A short course on Deep Learning

ICSEE2018 offers for the first time a three hour hands on short course during the conference

Date: 12/12/2018- first day of the conference at 13:30-16:30

Price: 70$

* Please note that the course is with limited enrollment and we anticipate it will fill quickly. Registration is on a first-come, first-served basis.


Raja Giryes is a senior lecturer in the school of electrical engineering at Tel Aviv University. He received the B.Sc (2007), M.Sc. (supervision by Prof. M. Elad and Prof. Y. C. Eldar, 2009), and PhD (supervision by Prof. M. Elad 2014) degrees from the Department of Computer Science, The Technion – Israel Institute of Technology, Haifa. Raja was a postdoc at the computer science department at the Technion (Nov. 2013 till July 2014) and at the lab of Prof. G. Sapiro at Duke University, Durham, USA (July 2014 and Aug. 2015). His research interests lie at the intersection between signal and image processing and machine learning, and in particular, in deep learning, inverse problems, sparse representations, and signal and image modeling. Raja received the ERC-StG grant,  Maof prize for excellent young faculty (2016-2019), VATAT scholarship for excellent postdoctoral fellows (2014-2015), Intel Research and Excellence Award (2005, 2013), the Excellence in Signal Processing Award (ESPA) from Texas Instruments (2008) and was part of the Azrieli Fellows program (2010-2013). He has co-organized workshops and tutorials on deep learning in leading conference such as ICML 2016 and 2018, ICCV 2015 and 2017, CVPR 2016 and 2017, EUSIPCO 2016, ACCV 2016 and CDC 2017.



Course description:


The course will provide a general description of what deep learning is, its usages for various applications and what are the tools available today for it.

The first half of the course will cover the key aspects of neural networks and the second one will include a hands-on experience in coding with deep learning. Participants will receive a mail with instructions in advance with details on what to download and install on their computer prior to the course.

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