7 papers
Federated Bilevel Performative Prediction
Liangxin Qian, Chang Liu, Xuanyu Cao +2
Federated bilevel optimization is widely used for nested learning problems across distributed clients, such as federated hyperparameter tuning and meta-learning under privacy and c…
Resource Allocation for Stable LLM Training in Mobile Edge Computing
Chang Liu, Jun Zhao
As mobile devices increasingly become focal points for advanced applications, edge computing presents a viable solution to their inherent computational limitations, particularly in…
Resource Allocation in Large Language Model Integrated 6G Vehicular Networks
Chang Liu, Jun Zhao
In the upcoming 6G era, vehicular networks are shifting from simple Vehicle-to-Vehicle (V2V) communication to the more complex Vehicle-to-Everything (V2X) connectivity. At the fore…
User Connection and Resource Allocation Optimization in Blockchain Empowered Metaverse over 6G Wireless Communications
Liangxin Qian, Chang Liu, Jun Zhao
The convergence of blockchain, Metaverse, and non-fungible tokens (NFTs) brings transformative digital opportunities alongside challenges like privacy and resource management. Addr…
Transforms for Multiplicative and Fractional Programming with Broad Applications in Edge Computing and Communication Networks
Yitong Wang, Chang Liu, Jun Zhao
Multiplicative Programming (MP) pertains to a spectrum of optimization problems that involve product term(s). As computational paradigms of communication systems continue to evolve…
Optimization for the Metaverse over Mobile Edge Computing with Play to Earn
Chang Liu, Terence Jie Chua, Jun Zhao
The concept of the Metaverse has garnered growing interest from both academic and industry circles. The decentralization of both the integrity and security of digital items has spu…