A chain rule for the expected suprema of Gaussian processes

DOI10.1016/j.tcs.2016.07.034zbMath1353.68242OpenAlexW2502165832MaRDI QIDQ329618

Andreas Maurer

Publication date: 21 October 2016

Published in: Theoretical Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.tcs.2016.07.034

zbMATH Keywords

empirical processesgeneralizationchain rulemulti-layers

Mathematics Subject Classification ID

Random fields (60G60) Gaussian processes (60G15) Extreme value theory; extremal stochastic processes (60G70) Learning and adaptive systems in artificial intelligence (68T05)

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Cites Work

• Regularity of Gaussian processes
• Characterization of the law of the iterated logarithm in Banach spaces
• A simple proof of the majorizing measure theorem
• Majorizing measures without measures
• Transfer bounds for linear feature learning
• The Generic Chaining
• 10.1162/1532443041424300
• 10.1162/153244303321897690
• Neural Network Learning
• $K$-Dimensional Coding Schemes in Hilbert Spaces
• \(\ell\)-norm and its application to learning theory
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