Graphon Cross-Validation with Application to Drug Repurposing
Huimin Cheng, PhD
Assistant Professor
Department of Biostatistics |
Boston University
WHEN: Wednesday, Sept 11, 2024, from 3:30 to 4:30 p.m.
WHERE: Hybrid | 2001 McGill College Avenue, Rm 1201 | Zoom
NOTE: Huimin Cheng will be presenting from Boston
Abstract
Graphon, short for graph function, provides a generative model for networks. In recent decades, various methods for graphon estimation have been proposed. The success of most graphon estimation methods depends on the proper specification of hyperparameters. While some network cross-validation methods have been proposed, they suffer from restrictive model assumptions, expensive computational costs, and a lack of theoretical guarantees. To address these issues, we propose a graphon cross-validation (GraphonCV) method. The asymptotic properties of GraphonCV are established. The effectiveness of the proposed method in terms of both computation and accuracy is demonstrated through extensive simulation studies and real drug repurposing examples.
Speaker Bio
Dr. Huimin Cheng is an Assistant Professor in the Department of Biostatistics at Boston University and a Rafik B. Hariri Junior Faculty Fellow. She received her Ph.D. in statistics from the University of Georgia in 2023. Her methodological research focuses on statistical network analysis, graph deep learning, causal inference, machine learning, and Riemannian geometry. For more information, please visit: https://sites.google.com/view/huimincheng/home/.