Apr 5, 2022 · We conduct an extensive empirical study spanning close to 1.5K unique configurations on five popular FL benchmarks.
[PDF] Empirical Analysis of Federated Learning in Heterogeneous ...
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Apr 8, 2022 · Abstract. Federated learning (FL) is becoming a popular paradigm for collaborative learning over distributed, private datasets.
Apr 19, 2022 · PDF | On Apr 5, 2022, Ahmed M. Abdelmoniem and others published Empirical analysis of federated learning in heterogeneous environments ...
An extensive empirical study spanning close to 1.5K unique configurations on five popular FL benchmarks shows that these sources of heterogeneity have a ...
We conduct an extensive empirical study spanning close to 1.5K unique configurations on five popular FL benchmarks.
Apr 8, 2022 · Abstract. Federated learning (FL) is becoming a popular paradigm for collaborative learning over distributed, private datasets.
A Comprehensive Empirical Study of Heterogeneity in Federated Learning
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Mar 7, 2023 · We conduct an extensive empirical study spanning nearly 1.5K unique configurations on five popular FL benchmarks.
Empirical analysis of federated learning in heterogeneous environments. https://doi.org/10.1145/3517207.3526969. Journal: Proceedings of the 2nd European ...
We aim to empirically characterize the impact of device and behavioral heterogeneity on the trained model.
Looking at these simulation results, it can be deduced that FedProx performs better in in- tense heterogeneous environments as compared to the. FedAvg algorithm ...