All seminars will take place on Fridays at 11 a.m. in DBH 6011. Check seminar details below.
October 22, 2021
11:00am - 12:00pm
Adaptive Online Scalable Learning with Graph Feedback
We live in an era of data deluge, where pervasive media collect massive amounts of data, often in a streaming fashion. Learning from these dynamic and large volumes of data is hence expected to bring significant science and engineering advances along with consequent improvements in quality of life. However, with the blessings come big challenges. The sheer volume of data makes it impossible to run analytics in batch form. Large-scale datasets are noisy, incomplete, and prone to outliers. As many sources continuously generate data in real time, it is often impossible to store all of it. Thus, analytics must often be performed in real time, without a chance to revisit past entries. In response to these challenges, this talk will first introduce an online scalable function approximation scheme that is suitable for various machine learning tasks. The novel approach adaptively learns and tracks the sought nonlinear function ‘on the fly’ with quantifiable performance guarantees, even in adversarial environments with unknown dynamics. Building on this robust and scalable function approximation framework, a scalable online learning approach with graph feedback will be outlined next for online learning with possibly related models. Effectiveness of the novel algorithms will be showcased in several real-world datasets.
Yanning Shen is an assistant professor with EECS department at the University of California, Irvine. She received her Ph.D. degree from the University of Minnesota, Twin Cities in 2019. Her research interests include machine learning, data science, network science, optimization and statistical signal processing. She was a Best Student Paper Award finalist of the 2017 Asilomar Conference on Signals, Systems, and Computers, the 2017 and 2019 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing. She was selected as Rising Stars in EECS by Stanford University in 2017 and received the UMN Doctoral Dissertation Fellowship in 2018. She received Microsoft Academic Grants for AI Research in 2021. More detailed information can be found at: https://sites.google.com/uci.edu/yanning-shen