Crafting Principled Machine Learning Architectures for Networked Systems
Speakers:
Sanjay G. Rao – Professor – Electrical and Computer Engineering – Purdue University
Bruno Ribeiro – Associate Professor – Department of Computer Science – Purdue University
Organizer:
Edmundo de Souza Silva – Systems Engineering and Computer Science/COPPE – Federal University of Rio de Janeiro
Matthew Caesar – Siebel School of Computing and Data Science – University of Illinois Urbana-Champaign
Modern networking environments’ dynamic and unpredictable nature poses significant challenges for traditional design approaches and off-the-shelf machine learning methods. As networked systems
adapt to changing conditions, such as topology shifts, complex constraints, and unforeseen scenarios, they often outpace the capabilities of conventional solutions. In this panel, we will
advocate for a cross-disciplinary approach that integrates insights and techniques from both networking and machine learning and will showcase two recent approaches that exemplify this ethos.
time
*** NOTE THE TIME CHANGE FOR THIS EVENT FOR EU PARTICIPANTS ***
4pm CET
(8am PDT / 11am EDT / 12am JST )
where
web-streamed | time streamed
contact
www.networkingchannel.eu
category
panel discussion