1 citations · 1 across the 5 of their papers we have counts for
7 papers
Decentralized Dynamic Cooperation of Personalized Models for Federated Continual Learning
Danni Yang, Zhikang Chen, Sen Cui +6
Federated continual learning (FCL) has garnered increasing attention for its ability to support distributed computation in environments with evolving data distributions. However, t…
RSMA-Enhanced Data Collection in RIS-Assisted Intelligent Consumer Transportation Systems
Chunjie Wang, Xuhui Zhang, Wenchao Liu +5
This paper investigates the data collection enhancement problem in a reconfigurable intelligent surface (RIS)-empowered intelligent consumer transportation system (ICTS). We propos…
Joint Beamforming Design for RIS-Empowered NOMA-ISAC Systems
Chunjie Wang, Xuhui Zhang, Jinke Ren +6
This paper investigates a reconfigurable intelligent surface (RIS)-assisted integrated sensing and communication (ISAC) system and proposes a joint communication and sensing beamfo…
Adaptive Pruning for Large Language Models with Structural Importance Awareness
Haotian Zheng, Jinke Ren, Yushan Sun +6
The recent advancements in large language models (LLMs) have significantly improved language understanding and generation capabilities. However, it is difficult to deploy LLMs on r…
Hierarchical Learning for IRS-Assisted MEC Systems with Rate-Splitting Multiple Access
Yinyu Wu, Xuhui Zhang, Yingchao Jiao +5
Intelligent reflecting surface (IRS)-assisted mobile edge computing (MEC) systems have shown notable improvements in efficiency, such as reduced latency, higher data rates, and bet…
Scalable Federated Unlearning via Isolated and Coded Sharding
Yijing Lin, Zhipeng Gao, Hongyang Du +4
Federated unlearning has emerged as a promising paradigm to erase the client-level data effect without affecting the performance of collaborative learning models. However, the fede…
Blockchain-enabled Trustworthy Federated Unlearning
Yijing Lin, Zhipeng Gao, Hongyang Du +3
Federated unlearning is a promising paradigm for protecting the data ownership of distributed clients. It allows central servers to remove historical data effects within the machin…