Connectionists: MACHINE LEARNING SUMMER SCHOOL

[Remi Munos]

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            10th MACHINE LEARNING SUMMER SCHOOL 
                       MLSS'08
             September 1-15, Ile de Re, France.
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     http://mlss08.futurs.inria.fr  email : mlss08 at inria.fr



(Thanks for forwarding this Announcement to potential
candidates and apologies for multiple copies).

THE APPLICATION PROCESS IS OPEN until APRIL 15, 2008
http://mlss08.futurs.inria.fr/application 

Machine Learning is a foundational discipline of the Information
Sciences. It combines theory from areas as diverse as Statistics,
Mathematics, Engineering, and Information Technology with many practical
and relevant real life applications. The aim of the summer school is to
cover the entire spectrum from theory to practice. It is mainly targeted
at research students, academics, and IT professionals from all over the
world.

The program will feature introductory courses at the beginning to
provide basic working knowledge of Machine Learning. Building on this
introductory material, advanced topics will be covered progressively
over the duration of the school. Subjects will be covered both in
lectures (4-6 per topic) and in practical courses (where students will
have the chance to implement methods for themselves); and are taught by
world experts in their fields.

This school is suited to PhD and Masters students, as well as advanced
undergraduates, provides an excellent opportunity for interaction with
top researchers in a broad cross-section of machine learning disciplines.
The confirmes speakers are:

  * Shai Ben-David (University of Waterloo) /"Theoretical Foundations
    of Clustering"/
  * Stephane Canu (INSA de Rouen) /"Introduction to Kernel Methods"/
  * Manuel Davy (CNRS/Predict&Control) /"Parametric and Non-parametric 
Bayesian
    Learning"/
  * Pierre Del Moral (Universite de Bordeaux) /"On the Foundations and
    the Applications of i-MCMC Methods"/
  * Isabelle Guyon (ClopiNet)
  * Yann LeCun (New York university) /"Supervised and Unsupervised
    Learning with Energy-Based Models"/
  * Rich Sutton (University of Alberta) /"Reinforcement Learning and
    Knowledge Representation"/
  * Patrick Wolfe (Harvard University) /"Overcomplete Representations
    with Incomplete Data: Learning Bayesian Models for Sparsity"/

The program is available at http://mlss08.futurs.inria.fr/

*Please find more information about registrations and application form
at http://mlss08.futurs.inria.fr/application
We are loking forward to seeing you in Ile de Re, France.

Best regards,
the MLSS organizing committee
   mlss08 at inria.fr
http://mlss08.futurs.inria.fr/