(Invitation from PRIME on behalf of Dr. Rhandley Cajote of UP Diliman. Kindly note that this talk will also be available via PRIME. Details to follow).
 
 
You are invited to attend the IEEE Circuits and Systems (CAS) Distinguished Lecture by Prof. Gerald Sobelman of University of Milwaukee in Minnesota on 24 February 2020, 2:00PM at the PLDT Multimedia Hall, EEE Institute building, UP Diliman.

The title of his lecture is "Machine Learning and Optimization for Communications and Deep Networks". This talk is jointly organised by IEEE Republic of Philippines Section, IEEE SP and CAS Society and the EEE Institute, UP Diliman. Abstract and short bio of Prof. Sobelman is attached below.

We request all those interested to please pre-register so we can estimate na number of attendees and make the necessary preparations on the venue if needed. 


To register for this event, please follow this link
Please feel free to forward this email invite to colleagues and friends.
Regards,
Rhandley D. Cajote
EEE Institute, UP Diliman

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Machine Learning and Optimization for Communications and Deep Networks
Prof. Gerald Sobelman
University of Minnesota, USA

 Abstract

In recent years, many remarkable achievements have been made in the field of machine learning.  While most of the initial successes were related to image, speech and language recognition, a recent important development has been the application of these techniques to other areas.  In particular, communications systems can benefit from applying these techniques.  For example, algorithms such as Monte Carlo Markov Chain  and Monte Carlo Tree Search have been successfully used in the design of MIMO (i.e., multiple antenna) transceivers.  In addition, highly quantized implementations, such as binarized networks, have led to implementations that are well-suited to power-limited mobile platforms.  In addition, metaheuristic optimization techniques such as genetic algorithms and others have been used to automatically find highly efficient deep learning architectures, eliminating the need for lengthy and tedious manual experimentation.  This lecture will describe these approaches and present some recent design examples.  Relationships between the algorithms will be emphasized, and important computational issues will be highlighted.  Finally, opportunities for future research in these areas will be suggested.

Brief Biography

Gerald Sobelman is a Professor in the Department of Electrical and Computer Engineering at the University of Minnesota, and he has served as the Director of Graduate Studies for the Graduate Program in Computer Engineering at the University of Minnesota.  He received a B.S. degree in physics from the University of California, Los Angeles, and M.S. and Ph.D. degrees in physics from Harvard University.  He has been a postdoctoral researcher at The Rockefeller University, and he has held senior engineering positions at Sperry Corporation and Control Data Corporation.

Prof. Sobelman has previously served twice as a Distinguished Lecturer of the IEEE Circuits and Systems Society, during 2008–2009 and during 2013-2014.  He has been a member of the technical program committees for several IEEE conferences.  He was Chair of the Technical Committee on Circuits and Systems for Communications of the IEEE Circuits and Systems Society, and he has also served as an Associate Editor for IEEE Transactions on Circuits and Systems I and for IEEE Signal Processing Letters.  In addition, he has chaired sessions at international conferences in the areas of communications and VLSI architectures.

Prof. Sobelman has presented short courses at a number of industrial and academic sites.  He has authored or co-authored more than 150 technical papers and 1 book, and he holds 12 U.S. patents.

A link to the bio here.

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