Personalized federated learning: A meta-learning approach

A Fallah, A Mokhtari, A Ozdaglar - arXiv preprint arXiv:2002.07948, 2020 - arxiv.org
In Federated Learning, we aim to train models across multiple computing units (users), while
users can only communicate with a common central server, without exchanging their data …
被引用次数：593 相关文章

Personalized Federated Learning: A Meta-Learning Approach

A Fallah, A Mokhtari, A Ozdaglar - arXiv e-prints, 2020 - ui.adsabs.harvard.edu
Abstract In Federated Learning, we aim to train models across multiple computing units
(users), while users can only communicate with a common central server, without …
[PDF] researchgate.net

[PDF][PDF] Personalized Federated Learning: A Meta-Learning Approach

A Fallah, A Mokhtari, A Ozdaglar - arXiv preprint arXiv:2002.07948, 2020 - researchgate.net
Abstract In Federated Learning, we aim to train models across multiple computing units
(users), while users can only communicate with a common central server, without …
[PDF] academia.edu

[PDF][PDF] Personalized Federated Learning: A Meta-Learning Approach

A Fallah, A Mokhtari, A Ozdaglar - academia.edu
The goal of federated learning is to design algorithms in which several agents communicate
with a central node, in a privacy-protecting manner, to minimize the average of their loss …
[PDF] researchgate.net

[PDF][PDF] Personalized Federated Learning: A Meta-Learning Approach

A Fallah, A Mokhtari, A Ozdaglar - researchgate.net
The goal of federated learning is to design algorithms in which several agents communicate
with a central node, in a privacy-protecting manner, to minimize the average of their loss …