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  1. Model and Method for Constructing a Heterogeneous Cluster Ensemble

    Berikov, V. B., 2022, In: Automation and Remote Control. 83, 12, p. 1944-1958 15 p.

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

  2. Multi-spectral image recognition using solution trees based on similarity

    Berikov, V. B., Pestunov, I. A., Kozinets, R. M. & Rylov, S. A., 12 Jan 2020, In: CEUR Workshop Proceedings. 2534, p. 260-266 7 p.

    Research output: Contribution to journal › Conference article › peer-review

  3. Multi-target Weakly Supervised Regression Using Manifold Regularization and Wasserstein Metric

    Kalmutskiy, K., Cherikbayeva, L., Litvinenko, A. & Berikov, V., 2023, Communications in Computer and Information Science. Springer, p. 364-375 12 p. (Communications in Computer and Information Science; vol. 1881 CCIS).

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

  4. Non-canonical maximum cliques without a design structure in the block graphs of 2-designs

    Goryainov, S. & Konstantinova, E. V., Nov 2024, In: Designs, Codes, and Cryptography. 92, 11, p. 3665-3675 11 p.

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

  5. Non-Clairvoyant Makespan Minimization Scheduling with Predictions

    Bampis, E., Кононов, А. В., Lucarelli, G. & Pascual, F., Dec 2023, Leibniz International Proceedings in Informatics, LIPIcs. Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, Vol. 283. 15 p. 9. (Leibniz International Proceedings in Informatics, LIPIcs; vol. 283).

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

  6. NP-Completeness of Some Problems of Partitioning a Finite Set of Points in Euclidean Space into Balanced Clusters

    Kel’manov, A. V., Pyatkin, A. V. & Khandeev, V. I., 1 Sept 2019, In: Doklady Mathematics. 100, 2, p. 416-419 4 p.

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

  7. NP-Hardness of 1-Mean and 1-Medoid 2-Clustering Problem with Arbitrary Clusters Sizes

    Pyatkin, A. V., 2021, Mathematical Optimization Theory and Operations Research: Recent Trends - 20th International Conference, MOTOR 2021, Revised Selected Papers. Strekalovsky, A., Kochetov, Y., Gruzdeva, T. & Orlov, A. (eds.). Springer, p. 248-256 9 p. (Communications in Computer and Information Science; vol. 1476 CCIS).

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

  8. NP-Hardness of balanced minimum sum-of-squares clustering

    Pyatkin, A., Aloise, D. & Mladenović, N., 1 Oct 2017, In: Pattern Recognition Letters. 97, p. 44-45 2 p.

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

  9. NP-hardness of quadratic euclidean 1-mean and 1-median 2-clustering problem with constraints on the cluster sizes

    Kel’manov, A. V., Pyatkin, A. V. & Khandeev, V. I., Nov 2019, In: Doklady Mathematics. 100, 3, p. 545-548 4 p.

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

  10. NP-Hardness of Some Data Cleaning Problem

    Kutnenko, O. A. & Plyasunov, A. V., Apr 2021, In: Journal of Applied and Industrial Mathematics. 15, 2, p. 285-291 7 p.

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

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