6 papers · 1 filter
Event-triggered Control and Online Learning for Networked Systems under Computational Delays
Xiaobing Dai, Armin Lederer, Zewen Yang +4
Online learning-based control is a promising approach to control uncertain systems, where unknown components are identified during operation to improve control performance. However…
Asynchronous Cooperative Online Learning for Multi-Robot Control under Computational Delays
Xiaobing Dai, Zewen Yang, Wei Ren +1
Ensuring the safe operation of multi-agent systems (MASs) under uncertain environments is crucial for cooperative robotic, where external disturbances and inaccurate dynamic models…
Quality or Quantity? Error-Informed Selective Online Learning with Gaussian Processes in Multi-Agent Systems: Extended Version
Zewen Yang, Xiaobing Dai, Jiajun Cheng +2
Effective cooperation is pivotal in distributed learning for multi-agent systems, where the interplay between the quantity and quality of the machine learning models is crucial. Th…
Streaming Generated Gaussian Process Experts for Online Learning and Control: Extended Version
Zewen Yang, Dongfa Zhang, Xiaobing Dai +5
Gaussian Processes (GPs), as a nonparametric learning method, offer flexible modeling capabilities and calibrated uncertainty quantification for function approximations. Additional…
GPgym: A Remote Service Platform with Gaussian Process Regression for Online Learning
Xiaobing Dai, Zewen Yang
Machine learning is now widely applied across various domains, including industry, engineering, and research. While numerous mature machine learning models have been open-sourced o…
Asynchronous Distributed Gaussian Process Regression for Online Learning and Dynamical Systems: Complementary Document
Zewen Yang, Xiaobing Dai, Sandra Hirche
This is a complementary document for the paper titled "Asynchronous Distributed Gaussian Process Regression for Online Learning and Dynamical Systems".