Machine Learning Summer School 2016, University of Cadiz, Spain, May 11th to 21st 2016

Joan just sent me the following:
   

Dear Igor,

I hope you are doing well.
I just wanted to let you know that we are organizing the upcoming machine learning summer school next summer. I was wondering if these are the sort of announcements you typically post on nuit blanche... here is the official announcement....

Best regards,

Joan

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Dear Colleagues,

We are happy to announce that applications are now open for the upcoming

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          MACHINE LEARNING SUMMER SCHOOL
at the University of Cadiz, Spain, May 11th to 21st 2016
http://learning.mpi-sws.org/mlss2016

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Overview
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The machine learning summer school provides graduate students, researchers and industry professionals with an intense learning experience on theory and applications of modern machine learning. Over the course of ten days, a panel of internationally renowned experts will offer lectures and tutorials covering a diverse range of theoretical and applied topics.This time the MLSS is co-located just after AISTATS 2016, in the medieval town of Cadiz (south of Spain).

Confirmed Speakers and Topics so far:
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• Arthur Gretton (UCL Gatsby), Kernel Methods Arthur Szlam (Facebook AI Research), Deep Learning
• Francis Bach (ENS), Optimization
• Jonas Peters (MPI-IS), Causality
• Le Song (Georgia Institute of Technology), Machine Learning for Networks
• Mathias Betghe (Center Integrative Neuroscience, U Tubingen), Machine Learning for Neuroscience
• Nando de Freitas (Oxford University, DeepMind), Deep Learning
• Neil Lawrence (University of Sheffield), Gaussian Processes
• Nicolas Le Roux (Criteo), Large Scale Machine Learning
• Peter Abbeel (UC Berkeley), Deep Reinforcement Learning
• Samory Kptufe (Princeton), Learning Theory
• Sebastien Bubek (Microsoft Research), Bandits
• Stefanie Jegelka (MIT), Submodularity
• Stephane Mallat (ENS), Mathematics of Convolutional Networks
• Tamara Broderick (MIT), Nonparametrics and Bayesian Statistics
• Michel Besserve (MPI-IS), Practical on Machine Learning for Neuroscience
• John Schulmann (UC Berkeley), Practical on Deep Reinforcement Learning
• Isabel Valera (MPI-SWS), Practical on Machine Learning for Networks
• Durk Kingma (U Amsterdam), Practical on Deep Learning

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 2000 characters, 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.

For more information visit http://learning.mpi-sws.org/mlss2016/application/


Important Dates
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* Monday November 23 2015            application system opens
* Sunday Jan 31 2016                  DEADLINE FOR APPLICATIONS
* Sunday Feb 28 2016                notification of acceptance


Organizers
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Manuel Gomez Rodriguez (MPI-SWS)
Joan Bruna (UC Berkeley)

inquiries should be directed to mlss2016@mpi-sws.org
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