Crafting Principled Machine Learning Architectures for Networked Systems скачать в хорошем качестве

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.