EE论坛（358期）：Advances in machine learning techniques with applications to communications and image processing
讲座题目：Advances in machine learning techniques with applications to communications and image processing
主讲人： Prof. Yik-Chung Wu
报告简介：This talk shall briefly overview the recent advances of machine learning techniques at the University of Hong Kong, andhow they are applied to communications and image processing problems. The specific topics to be introduced include Gaussian belief propagation, variational statistical inference and tensor processing.Surprisingly, many machine learning models are general enough to tackle problems that are seemingly unrelated.
The applications to be covered include synchronization in large-scale networks, channel estimation under high mobility, power state estimation in smart grid, massive MIMO channel estimation, face classification, surveillance video objects separation, and image de-noising.
Keywords: Machine learning, Image processing, Gaussian belief propagation.
主讲人简介：Yik-Chung Wu received the B.Eng. (EEE) degree in 1998 and the M.Phil. degree in 2001 from the University of Hong Kong (HKU). He received the Croucher Foundation scholarship in 2002 to study Ph.D. degree at Texas A&M University, College Station, and graduated in 2005. From August 2005 to August 2006, he was with the Thomson Corporate Research, Princeton, NJ, as a Member of Technical Staff. Since September 2006, he has been with HKU, currently as an Associate Professor. He was a visiting scholar at Princeton University, in the summers of 2011 and 2015. His research interests are in general area of signal processing, machine learning and communication systems, and in particular distributed signal processing and communications; and large-scale and robust optimization. Dr. Wu served as an Editor for IEEE Communications Letters, is currently an Editor for IEEE Transactions on Communications and Journal of Communications and Networks.