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ETHNOS_APP

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Lanyu Yao

Dados Biográficos

ID10056585
NOMELanyu Yao
PRENOMESLanyu
SOBRENOMEYao
ASSINATURAYAO L
AFILIAÇÕESXidian University
VERIFICADONão
TOTAL DE OBRAS1
TOTAL DE CITAÇÕES0
TOTAL COMO AUTOR1
TOTAL COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2026
ANO MAIS RECENTE DE PUBLICAÇÃO2026
ÍNDICE H0
  • Towards Adaptive Personalized Federated Meta-Learning Recommendation

    Open Access•Shanfeng Wang, Shanyang Gao et al.•ARTICLE•IEEE Transactions on Computational…•2026

    Federated recommendation systems aim to provide high-quality recommendations while protecting user privacy. However, existing federated recommendation algorithms typically use a unified item embedding framework, where all clients share the same item representations. Such approaches often fail to capture users’ personalized perceptions of the same item and struggle to reflect subtle changes in user preferences, limiting the effectiveness of person…

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  • Towards Adaptive Personalized Federated Meta-Learning Recommendation

    Open Access•Shanfeng Wang, Shanyang Gao et al.•ARTICLE•IEEE Transactions on Computational…•2026

    Federated recommendation systems aim to provide high-quality recommendations while protecting user privacy. However, existing federated recommendation algorithms typically use a unified item embedding framework, where all clients share the same item representations. Such approaches often fail to capture users’ personalized perceptions of the same item and struggle to reflect subtle changes in user preferences, limiting the effectiveness of person…

Advanced Technologies in Various Fields (1 obra) · Collaborative filtering (1 obra) · Embedding (1 obra) · Federated learning (1 obra) · Limiting (1 obra) · Personalization (1 obra) · Privacy-Preserving Technologies in Data (1 obra) · Recommender system (1 obra) · Recommender Systems and Techniques (1 obra) · Statistical model (1 obra)

Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae