Federated Unlearning and Its Privacy Threats Federated unlearning has emerged very recently as an attempt to realize "the right to be forgotten" in the context of federated learning. While the current... WangFei,LiBaochun,LiBo - 《IEEE Network》 被引量: 0发表: 2024年 Preserving Individual User...
联邦学习在ICLR 2023会议中的论文清单 [1]如下: A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy作者 Kaan Ozkara 作者 Antonious M. Girgis 作…
Fast Federated Machine Unlearning with Nonlinear Functional Theory Efficient Personalized Federated Learning via Sparse Model-Adaptation Alibaba code DoCoFL: Downlink Compression for Cross-Device Federated Learning VMware Research Private Federated Learning with Autotuned Compression Analysis of Error Feedback...
Additional security and privacy threats LLMs combined with FL could worsen security and privacy risks, creating new challenges. Existing FedLLM frameworks often overlook these issues. To the best of our knowledge, we are the first to analyze security and privacy threats in FedLLMs. According to ...
Taxonomy of Federated UnlearningWe outline the taxonomy for federated unlearning.Paper List of Federated UnlearningPrivacy (P1)Federated Unlearning and Its Privacy Threats (Fei Wang et al., IEEE Network 2023) 📖 FedRecovery: Differentially Private Machine Unlearning for Federated Learning Frameworks (...
Machine Unlearning of Federated Clusters University of Illinois Urbana-Champaign code FedFA: Federated Feature Augmentation ETH Zurich code Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach Carnegie Mellon University code Better Generative Replay for Continual Federated Learni...