报告题目：Edge Learning: Theory, Algorithm and System Design
报告地点：腾讯会议 ID: 416 7814 4962
Driving by flourishing of both distributed machine learning and mobile edge computing, there is a stringent need to combine the advantages of these technologies so as to provide the learning tasks with high performance. Edge Learning, as an emerging learning concept, is complementary to the cloud-based methods for big data analytics by enabling distributed edge nodes to cooperatively train models and conduct inferences with their local data. This talk will focus on learning paradigms, fundamental theories, and enabling technologies for Edge Learning. We will first explain the background and motivation for AI running at the network edge. Then, we will review the challenge issues existing in Edge Learning. Furthermore, we will provide an overview of the overarching architectures, frameworks, and emerging key technologies for learning performance, security, privacy, and incentive issues toward training/inference at the network edge. Finally, we will discuss future research opportunities on Edge Learning.
Song Guo is a Full Professor at Department of Computing, The Hong Kong Polytechnic University. He also holds a Changjiang Chair Professorship awarded by the Ministry of Education of China. Prof. Guo is a Fellow of the Canadian Academy of Engineering and a Fellow of the IEEE (Computer Society). His research interests are mainly in big data, edge AI, mobile computing, and distributed systems. He published many papers in top venues with wide impact in these areas and was recognized as a Highly Cited Researcher (Clarivate Web of Science). He is the recipient of over a dozen Best Paper Awards from IEEE/ACM conferences, journals, and technical committees. Prof. Guo is the Editor-in-Chief of IEEE Open Journal of the Computer Society and the Chair of IEEE Communications Society (ComSoc) Space and Satellite Communications Technical Committee. He was an IEEE ComSoc Distinguished Lecturer and a member of IEEE ComSoc Board of Governors. He has served for IEEE Computer Society on Fellow Evaluation Committee, and been named on editorial board of a number of prestigious international journals like IEEE TPDS, IEEE TCC, IEEE TETC, etc. He has also served as chairs of organizing and technical committees of many international conferences.