7 citations · 13 across the 7 of their papers we have counts for
7 papers
Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning
Bokeng Zheng, Bo Rao, Tianxiang Zhu +5
Advances in artificial intelligence (AI) including foundation models (FMs), are increasingly transforming human society, with smart city driving the evolution of urban living.Meanw…
Deep Unfolding of Fixed-Point Based Algorithm for Weighted Sum Rate Maximization
Jan Christian Hauffen, Chee Wei Tan, Giuseppe Caire
In this paper, we propose a novel approach that harnesses the standard interference function, specifically tailored to address the unique challenges of non-convex optimization in w…
FedReMa: Improving Personalized Federated Learning via Leveraging the Most Relevant Clients
Han Liang, Ziwei Zhan, Weijie Liu +3
Federated Learning (FL) is a distributed machine learning paradigm that achieves a globally robust model through decentralized computation and periodic model synthesis, primarily f…
Efficient Federated Unlearning with Adaptive Differential Privacy Preservation
Yu Jiang, Xindi Tong, Ziyao Liu +3
Federated unlearning (FU) offers a promising solution to effectively address the need to erase the impact of specific clients' data on the global model in federated learning (FL),…
FedUHB: Accelerating Federated Unlearning via Polyak Heavy Ball Method
Yu Jiang, Chee Wei Tan, Kwok-Yan Lam
Federated learning facilitates collaborative machine learning, enabling multiple participants to collectively develop a shared model while preserving the privacy of individual data…
Towards Efficient and Certified Recovery from Poisoning Attacks in Federated Learning
Yu Jiang, Jiyuan Shen, Ziyao Liu +2
Federated learning (FL) is vulnerable to poisoning attacks, where malicious clients manipulate their updates to affect the global model. Although various methods exist for detectin…