4 papers
Cost-Efficient Computation Offloading in SAGIN: A Deep Reinforcement Learning and Perception-Aided Approach
Yulan Gao, Ziqiang Ye, Han Yu
The Space-Air-Ground Integrated Network (SAGIN), crucial to the advancement of sixth-generation (6G) technology, plays a key role in ensuring universal connectivity, particularly b…
Fairness-Aware Multi-Server Federated Learning Task Delegation over Wireless Networks
Yulan Gao, Chao Ren, Han Yu
In the rapidly advancing field of federated learning (FL), ensuring efficient FL task delegation while incentivising FL client participation poses significant challenges, especiall…
Fairness-Aware Job Scheduling for Multi-Job Federated Learning
Yuxin Shi, Han Yu
Federated learning (FL) enables multiple data owners (a.k.a. FL clients) to collaboratively train machine learning models without disclosing sensitive private data. Existing FL res…
Multi-dimensional Fair Federated Learning
Cong Su, Guoxian Yu, Jun Wang +3
Federated learning (FL) has emerged as a promising collaborative and secure paradigm for training a model from decentralized data without compromising privacy. Group fairness and c…