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| Seminar Schedule (Seminar Organizer: Prof. Ziv Bar-Joseph) | |
Machine Learning Lunchtime Chats
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Summer 2005 Seminar
Date: August 24, 2005 Time: 2:00 PM - 4:00 PM Location: 1507 Newell-Simon Hall Speaker: Zoubin Ghahramani Associate Research Professor Title: Tutorial on non-parametric Bayesian methods for machine learning Abstract: Bayesian methods provide a sound statistical framework for modelling and decision making. However, most simple parametric models are not realistic for modelling real-world data. Non-parametric models are much more flexible and therefore are much more likely to capture our beliefs about the data. They also often result in much better predictive performance. I will give a survey/tutorial of the field of non-parametric Bayesian statistics from the perspective of machine learning. Topics will include: * The need for non-parametric models * Gaussian processes and their application to classification, regression, and other prediction problems * Chinese restaurant processes, different constructions, Pitman-Yor processes * Dirichlet processes, Dirichlet process mixtures, Hierarchical Dirichlet processes and infinite HMMs * Polya trees * Dirichlet diffusion trees * Time permitting, some new work on Indian buffet processes