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cs.LG2025
Closing the Generalization Gap in Parameter-efficient Federated Edge Learning
Xinnong Du, Zhonghao Lyu, Xiaowen Cao +3
Federated edge learning (FEEL) provides a promising foundation for edge artificial intelligence (AI) by enabling collaborative model training while preserving data privacy. However…
cs.IT2025
Integrated Sensing, Communication, and Computation for Over-the-Air Federated Edge Learning
Dingzhu Wen, Sijing Xie, Xiaowen Cao +4
This paper studies an over-the-air federated edge learning (Air-FEEL) system with integrated sensing, communication, and computation (ISCC), in which one edge server coordinates mu…