FYI: Machine Learning Summer School, Chicago, USA
Machine Learning Summer School, Chicago, USA
May 16-27, 2005
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:
Contact firstname.lastname@example.org for questions.