SpaRTaN/MacSeNet 2017 Summer School
Lisbon, Portugal, May 31 - June 2, 2017



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In collaboration with SPARS 2017, there is a Summer School provided by two European Union Marie Skłodowska-Curie Innovative Training Networks:
  • MacSeNet (H2020-MSCA-ITN-2014:642685)

  • SpaRTaN (FP7-PEOPLE-2013-ITN:607290)
Spaces are limited so if you are interested in attending, please apply by sending the following to macsenet@surrey.ac.uk before April 11, 2017:
  • Full name
  • Affiliation (university or workplace)
  • Research topics
  • Why you think you will benefit from the Summer school (max 500 words)
  • Letter of recommendation from supervisor (students only)
  • One-page page CV (non-students only)
  • Attending the SPARS workshop (yes/no)
Notifications of acceptance, with details of how to pay, will be sent by April 21, 2017.

The fee for the Summer School will be 125€.

If you are attending the summer school but not SPARS, you may be interested to know that we are offering free registration for the first day of SPARS (June 5, 2017).  Please let us know in your application if you would like to attend.
 
 

Speakers:

  • Volkan Cevher, École Polytechnique Fédérale de Lausanne, Switzerland
    • Topic: TBA

  • Cédric Févotte, Institut de Recherche en Informatique de Toulouse, France
    • Topic: Nonnegative Matrix Factorisation & Friends for Audio Signal Separation

  • Julien Mairal, INRIA, France
    • Topic: Sparse Estimation and Dictionary Learning

  • Brian McFee, New York University, USA
    • Topic: TBA

  • Guido MontúfarMax Planck Institute for Mathematics in the Sciences, Germany
    • Topic: TBA

  • Gabriele Steidl, Technische Universität Kaiserslautern, Germany
    • Topic: TBA

  • Bob Sturm, Queen Mary University of London, UK
    • Topic: Evaluation in Machine Learning (Horses: how to train them, and ways of whispering to them)

  • Sergios Theodoridis, University of Athens, Greece
    • Topic: Bayesian Learning

  • Rebecca Willett, University of Wisconsin, USA
    • Topic: Photon-limited Imaging








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