Basics of Bayesian Learning - Basically Bayes

Jan Larsen

AbstractTutorial presented at the IEEE Machine Learning for Signal Processing Workshop 2006, Maynooth, Ireland, September 8, 2006.
The tutorial focuses on the basic elements of Bayesian learning and its relation to classical learning paradigms. This includes a critical discussion of the pros and cons. The theory is illustrated by specific models and examples.
Keywordsbayes learning, generalization, model evaluation
TypeMisc [Presentation]
Year2006    Month September
PublisherInformatics and Mathematical Modelling, Technical University of Denmark
AddressRichard Petersens Plads, Building 321, DK-2800 Kongens Lyngby
NoteTutorial presented at the IEEE Machine Learning for Signal Processing Workshop 2006, Maynooth, Ireland, September 8, 2006
Electronic version(s)[zip]
Publication linkhttp://mlsp2006.conwiz.dk/index.php?id=16
BibTeX data [bibtex]
IMM Group(s)Intelligent Signal Processing


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