Connectionists: Call for participation: Machine Learning Summer School, 28 June - 10 July 2020, Germany

[Wittawat Jitkrittum]

Dear all,

The Machine Learning Summer School (MLSS) 2020 will be held at the Max
Planck Institute for Intelligent Systems, Tübingen, Germany between  28
June - 10 July 2020. The MLSS presents topics which are at the core of
modern machine learning, from fundamentals to state-of-the-art practice.
The speakers are leading experts in their field.

# INVITED SPEAKERS & TOPICS


   1.

   Francis Bach <https://www.di.ens.fr/~fbach/>, INRIA. Optimization
   2.

   Stefan Bauer <https://www.is.mpg.de/~sbauer>, Max Planck Institute for
   Intelligent Systems. Causal Inference
   3.

   Yoshua Bengio <https://mila.quebec/en/yoshua-bengio/>, University of
   Montreal (Computer Sc. & Op. Res.), Mila, CIFAR, CRM, IVADO, REPARTI,
   GRSNC. Deep learning
   4.

   Michael Bronstein <https://www.imperial.ac.uk/people/m.bronstein>,
   Imperial College London and Twitter. Geometric Deep Learning
   5.

   Nicoló Cesa-Bianchi <http://cesa-bianchi.di.unimi.it/>, University of
   Milan. Learning Theory
   6.

   Marco Cuturi <https://marcocuturi.net/>, Google Brain and Institut
   Polytechnique de Paris. Optimal Transport
   7.

   Constantinos Daskalakis <http://people.csail.mit.edu/costis/>,
   Massachusetts Institute of Technology (MIT). Game Theory in Machine Learning
   8.

   Peter Dayan <https://www.kyb.tuebingen.mpg.de/person/95844/60427>, Max
   Planck Institute for Biological Cybernetics. Machine learning for
   Computational Neuroscience
   9.

   Arthur Gretton <http://www.gatsby.ucl.ac.uk/~gretton/>, Gatsby
   Computational Neuroscience Unit, UCL. Kernel Methods
   10.

   Moritz Hardt <https://www.mrtz.org/>, University of California,
   Berkeley. Fairness
   11.

   Stefanie Jegelka <https://people.csail.mit.edu/stefje/>, Massachusetts
   Institute of Technology (MIT). Submodularity
   12.

   Shakir Mohamed <https://shakirm.com/>, DeepMind. Bayesian Inference
   13.

   Doina Precup <https://www.cs.mcgill.ca/~dprecup/>, McGill University and
   DeepMind. (Deep) Reinforcement Learning
   14.

   Bernhard Schölkopf <https://www.is.mpg.de/~bs>, Max Planck Institute for
   Intelligent Systems. Causal Inference
   15.

   Yee Whye Teh <https://www.stats.ox.ac.uk/~teh/>, University of Oxford
   and DeepMind. Meta-Learning
   16.

   Mihaela van der Schaar
   <http://www.vanderschaar-lab.com/NewWebsite/Professor.html>, University
   of Cambridge and Alan Turing Institute. Machine Learning for Healthcare


The list of invited speakers is still growing, which will be updated on our
website <http://mlss.tuebingen.mpg.de/2020/speakers.html>.


# APPLICATION & PROGRAM

We are inviting applications to participate in the MLSS 2020. The
application deadline is 11 February 2020. Details regarding the application
process can be found at <https://www.mlrs.ai/participate>
http://mlss.tuebingen.mpg.de/2020/participate.html . Everyone is welcome to
apply to MLSS 2020 regardless of their origin, nationality, and country of
residence. We aim to select 150 strongly motivated participants. Our
primary target audience is early-mid stage PhD students with good technical
background whose research topics are related to machine learning. All
applicants are subject to a selection process. Note that the application
portal may close earlier than the deadline if the number of applications
exceeds our capacity to review

There is no application fee. However, for applicants selected to
participate, there is a registration fee (details here
<http://mlss.tuebingen.mpg.de/2020/participate.html>). The registration fee
will allow us to offer access to all lectures by the invited speakers,
lunch, dinner and two coffee breaks everyday, social events (banquet,
outdoor activities). A small number of travel awards are available for
students who are accepted to attend.

# CONTACT:

Please do not hesitate to contact us at  mlss2020-team at tuebingen.mpg.de for
any questions or suggestions.


Kind regards,

The MLSS 2020 Team <http://mlss.tuebingen.mpg.de/2020/organizers.html>
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