Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Confidentialité différentielle"'
Autor:
Sun, Jia Ao
Nous présentons une nouvelle approche de préservation de la vie privée pour améliorer l’équité des éléments dans les systèmes de classement. Nous utilisons des techniques de post-traitement dans un environnement de recommandation multipart
Externí odkaz:
http://hdl.handle.net/1866/32003
Autor:
Mo, Fengran
Dans les applications de traitement du langage naturel (NLP), la formation d’un modèle efficace nécessite souvent une quantité massive de données. Cependant, les données textuelles dans le monde réel sont dispersées dans différentes institu
Externí odkaz:
http://hdl.handle.net/1866/27948
Autor:
Ryffel, Théo
Publikováno v:
Computer Science [cs]. ENS Paris-Ecole Normale Supérieure de Paris, 2022. English. ⟨NNT : ⟩
The ever growing use of machine learning (ML), motivated by the possibilities it brings to a large number of sectors, is increasingly raising questions because of the sensitive nature of the data that must be used and the lack of transparency on the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______165::6f0ccccab48ce070a0970d4ce91787b4
https://hal.science/tel-04005263/file/Theo_Ryffel_Phd_Thesis_Manuscript_VDEF.pdf
https://hal.science/tel-04005263/file/Theo_Ryffel_Phd_Thesis_Manuscript_VDEF.pdf
Autor:
Sabater, César
Publikováno v:
Machine Learning [cs.LG]. Université de Lille, 2022. English. ⟨NNT : ⟩
Machine Learning [cs.LG]. Université de Lille, 2022. English. ⟨NNT : 2022ULILB010⟩
Machine Learning [cs.LG]. Université de Lille, 2022. English. ⟨NNT : 2022ULILB010⟩
In recent years, the concern for privacy has significantly grown. This is a consequence of the regular use of data-intensive services that require the massive outsourcing and processing of individuals data, which is often sensitive. For that reason,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::3210f6c82a8f25a77c36eb24109ee169
https://inria.hal.science/tel-03904039/file/main.pdf
https://inria.hal.science/tel-03904039/file/main.pdf
Autor:
Sabater, C. (César)
Ces dernières années, la préoccupation pour la protection de la vie privée s'est considérablement accrue. Cela s'explique par l'utilisation régulière de services qui nécessitent l'externalisation et le traitement massif de données personnell
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::2f87f0b4d23f60b9e2d0bf1be13be94f
http://hdl.handle.net/20.500.12210/80025
http://hdl.handle.net/20.500.12210/80025
Autor:
Kerkouche, Raouf
Publikováno v:
Performance [cs.PF]. Université Grenoble Alpes [2020-..], 2021. English. ⟨NNT : 2021GRALM023⟩
In Machine Learning, several entities may want to collaborate in order to improve their local model accuracy. In traditional machine learning, such collaboration requires to first store all entities’ data on a centralized server before training the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::d133f30b3a2d7e7910348d6268e0f632
https://tel.archives-ouvertes.fr/tel-03467131
https://tel.archives-ouvertes.fr/tel-03467131
Autor:
Fernandes, Natasha
Publikováno v:
Information Theory [cs.IT]. École Polytechnique Paris; Macquarie University, 2021. English
Information Theory [cs.IT]. Institut Polytechnique de Paris; Macquarie university (Sydney, Australie), 2021. English. ⟨NNT : 2021IPPAX030⟩
Information Theory [cs.IT]. Institut Polytechnique de Paris; Macquarie university (Sydney, Australie), 2021. English. ⟨NNT : 2021IPPAX030⟩
The problem of data privacy - protecting sensitive or personal data from discovery - has been a long-standing research issue. In this regard, differential privacy, introduced in 2006, is considered to be the gold standard. Differential privacy was de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e6d2d4d3c50e9ad30dbd3e29cb5fe48
https://tel.archives-ouvertes.fr/tel-03344320/file/ThesisFinalSubmission_Natasha_Fernandes_LIX.pdf
https://tel.archives-ouvertes.fr/tel-03344320/file/ThesisFinalSubmission_Natasha_Fernandes_LIX.pdf
Autor:
Leukam Lako, Franklin
Publikováno v:
Réseaux et télécommunications [cs.NI]. Institut Polytechnique de Paris, 2021. Français. ⟨NNT : 2021IPPAS004⟩
Smart grids are important bricks in the fight against climate change. Smart grids allow the massive introduction of renewable energies, which are intermittent, while guaranteeing grid stability, i.e., ensuring a real-time balance between demand and p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::42ae9d8efef014f8d3ccfcdfa3a3dcff
https://tel.archives-ouvertes.fr/tel-03249688
https://tel.archives-ouvertes.fr/tel-03249688
Autor:
Chatalic, Antoine
Publikováno v:
Machine Learning [cs.LG]. Université Rennes 1, 2020. English. ⟨NNT : 2020REN1S030⟩
Machine Learning [cs.LG]. Université de rennes 1, 2020. English
Machine Learning [cs.LG]. Université de rennes 1, 2020. English
The topic of this Ph.D. thesis lies on the borderline between signal processing, statistics and computer science. It mainly focuses on compressive learning, a paradigm for large-scale machine learning in which the whole dataset is compressed down to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::015d53c79cf8589423e7590ba5e33ed8
https://theses.hal.science/tel-03023287v2/document
https://theses.hal.science/tel-03023287v2/document
Autor:
Duguépéroux, Joris
Publikováno v:
Other [cs.OH]. Université Rennes 1, 2020. English. ⟨NNT : 2020REN1S023⟩
This work focuses on protecting workers in a crowdsourcing context. Indeed, workers are especially vulnerable in online work, and both surveillance from platforms and lack of regulation are frequently denounced for endangering them. Our first contrib
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a01f13dfd1df74a25aa8cf08ad2f9369
https://tel.archives-ouvertes.fr/tel-03099278/file/DUGUEPEROUX_Joris.pdf
https://tel.archives-ouvertes.fr/tel-03099278/file/DUGUEPEROUX_Joris.pdf