] Shenmaier V. V., “Approksimatsionnaya skhema dlya odnoi zadachi poiska podmnozhestva vektorov”, Diskretnyi analiz i issledovanie operatsii, 19:2 (2012), 92–100 | MR | Zbl
[12] Papadimitriou C. H., Steiglitz K., Combinatorial Optimization: Algorithms and Complexity, Prentice-Hall, Englewood Cliffs, N.J., 1982 | MR | Zbl
[13] Mollin R. A., Fundamental Number Theory with Applications, Second Edition, CRC Press, 2008 | MR | Zbl