Distributed Data-Driven Iterative Learning Consensus Tracking for Nonlinear Discrete-Time Multi-Agent Systems
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Automatic Control"
DOI: 10.1109/tac.2021.3105653
Abstract: In this paper, a data-driven distributed leader-follower iterative learning consensus tracking control approach is proposed for unknown repetitive nonlinear non-affine discrete-time multi-agent systems. The leader's command is only communicated to a subset of the following… read more here.
Keywords: agent; consensus tracking; consensus; data driven ... See more keywords
Use of Machine Learning Consensus Clustering to Identify Distinct Subtypes of Kidney Transplant Recipients With DGF and Associated Outcomes
Sign Up to like & getrecommendations! Published in 2022 at "Transplant International"
DOI: 10.3389/ti.2022.10810
Abstract: Data and transplant community opinion on delayed graft function (DGF), and its impact on outcomes, remains varied. An unsupervised machine learning consensus clustering approach was applied to categorize the clinical phenotypes of kidney transplant (KT)… read more here.
Keywords: learning consensus; machine learning; kidney transplant; transplant recipients ... See more keywords