[Statlist] Talk on Thursday May 22 in ZH on Machine learning

[Werner Stahel]

Dear colleagues

It is my great pleasure to announce the following talk by
Prof. Zoubin Ghahramani, Cambridge University UK
on Bayesian modeling.

Zoubin will be at ETH on May 22-23, 2008. If you like to meet
with him please let me know.

Best wishes, Joachim Buhmann

Date:  Thursday, May 22, 2008, 
Time:  16:15
Place: CAB G 51

Title:
Recent directions in nonparametric Bayesian machine learning

Prof. Zoubin Ghahramani
Department of Engineering
University of Cambridge

Machine learning is an interdisciplinary field which seeks to develop 
both the mathematical foundations and practical applications of systems 
that learn, reason and act. Machine learning draws from many fields, 
ranging from Computer Science, to Engineering, Psychology, Neuroscience, 
and Statistics. Because uncertainty, data, and inference play a 
fundamental role in the design of systems that learn, statistical 
methods have recently emerged as one of the key components of the field 
of machine learning. In particular, Bayesian methods, based on the work 
of Reverend Thomas Bayes in the 1700s, describe how probabilities can be 
used to represent the degrees of belief of a rational agent. Bayesian 
methods work best when they are applied to models that are flexible 
enough to capture to complexity of real-world data. Recent work on 
non-parametric Bayesian methods provides this flexibility. I will touch 
upon key developments in the field, including Gaussian processes, 
Dirichlet processes, and the Indian buffet process (IBP). Focusing on 
the IBP, I will describe how this can be used in a number of 
applications such as collaborative filtering, bioinformatics, cognitive 
modelling, independent components analysis, and causal discovery. 
Finally, I will outline the main challenges in the field: how to develop 
new models, new fast inference algorithms, and compelling applications.



=====================================================================
Joachim M. Buhmann
Institute for Computational Science    Tel.(office) : +41-44-63 23124
ETH Zentrum, CAB G 69.2                Tel.(secret.): +41-44-63 26496
Universitätstrasse 6                             Fax: +41-44-63 21562
CH-8092 Zurich, Switzerland               email: jbuhmann at inf.ethz.ch