Web: http://arxiv.org/abs/2201.06598

Jan. 21, 2022, 2:11 a.m. | Afra Mashhadi, Alex Kyllo, Reza M. Parizi

cs.LG updates on arXiv.org arxiv.org

Federated learning involves training statistical models over remote devices
such as mobile phones while keeping data localized. Training in heterogeneous
and potentially massive networks introduces opportunities for
privacy-preserving data analysis and diversifying these models to become more
inclusive of the population. Federated learning can be viewed as a unique
opportunity to bring fairness and parity to many existing models by enabling
model training to happen on a diverse set of participants and on data that is
generated regularly and dynamically. …

applications arxiv fairness federated learning learning

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