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FedLTLib

model1 events
papersTODAY 04:00 UTC

FedLTLib Benchmark Targets Federated Learning on Long-Tail Data

Researchers introduced FedLTLib, a benchmark suite for federated learning in settings where data across clients follows a long-tailed distribution. The work addresses real-world mobile and edge deployments, where privacy constraints keep data decentralized and class frequencies are highly uneven. The benchmark aims to standardize evaluation of methods designed for this combination of challenges.

federated-learning/benchmark/long-tail/privacy