Joseph C. Ford Professor of Engineering
Seminar: Random Walk on a Tree for Stochastic Optimization and Learning
Abstract: The problem of searching for a few rare events of interest among a massive number of possibilities is ubiquitous. The rare events may represent opportunities with exceptional returns, extremely useful information in a deluge of data, or anomalies with potentially catastrophic consequences. The key challenges are that the search space is massive, observations are noisy and costly, and stochastic models of the rare events are unknown. Example applications include identifying infected individuals in a large population, detecting intrusions and attacks in large communication/computer networks, and the general problem of stochastic optimization for finding the optimal point of an unknown objective function in a high-dimensional space. We discuss in this talk a solution framework and its optimality in terms of learning efficiency. The key idea of the approach is to devise a biased random walk on a tree-based hierarchical representation of the search space. This is a joint work with Sudeep Salgia and Sattar Vakili.
About the speaker: Qing Zhao joined Cornell in 2015, where she is the Joseph C. Ford Professor of Engineering. Prior to that, she was a professor in the Department of Electrical and Computer Engineering at UC Davis from 2004 to 2015 and a system engineer with Aware., Inc. from 2001 to 2003. She earned her Ph.D. degree in electrical engineering from Cornell University in 2001. Professor Zhao is a Fellow of IEEE, a Marie Skłodowska-Curie Fellow of the European Union research and innovation program, a Jubilee Chair Professor of Chalmers University during her 2018-2019 sabbatical leave, and a Distinguished Lecturer of the IEEE Signal Processing Society.
Host: UVA Engineering chapter of the IEEE Signal Processing Society