FedVoting: A Cross-Silo Boosting Tree Construction Method for Privacy-Preserving Long-Term Human Mobility Prediction.

Liu, Yinghao; Fan, Zipei; Song, Xuan; Shibasaki, Ryosuke

Liu, Yinghao; Fan, Zipei; Song, Xuan; Shibasaki, Ryosuke.

Afiliação

Liu Y; Center of Spatial Information Sciences, The University of Tokyo, Kashiwanoha 5 Chome-1-5, Kashiwa 277-0882, Japan.
Fan Z; Center of Spatial Information Sciences, The University of Tokyo, Kashiwanoha 5 Chome-1-5, Kashiwa 277-0882, Japan.
Song X; SUSTech-UTokyo Joint Research Center on Super Smart City, Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen 518055, China.
Shibasaki R; Center of Spatial Information Sciences, The University of Tokyo, Kashiwanoha 5 Chome-1-5, Kashiwa 277-0882, Japan.

Sensors (Basel) ; 21(24)2021 Dec 10.

Article em En | MEDLINE | ID: mdl-34960376

Assuntos

Privacidade; Projetos de Pesquisa; Humanos; Política

Palavras-chave

GPS; differential privacy; federated learning; gradient-boosting decision tree; long-term human mobility prediction; privacy protection

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Projetos de Pesquisa / Privacidade Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Japão

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