Learning a function from noisy samples at a finite sparse set of points

DOI10.1016/j.jat.2008.11.003zbMath1205.94061OpenAlexW2028550852MaRDI QIDQ1048968

Friedrich Pillichshammer, Andreas Hofinger

Publication date: 8 January 2010

Published in: Journal of Approximation Theory (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jat.2008.11.003

zbMATH Keywords

regularizationlearning theorysampling theoryquasi-Monte Carlo methods

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Sampling theory in information and communication theory (94A20)

Related Items (2)

Nonlinear function approximation: computing smooth solutions with an adaptive greedy algorithm ⋮ The weight-decay technique in learning from data: an optimization point of view

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