4 papers · 1 filter
Imperfect Digital Twin Assisted Low Cost Reinforcement Training for Multi-UAV Networks
Xiucheng Wang, Nan Cheng, Longfei Ma +3
Deep Reinforcement Learning (DRL) is widely used to optimize the performance of multi-UAV networks. However, the training of DRL relies on the frequent interactions between the UAV…
Effectively Heterogeneous Federated Learning: A Pairing and Split Learning Based Approach
Jinglong Shen, Xiucheng Wang, Nan Cheng +3
As a promising paradigm federated Learning (FL) is widely used in privacy-preserving machine learning, which allows distributed devices to collaboratively train a model while avoid…
Distilling Knowledge from Resource Management Algorithms to Neural Networks: A Unified Training Assistance Approach
Longfei Ma, Nan Cheng, Xiucheng Wang +3
As a fundamental problem, numerous methods are dedicated to the optimization of signal-to-interference-plus-noise ratio (SINR), in a multi-user setting. Although traditional model-…
Digital Twin-Assisted Knowledge Distillation Framework for Heterogeneous Federated Learning
Xiucheng Wang, Nan Cheng, Longfei Ma +3
In this paper, to deal with the heterogeneity in federated learning (FL) systems, a knowledge distillation (KD) driven training framework for FL is proposed, where each user can se…