Custom Machine Learning Architectures
Wayne Luk - Professor of Computer Engineering at Imperial College London
Monday, May 21, 2018

Abstract

Machine learning and custom computing architectures are two areas that have experienced rapid advances in recent years. This talk provides an overview of recent research in custom computing architectures which have shown promise for machine learning applications. The architectures for a variety of machine learning approaches will be covered, including those for convolutional neural networks, support vector machines, and genetic programming methods. The performance of such architectures targeting applications such as hyperspectral image processing and anomaly detection will be described, and future research directions in this topic will be presented.

About the speaker

Wayne Luk is Professor of Computer Engineering at Imperial College London. His current research interests include theory and practice of customising designs for specific application domains such as machine learning and computational genomics, and compilation techniques and tools for high-performance computers and embedded systems. He is a fellow of the Royal Academy of Engineering, the IEEE, and the BCS. He received the Research Excellence Award from Imperial College London, and 15 awards for his publications from various international conferences.