July 20, 2022, 1:20 a.m. | Congzheng Song, Filip Granqvist, Kunal Talwar

cs.CR updates on arXiv.org arxiv.org

Cross-device federated learning is an emerging machine learning (ML) paradigm
where a large population of devices collectively train an ML model while the
data remains on the devices. This research field has a unique set of practical
challenges, and to systematically make advances, new datasets curated to be
compatible with this paradigm are needed. Existing federated learning
benchmarks in the image domain do not accurately capture the scale and
heterogeneity of many real-world use cases. We introduce FLAIR, a challenging …

federated learning lg repository

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