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Dmitry Namiot,Eugene Ilyushin
Pág. 60 - 69
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Dmitry Namiot,Eugene Ilyushin
Pág. 126 - 134
In the modern interpretation, artificial intelligence systems are machine learning systems. Often this is even further narrowed down to artificial neural networks. The robustness of machine learning systems has traditionally been considered as the main i...
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Dmitry Namiot,Eugene Ilyushin,Ivan Chizhov
Pág. 135 - 147
In this article, we consider the relationship between artificial intelligence systems and cybersecurity. In the modern interpretation, artificial intelligence systems are machine learning systems, sometimes it is even more narrowed down to artificial neu...
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Dmitry Namiot,Eugene Ilyushin
Pág. 84 - 93
The fundamental moment of the operation of machine learning systems is that the models are trained on some selected training data set. Accordingly, the generalizations obtained at the training stage are due to the characteristics of some subset of the ge...
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Dmitry Namiot,Eugene Ilyushin
Pág. 101 - 118
This article, written for the Robust Machine Learning Curriculum, discusses the so-called Generative Models in Machine Learning. Generative models learn the distribution of data from some sample data set and then can generate (create) new data instances....
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Dmitry Namiot,Eugene Ilyushin,Oleg Pilipenko
Pág. 119 - 127
The development and use of artificial intelligence systems (machine learning) in critical areas (avionics, autonomous movement, etc.) inevitably raise the question of the reliability of the software used. Trusted computing systems have been around for a ...
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Dmitry Namiot,Eugene Ilyushin,Ivan Chizhov
Pág. 30 - 34
The paper deals with the issues of formal verification of machine learning systems. With the growth of the introduction of systems based on machine learning in the so-called critical systems (systems with a very high cost of erroneous decisions and actio...
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Eugene Ilyushin,Dmitry Namiot,Ivan Chizhov
Pág. 17 - 22
The paper deals with the problem of adversarial attacks on machine learning systems. Such attacks are understood as special actions on the elements of the machine learning pipeline (training data, the model itself, test data) in order to either achieve t...
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Dmitry Namiot,Eugene Ilyushin,Ivan Chizhov
Pág. 69 - 76
This article is devoted to the applied aspects of the application of machine learning systems. It is obvious that the areas of practical applications of this kind of solution are constantly increasing. The main driver here is that, from a practical point...
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Bulat Nutfullin,Eugene Ilyushin
Pág. 14 - 20
Speech is a specific feature of human and his advantage over other species within evolution. Sound diarization is a process of sound separation, taking into account belonging to the speaker. Before the advent of deep learning and the ...
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