A machine learning summer school will be held at Chalmers, Gothenburg,
the second largest Swedish city, in the period 14-16 April.
Information and registration:
http://www.chalmers.se/en/departments/cse/organisation/CS/Pages/machine-learning-summer-school.aspx
Topics
Machine learning has increasing importance in today's society, with
ever-wider application of autonomous learning systems in areas ranging
from advertising to energy and finance. It also has many scientific
applications, as evidence by the growth of data science as a discipline.
This summer school will give thorough introductions to a number of
techniques and application areas in machine learning, including.
On the theory side, topics covered will include Bayesian inference, Deep
learning, Gaussian processes, Markov decision processes, Monte-Carlo
methods and Reinforcement learning. The applications will include
Computational Biology, Computer vision, Energy and Smart Grids, Medicine
and Robotics.
Travel grants are available for students.
Speakers
Marc Deisenroth, Imperial College, UK.
Mattias Villani, Linköping University, Sweden.
Tomas Schon, Uppsala University, Sweden.
Josephine Sullivan, KTH, Sweden
Tom Heskes, Radbound University, Nimejgen, Netherlands.
Devdatt Dubhashi, Chalmers University of Technology, Sweden.
Lars Carlsson, Astra Zeneca, Sweden
Christos Dimitrakakis, Chalmers University of Technology, Sweden.
Damien Ernst, University of Liege, Belgium.
Ronald Ortner, University of Loeben, Austria
Sponsors:
- Chalmers (Computing Science Division, Energy Area of Advance, ICT Area
of Advance)
- Swedish AI Society
Contact Christos Dimitrakakis <[email protected]> or Devdatt Dubhashi
<[email protected]> for further information.
--
Christos Dimitrakakis
http://www.cse.chalmers.se/~chrdimi/
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