CSGSA

GRaDS talk: Mitigating the impact of IID violations in federated learning systems

by Joel Wolfrath on 2022-04-15

Abstract

The proliferation of smart devices has caused data to be generated in an increasingly distributed manner. Due to high cost and privacy concerns, this data cannot necessarily be transferred to a centralized location for model training. Furthermore, computational resources and data distributions may vary substantially from location to location. We present a federated learning system that addresses these sources of heterogeneity and substantially reduces model training time in these distributed settings.

About the speaker

Joel Wolfrath is a third-year Ph.D. candidate in the Department of Computer Science & Engineering, advised by Dr. Abhishek Chandra. His interests include distributed systems, edge computing, and statistics.