MLSS 2013 - MACHINE LEARNING SUMMER SCHOOL

Machine Learning Summer School is next Monday, 11 March 2013.
See the following re-post for details. Many thanks for your interest.
http://mlss.tuebingen.mpg.de
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MACHINE LEARNING SUMMER SCHOOL
at the Max Planck Institute for Intelligent Systems in Tübingen, Germany
26 August to 6 September 2013
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Overview
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The machine learning summer school provides graduate students and industry
professionals with an intense learning experience on the theory and
applications of modern machine learning. Over the course of two weeks,
a panel of internationally renowned experts of the field will offer
tutorials covering basic as well as advanced topics.
Confirmed Speakers and Topics
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Yasemin Altun (Google) will speak on
Structured Output Prediction
Christopher Bishop (Microsoft Research) will speak on
Graphical Models
Léon Bottou (Microsoft Research) will speak on
Multilayer Networks
Peter Dayan (Gatsby Computational Neuroscience Unit) will speak on
Cognitive Learning
Zoubin Ghahramani (University of Cambridge) will speak on
Bayesian Inference
Ralf Herbrich (Amazon) will speak on
Distributed Machine Learning at Scale
Andreas Krause (ETH Zürich) will speak on
Submodularity
Tom Minka (Microsoft Research) will teach a practical on
Graphical Models
Joaquin Quiñonero-Candela (Facebook) will teach a practical on
a topic to be announced
Stefan Schaal (Max Planck Institute for Intelligent Systems) will speak on
Learning Robots
Matthias Seeger (École Polytechnique Fédérale de Lausanne) will speak on
Sparse Models
Ingo Steinwart (University of Stuttgart) will speak on
Learning Theory
YeeWhye Teh (University of Oxford) will speak on
Bayesian Nonparametrics
Marc Toussaint (University of Stuttgart) will speak on
Reinforcement Learning
Stephen Wright (University of Wisconsin-Madison) will speak on
Optimization
Practical Tutorials will, among others, be taught by
Application process
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Applications are invited from graduate students, postdoctoral researchers
and industry professionals looking to use, or already using machine
learning methods in their work. This includes researchers in applied
fields as well as students of machine learning itself. Prior experience
is not strictly required, but helpful. A small number of travel stipends
will be available.
Applicants will be asked to submit a CV, a cover letter of up to 200
words, and a short letter of recommendation from one referee of their
choice. We are also seeking to give participants a chance to discuss their
own work with their peers and the speakers. Each applicant is thus invited
to provide the title of a poster they would like to present at the school.
Important Dates
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* Monday 11 February 2013 application system opens
* Monday 11 March 2013 DEADLINE FOR APPLICATIONS
* Friday 12 April 2013 notification of acceptance
The school takes place from
Monday 26 August to Friday 6 September 2013
Organizers
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Philipp Hennig Stefan Harmeling Bernhard Schölkopf
inquiries should be directed to mlss2013-AT-tuebingen.mpg.de