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Publications in Math-Net.Ru
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Complexity of some problems of quadratic partitioning of a finite set of points in Euclidean space into balanced clusters
Zh. Vychisl. Mat. Mat. Fiz., 60:1 (2020), 151–158
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Exact algorithms of searching for the largest size cluster in two integer 2-clustering problems
Sib. Zh. Vychisl. Mat., 22:2 (2019), 121–136
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Quadratic Euclidean 1-Mean and 1-Median 2-Clustering Problem with Constraints on the Size of the Clusters: Complexity and Approximability
Trudy Inst. Mat. i Mekh. UrO RAN, 25:4 (2019), 69–78
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Polynomial-time solvability of the one-dimensional case of an NP-hard clustering problem
Zh. Vychisl. Mat. Mat. Fiz., 59:9 (2019), 1617–1625
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Randomized algorithms for some hard-to-solve problems of clustering a finite set of points in Euclidean space
Zh. Vychisl. Mat. Mat. Fiz., 59:5 (2019), 895–904
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On the Complexity of Some Max–Min Clustering Problems
Trudy Inst. Mat. i Mekh. UrO RAN, 24:4 (2018), 189–198
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A randomized algorithm for a sequence 2-clustering problem
Zh. Vychisl. Mat. Mat. Fiz., 58:12 (2018), 2169–2178
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Exact pseudopolynomial algorithm for one sequence partitioning problem
Avtomat. i Telemekh., 2017, no. 1, 80–90
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Approximation algorithm for the problem of partitioning a sequence into clusters
Zh. Vychisl. Mat. Mat. Fiz., 57:8 (2017), 1392–1400
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Fully polynomial-time approximation scheme for a sequence $2$-clustering problem
Diskretn. Anal. Issled. Oper., 23:2 (2016), 21–40
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An approximation algorithm for the problem of partitioning a sequence into clusters with constraints on their cardinalities
Trudy Inst. Mat. i Mekh. UrO RAN, 22:3 (2016), 144–152
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Fully polynomial-time approximation scheme for a special case of a quadratic Euclidean 2-clustering problem
Zh. Vychisl. Mat. Mat. Fiz., 56:2 (2016), 332–340
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An exact pseudopolynomial algorithm for a bi-partitioning problem
Diskretn. Anal. Issled. Oper., 22:4 (2015), 50–62
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A randomized algorithm for two-cluster partition of a set of vectors
Zh. Vychisl. Mat. Mat. Fiz., 55:2 (2015), 335–344
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A $2$-approximation polynomial algorithm for one clustering problem
Diskretn. Anal. Issled. Oper., 20:4 (2013), 36–45
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