54 citations · 341 across the 72 of their papers we have counts for
6 papers · 1 filter
Adaptive Federated Pruning in Hierarchical Wireless Networks
Xiaonan Liu, Shiqiang Wang, Yansha Deng +1
Federated Learning (FL) is a promising privacy-preserving distributed learning framework where a server aggregates models updated by multiple devices without accessing their privat…
Federated Learning and Meta Learning: Approaches, Applications, and Directions
Xiaonan Liu, Yansha Deng, Arumugam Nallanathan +1
Over the past few years, significant advancements have been made in the field of machine learning (ML) to address resource management, interference management, autonomy, and decisi…
Time-triggered Federated Learning over Wireless Networks
Xiaokang Zhou, Yansha Deng, Huiyun Xia +2
The newly emerging federated learning (FL) framework offers a new way to train machine learning models in a privacy-preserving manner. However, traditional FL algorithms are based…
Machine Learning for Massive Industrial Internet of Things
Hui Zhou, Changyang She, Yansha Deng +2
Industrial Internet of Things (IIoT) revolutionizes the future manufacturing facilities by integrating the Internet of Things technologies into industrial settings. With the deploy…
Learning based signal detection for MIMO systems with unknown noise statistics
Ke He, Le He, Lisheng Fan +3
This paper aims to devise a generalized maximum likelihood (ML) estimator to robustly detect signals with unknown noise statistics in multiple-input multiple-output (MIMO) systems.…
Green Deep Reinforcement Learning for Radio Resource Management: Architecture, Algorithm Compression and Challenge
Zhiyong Du, Yansha Deng, Weisi Guo +2
AI heralds a step-change in the performance and capability of wireless networks and other critical infrastructures. However, it may also cause irreversible environmental damage due…