185 citations · 326 across the 10 of their papers we have counts for
6 papers · 1 filter
Recent Advances in Data-Driven Wireless Communication Using Gaussian Processes: A Comprehensive Survey
Kai Chen, Qinglei Kong, Yijue Dai +4
Data-driven paradigms are well-known and salient demands of future wireless communication. Empowered by big data and machine learning, next-generation data-driven communication sys…
Bayesian Inference Forgetting
Shaopeng Fu, Fengxiang He, Yue Xu +1
The right to be forgotten has been legislated in many countries but the enforcement in machine learning would cause unbearable costs: companies may need to delete whole models lear…
Scalable Learning Paradigms for Data-Driven Wireless Communication
Yue Xu, Feng Yin, Wenjun Xu +3
The marriage of wireless big data and machine learning techniques revolutionizes the wireless system by the data-driven philosophy. However, the ever exploding data volume and mode…
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…
Wireless Traffic Prediction with Scalable Gaussian Process: Framework, Algorithms, and Verification
Yue Xu, Feng Yin, Wenjun Xu +2
The cloud radio access network (C-RAN) is a promising paradigm to meet the stringent requirements of the fifth generation (5G) wireless systems. Meanwhile, wireless traffic predict…