Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Towards securing machine learning models against membership inference attacks

Autor: Sana Belguith, Adeeb Alhomoud, Abderrazak Jemai, S Ben Hamida, Hichem Mrabet

From fraud detection to speech recognition, including price prediction,\ud Machine Learning (ML) applications are manifold and can significantly improve\ud different areas. Nevertheless, machine learning models are vulnerable and are\ud exposed to di

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a9a3b1f649555370aa54d38020a0995
https://usir.salford.ac.uk/id/eprint/61405/8/TSP_CMC_44945.pdf

Mu opioid receptors in the medial habenula contribute to naloxone aversion

Autor: Emmanuel Darcq, M. Maitra, Aliza T. Ehrlich, Brigitte L. Kieffer, S. Ben Hamida, Laura-Joy Boulos, Julie Bailly, Claire Gaveriaux-Ruff

Publikováno v: Neuropsychopharmacology
Neuropsychopharmacology, 2019, 45 (2), pp.247-255. ⟨10.1038/s41386-019-0395-7⟩

The medial habenula (MHb) is considered a brain center regulating aversive states. The mu opioid receptor (MOR) has been traditionally studied at the level of nociceptive and mesolimbic circuits, for key roles in pain relief and reward processing. MO

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::93e4f5d55d53faf74c57865697216a94
https://doi.org/10.1038/s41386-019-0395-7

Bi-Objective CSO for Big Data Scientific Workflows Scheduling in the Cloud: Case of LIGO Workflow

Autor: Khadija Bousselmi, Marta Rukoz, S. Ben Hamida

Publikováno v: 15th International Conference on Software Technologies
15th International Conference on Software Technologies, Jul 2020, Lieusaint-Paris, France. pp.615-624, ⟨10.5220/0009827106150624⟩
Proceedings of the 15th International Conference on Software Technologies (ICSOFT 2020)
ICSOFT

International audience; Scientific workflows are used to model scalable, portable, and reproducible big data analyses and scientific experiments with low development costs. To optimize their performances and ensure data resources efficiency, scientif

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d1278f2da03b109955794784444ae42
https://hal.archives-ouvertes.fr/hal-03282507

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.