Past talk · AI/ML Seminar Series
Adaptive Online Scalable Learning with Graph Feedback
Assistant Professor of Electrical Engineering and Computer Science, University of California, Irvine
- Date & time
- Monday, November 7, 2022 · 1:00 PM
- Location
- Donald Bren Hall 4011
Abstract
We live in an era of data deluge, where pervasive media collect massive amounts of data, often in a streaming fashion. The sheer volume makes batch analytics impossible, and data are noisy, incomplete, and prone to outliers, so analytics must often be performed in real-time. This talk introduces an online scalable function approximation scheme that adaptively learns and tracks the sought nonlinear function on the fly with quantifiable performance guarantees, even in adversarial environments. Building on this framework, a scalable online learning approach with graph feedback is outlined for online learning with possibly related models, showcased on several real-world datasets.
About the speaker
Yanning Shen is an assistant professor with the EECS department at UC Irvine. She received her Ph.D. from the University of Minnesota in 2019, was selected as a Rising Star in EECS by Stanford in 2017, and received the Google Research Scholar Award and the Hellman Fellowship in 2022. Her research spans machine learning, network science, data science, and signal processing.