Zobrazeno 1 - 10
of 160
pro vyhledávání: '"Philippe Lalanda"'
Pervasive computing promotes the integration of smart devices in our living spaces to develop services providing assistance to people. Such smart devices are increasingly relying on cloud-based Machine Learning, which raises questions in terms of sec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a3a37b26087c066d8aa155671e730524
http://arxiv.org/abs/2210.16918
http://arxiv.org/abs/2210.16918
Publikováno v:
2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c7f0b080a1d520bf7448967de2e5b2f9
https://doi.org/10.1109/isgt-europe54678.2022.9960593
https://doi.org/10.1109/isgt-europe54678.2022.9960593
Autor:
Philippe Lalanda
Publikováno v:
The Evolution of Pervasive Information Systems ISBN: 9783031181757
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a4801860d3e94faf6bd556e8daa4e92
https://doi.org/10.1007/978-3-031-18176-4_5
https://doi.org/10.1007/978-3-031-18176-4_5
Publikováno v:
2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::555056a176ec08b0e8095f9a3fdeb35a
https://doi.org/10.1109/percomworkshops53856.2022.9767288
https://doi.org/10.1109/percomworkshops53856.2022.9767288
Publikováno v:
2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops).
Federated Learning is a new machine learning paradigm dealing with distributed model learning on independent devices. One of the many advantages of federated learning is that training data stay on devices (such as smartphones), and only learned model
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::805712a94d4540384f4481e83eea5d75
https://doi.org/10.1109/percomworkshops53856.2022.9767369
https://doi.org/10.1109/percomworkshops53856.2022.9767369
Autor:
Philippe Lalanda
Publikováno v:
2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5481a297327a2b8fec389bcd44f3439c
https://doi.org/10.1109/percomworkshops53856.2022.9767408
https://doi.org/10.1109/percomworkshops53856.2022.9767408
Autor:
Philippe Lalanda, Catherine Hamon
Publikováno v:
CCF Transactions on Pervasive Computing and Interaction. 2:206-217
The purpose of this paper is to present an edge pervasive platform supporting the development, deployment and management of flexible, context-aware pervasive applications. This platform, named iCasa, is built on top of the OSGi/iPOJO service-oriented
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e6b0e04254951ba99417f4c055a25524
https://doi.org/10.1007/s42486-020-00046-y
https://doi.org/10.1007/s42486-020-00046-y
Publikováno v:
HAL
Federated Learning has been introduced as a new machine learning paradigm enhancing the use of local devices. At a server level, FL regularly aggregates models learned locally on distributed clients to obtain a more general model. Current solutions r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fbb294c277ad4b4f801a5cc87454cafc
Federated Learning has been introduced as a new machine learning paradigm enhancing the use of local devices. At a server level, FL regularly aggregates models learned locally on distributed clients to obtain a more general model. In this way, no pri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1eccdc9d2031945e978867f346a49bb
Publikováno v:
IFIP Advances in Information and Communication Technology ISBN: 9783030965914
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::06308bbd88def3b29d1d3257b6b9ce80
https://doi.org/10.1007/978-3-030-96592-1_11
https://doi.org/10.1007/978-3-030-96592-1_11