185 citations · 234 across the 12 of their papers we have counts for
12 papers
Output-Dependent Gaussian Process State-Space Model
Zhidi Lin, Lei Cheng, Feng Yin +2
Gaussian process state-space model (GPSSM) is a fully probabilistic state-space model that has attracted much attention over the past decade. However, the outputs of the transition…
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…
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…
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…
A General Hyper-Parameter Optimization for Gaussian Process Regression with Cross-Validation and Non-linearly Constrained ADMM
Linning Xu, Feng Yin, Jiawei Zhang +2
Hyper-parameter optimization remains as the core issue of Gaussian process (GP) for machine learning nowadays. The benchmark method using maximum likelihood (ML) estimation and gra…
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…
Multi-Antenna Channel Interpolation via Tucker Decomposed Extreme Learning Machine
Han Zhang, Bo Ai, Wenjun Xu +2
Channel interpolation is an essential technique for providing high-accuracy estimation of the channel state information (CSI) for wireless systems design where the frequency-space…
Multitask Gaussian Process with Hierarchical Latent Interactions
Kai Chen, Twan van Laarhoven, Elena Marchiori +2
Multitask Gaussian process (MTGP) is powerful for joint learning of multiple tasks with complicated correlation patterns. However, due to the assembling of additive independent lat…
Compressible Spectral Mixture Kernels with Sparse Dependency Structures for Gaussian Processes
Kai Chen, Yijue Dai, Feng Yin +2
Spectral mixture (SM) kernels comprise a powerful class of generalized kernels for Gaussian processes (GPs) to describe complex patterns. This paper introduces model compression an…
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…
Streaming Algorithms for News and Scientific Literature Recommendation: Submodular Maximization with a d-Knapsack Constraint
Qilian Yu, Easton Li Xu, Shuguang Cui
Submodular maximization problems belong to the family of combinatorial optimization problems and enjoy wide applications. In this paper, we focus on the problem of maximizing a mon…
Detection of Cooperative Interactions in Logistic Regression Models
Easton Li Xu, Xiaoning Qian, Tie Liu +1
An important problem in the field of bioinformatics is to identify interactive effects among profiled variables for outcome prediction. In this paper, a logistic regression model w…