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pro vyhledávání: '"Lukyanov, Kirill"'
The vulnerability of artificial neural networks to adversarial perturbations in the black-box setting is widely studied in the literature. The majority of attack methods to construct these perturbations suffer from an impractically large number of qu
Externí odkaz:
http://arxiv.org/abs/2410.15889
Publikováno v:
2022 Ivannikov Ispras Open Conference (ISPRAS), 2022, pp. 31-36
Social networks crawling is in the focus of active research the last years. One of the challenging task is to collect target nodes in an initially unknown graph given a budget of crawling steps. Predicting a node property based on its partially known
Externí odkaz:
http://arxiv.org/abs/2403.13865
Autor:
Pozdnyakov, Vitaliy, Kovalenko, Aleksandr, Makarov, Ilya, Drobyshevskiy, Mikhail, Lukyanov, Kirill
Publikováno v:
IEEE Open Journal of the Industrial Electronics Society, 5 (2024) 428-440
Integrating machine learning into Automated Control Systems (ACS) enhances decision-making in industrial process management. One of the limitations to the widespread adoption of these technologies in industry is the vulnerability of neural networks t
Externí odkaz:
http://arxiv.org/abs/2403.13502