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Robust Personalized Federated Learning with Sparse Penalization*
Journal of the American Statistical Association ( IF 3.7 ) Pub Date : 2024-02-23 , DOI: 10.1080/01621459.2024.2321652 Weidong Liu 1 , Xiaojun Mao 2 , Xiaofei Zhang 3 , Xin Zhang 4
Journal of the American Statistical Association ( IF 3.7 ) Pub Date : 2024-02-23 , DOI: 10.1080/01621459.2024.2321652 Weidong Liu 1 , Xiaojun Mao 2 , Xiaofei Zhang 3 , Xin Zhang 4
Affiliation
Federated learning (FL) is an emerging topic due to its advantage in collaborative learning with distributed data. Due to the heterogeneity in the local data-generating mechanism, it is important t...
中文翻译：
具有稀疏惩罚的鲁棒个性化联合学习*
联邦学习（FL）因其在分布式数据协作学习方面的优势而成为一个新兴主题。由于本地数据生成机制的异构性，重要的是......
更新日期：2024-02-23
中文翻译：
具有稀疏惩罚的鲁棒个性化联合学习*
联邦学习（FL）因其在分布式数据协作学习方面的优势而成为一个新兴主题。由于本地数据生成机制的异构性，重要的是......
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