Cargando…
Federated Learning for Privacy-Aware Human Mobility Modeling
Human mobility modeling is a complex yet essential subject of study related to modeling important spatiotemporal events, including traffic, disease spreading, and customized directions and recommendations. While spatiotemporal data can be collected easily via smartphones, current state-of-the-art de...
Autores principales: | Ezequiel, Castro Elizondo Jose, Gjoreski, Martin, Langheinrich, Marc |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273827/ https://www.ncbi.nlm.nih.gov/pubmed/35837615 http://dx.doi.org/10.3389/frai.2022.867046 |
Ejemplares similares
-
In the Pursuit of Privacy: The Promises and Predicaments of Federated Learning in Healthcare
por: Topaloglu, Mustafa Y., et al.
Publicado: (2021) -
AI Technologies, Privacy, and Security
por: Elliott, David, et al.
Publicado: (2022) -
A framework for the prediction of earthquake using federated learning
por: Tehseen, Rabia, et al.
Publicado: (2021) -
A federated learning framework based on transfer learning and knowledge distillation for targeted advertising
por: Su, Caiyu, et al.
Publicado: (2023) -
A systematic review of security and privacy issues in the internet of medical things; the role of machine learning approaches
por: Hameed, Shilan S., et al.
Publicado: (2021)