3 citations · 3 across the 8 of their papers we have counts for
4 papers · 1 filter
Providing Differential Privacy for Federated Learning Over Wireless: A Cross-layer Framework
Jiayu Mao, Tongxin Yin, Aylin Yener +1
Federated Learning (FL) is a distributed machine learning framework that inherently allows edge devices to maintain their local training data, thus providing some level of privacy.…
Adaptive Personalized Over-the-Air Federated Learning with Reflecting Intelligent Surfaces
Jiayu Mao, Aylin Yener
Over-the-air federated learning (OTA-FL) unifies communication and model aggregation by leveraging the inherent superposition property of the wireless medium. This strategy can ena…
ProFL: Performative Robust Optimal Federated Learning
Xue Zheng, Tian Xie, Xuwei Tan +2
Performative prediction is a framework that captures distribution shifts that occur during the training of machine learning models due to their deployment. As the trained model is…
Personalized Over-the-Air Federated Learning with Personalized Reconfigurable Intelligent Surfaces
Jiayu Mao, Aylin Yener
Over-the-air federated learning (OTA-FL) provides bandwidth-efficient learning by leveraging the inherent superposition property of wireless channels. Personalized federated learni…