753 citations · 4.3k across the 89 of their papers we have counts for
7 papers · 1 filter
Distributed Multi-agent Meta Learning for Trajectory Design in Wireless Drone Networks
Ye Hu, Mingzhe Chen, Walid Saad +2
In this paper, the problem of the trajectory design for a group of energy-constrained drones operating in dynamic wireless network environments is studied. In the considered model,…
UVeQFed: Universal Vector Quantization for Federated Learning
Nir Shlezinger, Mingzhe Chen, Yonina C. Eldar +2
Traditional deep learning models are trained at a centralized server using labeled data samples collected from end devices or users. Such data samples often include private informa…
Meta-Reinforcement Learning for Trajectory Design in Wireless UAV Networks
Ye Hu, Mingzhe Chen, Walid Saad +2
In this paper, the design of an optimal trajectory for an energy-constrained drone operating in dynamic network environments is studied. In the considered model, a drone base stati…
Convergence Time Optimization for Federated Learning over Wireless Networks
Mingzhe Chen, H. Vincent Poor, Walid Saad +1
In this paper, the convergence time of federated learning (FL), when deployed over a realistic wireless network, is studied. In particular, a wireless network is considered in whic…
Voting-Based Multi-Agent Reinforcement Learning for Intelligent IoT
Yue Xu, Zengde Deng, Mengdi Wang +3
The recent success of single-agent reinforcement learning (RL) in Internet of things (IoT) systems motivates the study of multi-agent reinforcement learning (MARL), which is more c…
Load Balancing for Ultra-Dense Networks: A Deep Reinforcement Learning Based Approach
Yue Xu, Wenjun Xu, Zhi Wang +2
In this paper, we propose a deep reinforcement learning (DRL) based mobility load balancing (MLB) algorithm along with a two-layer architecture to solve the large-scale load balanc…