Basics of Bayesian Learning - Basically Bayes |
Jan Larsen
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| Abstract | Tutorial 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. |
| Keywords | bayes learning, generalization, model evaluation |
| Type | Misc [Presentation] |
| Year | 2006 Month September |
| Publisher | Informatics and Mathematical Modelling, Technical University of Denmark |
| Address | Richard Petersens Plads, Building 321, DK-2800 Kongens Lyngby |
| Note | Tutorial presented at the IEEE Machine Learning for Signal Processing Workshop 2006, Maynooth, Ireland, September 8, 2006 |
| Electronic version(s) | [zip] |
| Publication link | http://mlsp2006.conwiz.dk/index.php?id=16 |
| BibTeX data | [bibtex] |
| IMM Group(s) | Intelligent Signal Processing |