Dear colleagues,
It is our pleasure to inform you about the upcoming “CoSIP Intense Course on Deep Learning”, which will take place at TU Berlin from November 29 to December 1, 2017, organized by Rudolf Mathar, Maximilian März, and myself. This intense course is related to the DFG-Priority Programme “Compressed Sensing in Information Processing (CoSIP)”, but is open to all interested researchers.
We are honored that the following seven internationally recognized experts have agreed to give a 2-hours lecture at this event:
* Helmut Bölcskei (ETH Zürich)
* Michael Elad (Technion)
* Philipp Grohs (University of Vienna)
* Lars Ruthotto (Emory University)
* Wojciech Samek (Fraunhofer HHI)
* Vignesh Srinivasan (Fraunhofer HHI)
* René Vidal (The Johns Hopkins University)
The topics of the courses will cover a wide range of relevant topics in deep learning, including an introduction lecture and a training in Tensorflow. There will be a special emphasis on theoretical foundations of the field.
The deadline for the registration is October 31, 2017.
Continuous updates, more information about the program, venue etc. and the online registration can be found here:
http://www3.math.tu-berlin.de/numerik/CoSIPICDL2017/
This intense course is closely related to the 3. International Matheon-Conference on “Compressed Sensing and its Applications”, which will be held in the same place in the subsequent week (December 4-8). This time an additional focus of the conference will be put on foundations of deep learning. Hence this intense course will not only equip the upcoming generation of researchers with the necessary tools in the novel area of deep learning, but also lay the foundation for attending the Matheon-Conference.
Please do not hesitate to contact us if you have any questions related to the intense course.
With best regards,
Gitta Kutyniok (on behalf of the other organizers)
Prof. Dr. Gitta Kutyniok
Einstein-Professorin
Technische Universität Berlin
Institut für Mathematik, Sekr. MA 5-4
10623 Berlin Germany
Phone: +49 (030) 314 25758
Fax: +49 (030) 314 21604