Machine Learning at the Wireless Edge

Wireless networks can be used as platforms for machine learning, taking advantage of the fact that data is often collected at the edges of networks, and also mitigating the latency and privacy concerns that backhauling data to the cloud can entail. Focusing primarily on federated learning, this talk will discuss several issues arising in this context including the effects of wireless transmission on learning performance, the allocation of wireless resources to learning, and privacy leakage.

Co-sponsored by: Computers and Instrumentation Chapter

Speaker(s): Prof. Vincent Poor,

Agenda:
6:15 pm: Hosting Speaker – Webex Check

6:30 pm: Introducing Speaker

6:30 – 7:30 pm Distinguish Lecture (Vincent Poor of Princeton University)

7:30 – 8 pm Questions and Answers

8:00 pm Closure

Princeton, New Jersey, United States, 08544, Virtual: https://events.vtools.ieee.org/m/307252