1.5k citations · 3.2k across the 30 of their papers we have counts for
17 papers · 1 filter
Blockchain Assisted Decentralized Federated Learning (BLADE-FL) with Lazy Clients
Jun Li, Yumeng Shao, Ming Ding +4
Federated learning (FL), as a distributed machine learning approach, has drawn a great amount of attention in recent years. FL shows an inherent advantage in privacy preservation,…
Deep Reinforcement Learning for IoT Networks: Age of Information and Energy Cost Tradeoff
Xiongwei Wu, Xiuhua Li, Jun Li +2
In most Internet of Things (IoT) networks, edge nodes are commonly used as to relays to cache sensing data generated by IoT sensors as well as provide communication services for da…
When Federated Learning Meets Blockchain: A New Distributed Learning Paradigm
Chuan Ma, Jun Li, Ming Ding +4
Motivated by the explosive computing capabilities at end user equipments, as well as the growing privacy concerns over sharing sensitive raw data, a new machine learning paradigm,…
Caching Transient Content for IoT Sensing: Multi-Agent Soft Actor-Critic
Xiongwei Wu, Xiuhua Li, Jun Li +3
Edge nodes (ENs) in Internet of Things commonly serve as gateways to cache sensing data while providing accessing services for data consumers. This paper considers multiple ENs tha…
Multi-Agent Reinforcement Learning for Cooperative Coded Caching via Homotopy Optimization
Xiongwei Wu, Jun Li, Ming Xiao +2
Introducing cooperative coded caching into small cell networks is a promising approach to reducing traffic loads. By encoding content via maximum distance separable (MDS) codes, co…
Reconfigurable Intelligent Surface (RIS)-Enhanced Two-Way OFDM Communications
Chandan Pradhan, Ang Li, Lingyang Song +3
In this paper, we focus on the reconfigurable intelligent surface (RIS)-enhanced two-way device-to-device (D2D) multi-pair orthogonal-frequency-division-multiplexing (OFDM) communi…