With the superior capability of discovering intricate structure of large data sets, machine learning has been widely applied in various areas including wireless networking. Modern wireless networks have seen a tremendous increase in size and complexity, where the capacity optimization urgently calls for an innovative and efficient computing paradigm. This talk gives our recent studies on how to exploit deep learning for significant performance gain in wireless network optimization. We start with a discussion about our vision of the supremacy of machine learning (ML), trying to fundamentally understand where and how the ML based approaches show advantages versus the conventional modeling-based approaches. We then demonstrate that ML has the unique capability to identify latent structure information, embedded in historical solved optimization instances but invisible to traditional algorithms, leading to new algorithms that can greatly mitigate the computation overhead while maintain a good performance. New ML techniques have been developed to extract and leverage the structure information from three perspectives: topology-level, algorithm-level, and application-level.
Yu Cheng received the B.E. and M.E. degrees in electronic engineering from Tsinghua University, Beijing, China, in 1995 and 1998, respectively, and the Ph.D. degree in electrical and computer engineering from the University of Waterloo, Waterloo, ON, Canada, in 2003. He is currently a Full Professor with the Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, USA. His current research interests include wireless network performance analysis, machine learning, age of information, and network security. Dr. Cheng was a recipient of the Best Paper Award at QShine 2007, the IEEE ICC 2011, the Runner-Up Best Paper Award at ACM MobiHoc 2014, the National Science Foundation CAREER Award in 2011, and the IIT Sigma Xi Research Award in the Junior Faculty Division in 2013. He has served as several Symposium Co-Chairs for IEEE ICC and IEEE GLOBECOM, and the Technical Program Committee Co-Chair for WASA 2011 and ICNC 2015. He was a founding Vice Chair of the IEEE ComSoc Technical Subcommittee on Green Communications and Computing. He was an IEEE ComSoc Distinguished Lecturer from 2016 to 2017. He is an Associate Editor for the IEEE Transactions on Vehicular Technology, IEEE Internet of Things Journal, and IEEE Wireless Communications.