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pro vyhledávání: '"Sbihi, Mohammed"'
It is well established that to ensure or certify the robustness of a neural network, its Lipschitz constant plays a prominent role. However, its calculation is NP-hard. In this note, by taking into account activation regions at each layer as new cons
Externí odkaz:
http://arxiv.org/abs/2402.01199
Autor:
Bouabdallaoui, Ibrahim, Guerouate, Fatima, Bouhaddour, Samya, Saadi, Chaimae, Sbihi, Mohammed
Undoubtedly that the Bidirectional Encoder representations from Transformers is the most powerful technique in making Natural Language Processing tasks such as Named Entity Recognition, Question & Answers or Sentiment Analysis, however, the use of tr
Externí odkaz:
http://arxiv.org/abs/2312.07797
Autor:
Sbihi, Mohammed, Couellan, Nicolas
We address the issue of binary classification in Banach spaces in presence of uncertainty. We show that a number of results from classical support vector machines theory can be appropriately generalised to their robust counterpart in Banach spaces. T
Externí odkaz:
http://arxiv.org/abs/2202.08567
Autor:
Askoura, Youcef, Sbihi, Mohammed
We prove a conditional expectation bang-bang principle. Based on properties of the conditional expectation vector measure, we establish that the conditional expectation of a set-valued mapping coincides with the conditional expectation of the set of
Externí odkaz:
http://arxiv.org/abs/2201.13196
Akademický článek
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Publikováno v:
In Transportation Research Part C April 2023 149
Publikováno v:
In Computers & Industrial Engineering March 2023 177
Theoretical aspects of robust SVM optimization in Banach spaces and Nash equilibrium interpretation.
Autor:
Sbihi, Mohammed, Couellan, Nicolas
Publikováno v:
Annals of Mathematics & Artificial Intelligence; Oct2024, Vol. 92 Issue 5, p1273-1293, 21p
Publikováno v:
In Transportation Research Part C November 2021 132
Publikováno v:
In Procedia CIRP 2021 99:139-144