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        Machine Learning Summer School
        Chicago, USA
        May 16-27, 2005
        http://chicago05.mlss.cc/

TTI-Chicago and the University of Chicago are hosting a Machine
Learning Summer School from May 16-27.  This will include all the
machine learning and learning theory that can be covered in 2 weeks of
intense instruction.  The target audience is anyone interested in the
subject including graduate students and academic and industry
researchers.  Please join us.

Subjects: Bayesian Learning, Boosting, Decision trees, Empirical
Comparisons and Case Studies, Energy Models, Evidence Integration in
Bioinformatics, Generalization Bounds, Information Geometry, Manifold
Methods, Object Recognition, Online Learning, Reductions,
Regularization, Semisupervised Learning, Structured Learning, SVMs

Speakers: Yasemin Altun, Misha Belkin, Rich Caruana, Sanjoy Dasgupta,
Zoubin Ghahramani, Mark Johnson, Adam Kalai, John Langford, Yann LeCun,
Phil Long, David McAllester, Partha Niyogi, Robert Nowak, Robert
Schapire, Yoram Singer, Steve Smale (and possibly more).

In addition, the summer school will be colocated with two workshops
and the 'special emphasis on learning theory' quarter at TTI-Chicago.
Attendees of the school will be able to attend the workshops and
vice-versa. For further details on the quarter see:

        http://www.tti-c.org/abstracts/learning_theory.html

Contact jl at tti-c.org for questions.