Hi all,
The ASA San Antonio Chapter will host a virtual seminar on Friday, March 6, at 10 AM. If your schedule allows, we warmly invite you to join and support this chapter event.
Detailed seminar information is provided below.
Thank you very much, and we hope to see you there!
ASA San Antonio Chapter Virtual Seminar
"High-resolution feature identification in
high-dimensional clustering"
Dr. Xiwei Tang
Associate Professor
Department of Mathematical Science
University of Texas at Dallas
Friday, March 6, 10 am CST
Zoom: https://utsa.zoom.us/j/95583225432
Abstract: Interpretable clustering, which involves identifying heterogeneous subgroups and the informative features that define them, is a critical yet challenging task across various fields, including omics studies, clinical research, and policy evaluation. Existing methods typically either focus narrowly on global feature heterogeneity or treat feature selection and clustering as separate tasks, failing to account for their interaction. To address these limitations, we propose a novel unsupervised learning approach, PAirwise REciprocal fuSE (PARSE), which concurrently pinpoints cluster-specific informative features and conducts high-dimensional clustering effectively. PARSE provides a high-resolution map of features segmenting the population by leveraging a new regularization framework that heavily penalizes features with minor differences across clusters. We establish the oracle property for PARSE and derive lower bounds for clustering and cluster-specific feature identification, demonstrating the method's optimality. Additionally, we propose an adaptive Expectation-Maximization algorithm, ensuring both statistical guarantees and computational scalability. Extensive numerical studies demonstrate PARSE's superiority over existing methods. In applying single-cell RNA sequencing data to identify gene signatures in human pancreatic cell subtypes, PARSE outperforms leading methods in both subtype detection and corresponding feature identification.
Bio: Dr. Xiwei Tang is currently an Associate Professor in the Department of Mathematical Science at the University of Texas at Dallas, and also serves as the co-director of the Texas AI Research Institute (TAIRI) at UT Dallas and the Associate Editor of JASA (T&M). Prior to that, Dr. Tang was an Associate Professor in the Department of Statistics at the University of Virginia. His research focuses on statistics and machine learning, aiming to develop innovative methodologies for complex, modern real-world data analysis, especially in data heterogeneity modeling, multi-modality data analysis, tensor data and imaging analysis, spatial-temporal processes, transfer learning, and federated learning.
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Yuexia Zhang
Assistant Professor
Department of Statistics and Data Science
The University of Texas at San Antonio
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