A meta-learning approach to the regularized learning -- case study: blood glucose prediction

DOI10.1016/j.neunet.2012.05.004zbMath1258.68119OpenAlexW2026886773WikidataQ45367331 ScholiaQ45367331MaRDI QIDQ1941597

S. Sivananthan, Valeriya Naumova, Sergei V. Pereverzyev

Publication date: 13 March 2013

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2012.05.004

zbMATH Keywords

regularizationlearning theorykernel choiceblood glucose predictionadaptive parameter choicemeta-learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (4)

Multi-penalty regularization in learning theory ⋮ A machine learning approach to optimal Tikhonov regularization I: Affine manifolds ⋮ A meta-learning approach to the regularized learning -- case study: blood glucose prediction ⋮ Continuous-time interval model identification of blood glucose dynamics for type 1 diabetes

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