February 15, 2019 –
Presenter: Tianyi Chen, PhD candidate, UMN
Title: Towards Edge Intelligence: Machine Learning Meets Internet-of-Things
Date: Friday, February 15
Location: HBL 1947 Room
Internet-of-Things (IoT) envisions an intelligent infrastructure of networked smart devices offering computing, communication, and control services. Considering the massive amount of IoT devices, centralized machine learning via cloud computing incurs considerable overhead, and raises serious privacy concerns. Today, the widespread consensus is that besides data centers at the cloud, future machine learning tasks have to be performed starting from the network edge, namely IoT devices. This is an important step towards edge intelligence. In this context, we will highlight key challenges in machine learning at the edge, including communication overhead, heterogeneity, and adversarial attacks. Wedding advanced optimization techniques with system-level considerations, we will introduce novel methods for solving various distributed machine learning and reinforcement learning problems on IoT devices. Our methods are simple to implement, and they come with rigorous performance guarantees in terms of convergence and communication reduction. We will corroborate analytical guarantees with impressive empirical results, which offer valuable insights to guide future design of distributed machine learning algorithms.
Tianyi Chen received the B. Eng. degree in Communication Science and Engineering from Fudan University, and the M.Sc. degree in Electrical and Computer Engineering (ECE) from the University of Minnesota (UMN), in 2014 and 2016, respectively. Since July 2016, he has been working toward his Ph.D. degree in ECE at UMN. During 2017-2018, he has been a visiting scholar at Harvard University, University of California, Los Angeles, and University of Illinois Urbana-Champaign. His research interests lie in optimization and machine learning with applications to large-scale networked systems such as Internet-of-Things, next-generation computing systems, and energy systems. He was a Best Student Paper Award finalist in the 2017 Asilomar Conf. on Signals, Systems, and Computers. He received the National Scholarship from China in 2013, the UMN ECE Department Fellowship in 2014, and the UMN Doctoral Dissertation Fellowship in 2017.