Boosting: Foundations and Algorithms
by Robert E. Schapire, Yoav Freund
Publisher: The MIT Press 2014
Number of pages: 544
Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate 'rules of thumb'. A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry.
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by M. Mohri, A. Rostamizadeh, A. Talwalkar - The MIT Press
This is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools.
by Osvaldo Simeone - arXiv.org
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