activity
20182021
most citedWireless Traffic Prediction with Scalable Gaussian Process: Framework, Algorithms, and Verification

185 citations · 326 across the 10 of their papers we have counts for

collaborators

10 papers

cs.LG2021★ 2 cited

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…

cs.LG2021★ 6 cited

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…

eess.SP2020

Predicting Bit Error Rate from Meta Information using Random Forests

Jianyuan Yu, Yue Xu, Hussein Metwaly Saad +1

With the increasing power of machine learning-based reasoning, the use of meta-information (e.g., digital signal modulation parameters, channel conditions, etc.) to predict the per…

cs.IR2020★ 1 cited

Single-Layer Graph Convolutional Networks For Recommendation

Yue Xu, Hao Chen, Zengde Deng +5

Graph Convolutional Networks (GCNs) and their variants have received significant attention and achieved start-of-the-art performances on various recommendation tasks. However, many…

cs.DC2020★ 14 cited

FedLoc: Federated Learning Framework for Data-Driven Cooperative Localization and Location Data Processing

Feng Yin, Zhidi Lin, Yue Xu +5

In this overview paper, data-driven learning model-based cooperative localization and location data processing are considered, in line with the emerging machine learning and big da…

cs.LG2020★ 2 cited

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…

cs.LG2019

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…

cs.LG2019★ 104 cited

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…

cs.LG2019★ 185 cited

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…

cs.NI2018★ 12 cited

Handover Control in Wireless Systems via Asynchronous Multi-User Deep Reinforcement Learning

Zhi Wang, Lihua Li, Yue Xu +2

In this paper, we propose a two-layer framework to learn the optimal handover (HO) controllers in possibly large-scale wireless systems supporting mobile Internet-of-Things (IoT) u…