Comet Calendar Event Details

Mathematical Sciences Colloquium by Lingzhou Xue
Friday, Nov. 8
2 p.m. - 3 p.m. Location: CB1 1.104

Lingzhou Xue

Penn State University

Robust High-Dimensional Regression with Coefficient Thresholding and its Application to Imaging Data Analysis

It is of importance to develop statistical techniques to analyze high-dimensional data in the presence of both complex dependence and possible outliers in real-world applications such as the imaging data analyses. We propose a new robust high-dimensional regression with coefficient thresholding, in which an efficient nonconvex estimation procedure is proposed through the thresholding function and robust Huber loss. The proposed regularization method accounts for complex dependence structures in predictors and is robust against outliers. Theoretically, we carefully analyze the landscape of the nonconvex loss function for the proposed method, which enables us to establish both statistical and computational consistency under the high-dimensional setting. The finite sample properties of the proposed method are demonstrated by extensive simulation studies. An illustration of real-world application concerns a scalar-on-image regression analysis of the intelligence quotient score based on resting-state functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange study.

Coffee to be served 30 minutes prior to the talk in the alcove outside of FO 2.406.

 

 

Persons with disabilities may submit a request for accommodations to participate in this event at UT Dallas' ADA website. You may also call (972) 883-5331 for assistance or send an email to [email protected]. All requests should be received no later than 2 business days prior to the event.
Contact Info:
Viswanath Ramakrishna, 972-883-6873
Questions? Email me.

Tagged as Lectures/Seminars, Professional Dev.
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