most citedEnabling Trustworthy Federated Learning in Industrial IoT: Bridging the Gap Between Interpretability and Robustness

28 citations · 28 across the 1 of their papers we have counts for

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1 paper

cs.LG2024★ 28 cited

Enabling Trustworthy Federated Learning in Industrial IoT: Bridging the Gap Between Interpretability and Robustness

Senthil Kumar Jagatheesaperumal, Mohamed Rahouti, Ali Alfatemi +3

Federated Learning (FL) represents a paradigm shift in machine learning, allowing collaborative model training while keeping data localized. This approach is particularly pertinent…