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Turdakov, Denis Yur'evich
Statistics Math-Net.Ru
Total publications: 27
Scientific articles: 26
Talks: 1

Number of views:
This page:917
Abstract pages:8568
Full texts:3819
Talk pages:540
Video records:86

https://www.mathnet.ru/eng/person124966
List of publications on Google Scholar
https://orcid.org/0000-0001-8745-0984

Publications in Math-Net.Ru Citations
2025
1. N. A. Eliseev, A. I. Perminov, D. Yu. Turdakov, “Convergence of a multilayer perceptron to histogram-based Bayesian regression”, Uspekhi Mat. Nauk, 80:6(486) (2025),  45–72  mathnet  mathscinet; Russian Math. Surveys, 80:6 (2025), 975–1002  isi  scopus
2. A. I. Perminov, A. P. Kovalenko, D. Yu. Turdakov, “Method for training perceptron on tabular data with missing values”, Proceedings of ISP RAS, 37:6(2) (2025),  93–106  mathnet
3. A. D. Sosnovikov, A. D. Zemerov, D. Yu. Turdakov, “Iterative weak supervision with LLM-guided labeling function refinement”, Proceedings of ISP RAS, 37:6(2) (2025),  65–76  mathnet
4. I. S. Alekseevskaia, D. V. Khaibullin, D. Yu. Turdakov, “Developing a defence for large language models against adversarial attacks based on paraphrasing in a black-box scenario”, Proceedings of ISP RAS, 37:5 (2025),  195–204  mathnet
5. K. S. Lukyanov, A. I. Perminov, D. Yu. Turdakov, M. A. Pautov, “Knowledge distillation in local-region for black-box adversarial examples”, Proceedings of ISP RAS, 37:4(2) (2025),  133–146  mathnet
2024
6. K. S. Lukyanov, P. A. Yaskov, A. I. Perminov, A. P. Kovalenko, D. Y. Turdakov, “Extrapolation of the Bayesian classifier with an unknown support of the two-class mixture distribution”, Uspekhi Mat. Nauk, 79:6(480) (2024),  57–82  mathnet  mathscinet; Russian Math. Surveys, 79:6 (2024), 991–1015  isi  scopus 3
7. I. S. Alekseevskaia, K. V. Arkhipenko, D. Yu. Turdakov, “Development of a red-teaming dataset for defending large language models against attacks”, Proceedings of ISP RAS, 36:5 (2024),  143–152  mathnet
8. A. D. Sosnovikov, D. Yu. Turdakov, “Automating the process of responding to a tax request using weak supervision”, Proceedings of ISP RAS, 36:3 (2024),  203–212  mathnet
9. Ph. A. Kolokolnikov, V. V. Orlov, D. Yu. Turdakov, “Prospects for using a trusted information analytical system based on the Talisman platform using artificial intelligence methods to improve the efficiency of complex hardware systems”, Proceedings of ISP RAS, 36:3 (2024),  105–122  mathnet
10. K. Lukyanov, M. Drobyshevskiy, D. Turdakov, “Detecting and eliminating covariate shifts in data for a more robust HDD failure prediction”, Zap. Nauchn. Sem. POMI, 540 (2024),  148–161  mathnet
2023
11. D. Shaikhelislamov, K. Lukyanov, N. Severin, M. Drobyshevskiy, I. Makarov, D. Turdakov, “A study of graph neural networks for link prediction on vulnerability to membership attacks”, Zap. Nauchn. Sem. POMI, 530 (2023),  113–127  mathnet; J. Math. Sci. (N. Y.), 285:2 (2024), 234–244 1
2022
12. D. Yu. Turdakov, A. I. Avetisyan, K. V. Arkhipenko, A. V. Antsiferova, D. S. Vatolin, S. S. Volkov, A. V. Gasnikov, D. A. Devyatkin, M. D. Drobyshevskiy, A. P. Kovalenko, M. I. Krivonosov, N. V. Lukashevich, V. A. Malykh, S. I. Nikolenko, I. V. Oseledets, A. I. Perminov, I. V. Sochenkov, M. M. Tihomirov, A. N. Fedotov, M. Yu. Khachay, “Trusted artificial intelligence: challenges and promising solutions”, Dokl. RAN. Math. Inf. Proc. Upr., 508 (2022),  13–18  mathnet  elib; Dokl. Math., 106:suppl. 1 (2022), S9–S13 4
13. R. K. Pastukhov, M. D. Drobyshevskiy, D. Yu. Turdakov, “Detecting influential users in social networks based on bipartite comments graph”, Proceedings of ISP RAS, 34:5 (2022),  127–142  mathnet
14. O. A. Mashkova, V. V. Shaklein, Yu. V. Markin, E. A. Karpulevitch, V. V. Ananev, A. A. Asatryan, Sh. T. Tigranyan, S. N. Skorik, D. Yu. Turdakov, “Methods for determining the elements of the PQRST-complex of the electrocardiogram”, Proceedings of ISP RAS, 34:4 (2022),  229–240  mathnet
15. A. I. Perminov, D. Yu. Turdakov, O. V. Belyaeva, “Loss functions for train document image segmentation models”, Proceedings of ISP RAS, 34:2 (2022),  89–110  mathnet
2021
16. V. V. Ananev, S. N. Skorik, V. V. Shaklein, A. A. Avetisyan, Y. E. Teregulov, D. Yu. Turdakov, V. Gliner, A. Schuster, E. A. Karpulevich, “Assessment of the impact of non-architectural changes in the predictive model on the quality of ECG classification”, Proceedings of ISP RAS, 33:4 (2021),  87–98  mathnet 1
2020
17. K. A. Skorniakov, A. S. Laskina, D. Yu. Turdakov, “Two step method for grouping news with similar topics”, Proceedings of ISP RAS, 32:4 (2020),  165–174  mathnet 1
18. P. K. Andreev, V. V. Ananev, V. A. Makarov, E. A. Karpulevich, D. Y. Turdakov, “Diagnosis of left atrial and left ventricular hypertrophies using a deep neural network”, Proceedings of ISP RAS, 32:4 (2020),  141–154  mathnet 1
2019
19. M. A. Ryndin, D. Y. Turdakov, “Domain adaptation by proactive labeling”, Proceedings of ISP RAS, 31:5 (2019),  145–152  mathnet 1
20. A. A. Avetisyan, M. D. Drobyshevskiy, D. Yu. Turdakov, “Methods for news items popularity estimation on early stages”, Proceedings of ISP RAS, 31:5 (2019),  137–144  mathnet
2018
21. A. A. Avetisyan, M. D. Drobyshevskiy, D. Yu. Turdakov, “Methods for information spread analysis”, Proceedings of ISP RAS, 30:6 (2018),  199–220  mathnet  elib 4
22. R. A. Gilyazev, D. U. Turdakov, “Active learning and crowdsourcing: a survey of annotation optimization methods”, Proceedings of ISP RAS, 30:2 (2018),  215–250  mathnet  elib 4
2016
23. Y. S. Trofimovich, I. S. Kozlov, D. Y. Turdakov, “Approaches to estimate location of social network users based on social graph”, Proceedings of ISP RAS, 28:6 (2016),  185–196  mathnet  elib 2
24. Mikhail Drobyshevskiy, Anton Korshunov, Denis Turdakov, “Parallel modularity computation for directed weighted graphs with overlapping communities”, Proceedings of ISP RAS, 28:6 (2016),  153–170  mathnet  elib 3
2015
25. A. Aleksiyants, O. Borisenko, D. Turdakov, A. Sher, S. Kuznetsov, “Implementing Apache Spark jobs execution and Apache Spark cluster creation for OpenStack Sahara”, Proceedings of ISP RAS, 27:5 (2015),  35–48  mathnet  elib 3
26. I. Andrianov, V. Mayorov, D. Turdakov, “Modern approaches to aspect-based sentiment analysis”, Proceedings of ISP RAS, 27:5 (2015),  5–22  mathnet  elib 5
2025
27. D. Yu. Turdakov, A. I. Avetisyan, “Giant component of truncated scale-free graphs: theory and applications to creation of datasets”, Uspekhi Mat. Nauk, 80:6(486) (2025),  184–186  mathnet  mathscinet; Russian Math. Surveys, 80:6 (2025), 1118–1120  isi  scopus

Presentations in Math-Net.Ru
1. Доверенный искусственный интеллект: современные направления и фундаментальные проблемы
A. I. Avetisyan, D. Yu. Turdakov

February 16, 2023 11:00   

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