output
20202024
most citedEnabling Trustworthy Federated Learning in Industrial IoT: Bridging the Gap Between Interpretability and Robustness

28 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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Showing 2024Show all

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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…

cs.CY2024★ 9 cited

The EAP-AIAS: Adapting the AI Assessment Scale for English for Academic Purposes

Jasper Roe, Mike Perkins, Yulia Tregubova

The rapid advancement of Generative Artificial Intelligence (GenAI) presents both opportunities and challenges for English for Academic Purposes (EAP) instruction. This paper propo…