On multi-view learning with additive models

DOI10.1214/08-AOAS202zbMath1167.62003arXiv0906.1117OpenAlexW3104527978MaRDI QIDQ1018621

Kjell Johnson, Mark Culp, George Michailidis

Publication date: 20 May 2009

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0906.1117

zbMATH Keywords

smoothingmodel selectiongeneralized additive modelssemi-supervised learning

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of statistics to environmental and related topics (62P12) Applications of graph theory (05C90)

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Uses Software

• pls
• ElemStatLearn
• SGTlight

Cites Work

• Special issue: Recent advances on machine learning and cybernetics. Selected papers based on the presentations at the 7th international conference on machine learning and cybernetics (ICML 2008), Kumming, China, July 2008.
• Linear smoothers and additive models
• Multivariate adaptive regression splines
• A generalization of Brouwer's fixed point theorem
• Understanding the Yarowsky Algorithm
• The elements of statistical learning. Data mining, inference, and prediction
• Random forests
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