4 papers
FUPareto: Bridging the Forgetting-Utility Gap in Federated Unlearning via Pareto Augmented Optimization
Zeyan Wang, Zhengmao Liu, Yongxin Cai +5
Federated Unlearning (FU) aims to efficiently remove the influence of specific client data from a federated model while preserving utility for the remaining clients. However, three…
Multi-Objective Large Language Model Unlearning
Zibin Pan, Shuwen Zhang, Yuesheng Zheng +3
Machine unlearning in the domain of large language models (LLMs) has attracted great attention recently, which aims to effectively eliminate undesirable behaviors from LLMs without…
Federated Unlearning with Gradient Descent and Conflict Mitigation
Zibin Pan, Zhichao Wang, Chi Li +4
Federated Learning (FL) has received much attention in recent years. However, although clients are not required to share their data in FL, the global model itself can implicitly re…
Coordinated Power Smoothing Control for Wind Storage Integrated System with Physics-informed Deep Reinforcement Learning
Shuyi Wang, Huan Zhao, Yuji Cao +4
The Wind Storage Integrated System with Power Smoothing Control (PSC) has emerged as a promising solution to ensure both efficient and reliable wind energy generation. However, exi…