Skip to first unread message
Ruth Urner
Feb 4, 2017, 4:45:32 AM2/4/17
to Ruth Urner
************************************************************************** *** APPLICATION PERIOD ENDS SOON *** *** http://mlss.tuebingen.mpg.de/2017/application.html *** ************************************************************************** Dear Colleagues, please note that the application deadline for the--------------------------------------------------------------------------
MACHINE LEARNING SUMMER SCHOOL
at the Max Planck Institute for Intelligent Systems in Tübingen, Germany
June 19 to 30, 2017
http://mlss.tuebingen.mpg.de/2017/
--------------------------------------------------------------------------
is approaching. The deadline is this Friday, Feb 10, at 23.59 GMT.
Reference letters will be accepted till Friday, Feb 17, 23.59 GMT.
Overview
--------------------------------------------------------------------------
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
lectures and tutorials covering basic as well as advanced topics.
Confirmed Speakers
--------------------------------------------------------------------------
Shai Ben-David (U Waterloo) - Learning Theory
Zoubin Ghahramani (Cambridge) - Bayesian Inference
Manuel Gomez Rodriguez (MPI for Software Systems) - tutorial on Networks
Stefanie Jegelka (MIT) - Submodularity
Michael Jordan (UC Berkeley) - Optimization: Distributed, Asynchronous,
Accelerated and Non-Convex.
Koray Kavukcuoglu (Deepmind) - Deep Learning for Agents
Jure Lescovec (Stanford) - Network Analysis
Ruslan Salakhutdinov (CMU) - Deep Learning
Suvrit Sra (MIT) - Optimization
Bernhard Schölkopf (MPI for Intelligent Systems) - Causality
Bharath Sriperumbudur (PennState) - Kernel Methods
Ilya Tolstikhin (MPI for Intelligent Systems) - tutorial on Theory
Ruth Urner (MPI for Intelligent Systems) - tutorial on Theory
Raquel Urtasun (Toronto) - Deep Structured Models
Application process
--------------------------------------------------------------------------
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.
The application system is now open.at the Max Planck Institute for Intelligent Systems in Tübingen, Germany
June 19 to 30, 2017
http://mlss.tuebingen.mpg.de/2017/
--------------------------------------------------------------------------
is approaching. The deadline is this Friday, Feb 10, at 23.59 GMT.
Reference letters will be accepted till Friday, Feb 17, 23.59 GMT.
Overview
--------------------------------------------------------------------------
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
lectures and tutorials covering basic as well as advanced topics.
Confirmed Speakers
--------------------------------------------------------------------------
Shai Ben-David (U Waterloo) - Learning Theory
Zoubin Ghahramani (Cambridge) - Bayesian Inference
Manuel Gomez Rodriguez (MPI for Software Systems) - tutorial on Networks
Stefanie Jegelka (MIT) - Submodularity
Michael Jordan (UC Berkeley) - Optimization: Distributed, Asynchronous,
Accelerated and Non-Convex.
Koray Kavukcuoglu (Deepmind) - Deep Learning for Agents
Jure Lescovec (Stanford) - Network Analysis
Ruslan Salakhutdinov (CMU) - Deep Learning
Suvrit Sra (MIT) - Optimization
Bernhard Schölkopf (MPI for Intelligent Systems) - Causality
Bharath Sriperumbudur (PennState) - Kernel Methods
Ilya Tolstikhin (MPI for Intelligent Systems) - tutorial on Theory
Ruth Urner (MPI for Intelligent Systems) - tutorial on Theory
Raquel Urtasun (Toronto) - Deep Structured Models
Application process
--------------------------------------------------------------------------
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://mlss.tuebingen.mpg.de/2017/application.html
Important Dates
--------------------------------------------------------------------------
* Fri, December 23, 2015 application system opens
* Fri, February 10, 2017 DEADLINE FOR APPLICATIONS
* Fri, February 17, 2017 deadline for reference letters
* Tue, February 28, 2017 notification of acceptance
The school will take place from
Monday, June 19 to Friday, June 30, 2017
Organizers
--------------------------------------------------------------------------
Ruth Urner, Michael Hirsch, Ilya Tolstikhin and Bernhard Schölkopf
inquiries should be directed to ruth....@tuebingen.mpg.de
==========================================================================
Reply all
Reply to author
Forward
0 new messages