Speaker: Shouyang Wang (Auburn University)

 

Title: Functional data analysis via deep neural networks. 

 

Abstract: In this presentation, I will first propose a deep neural networks based method to perform nonparametric regression for functional data. The proposed estimators are based on sparsely connected deep neural networks with ReLU activation function. Convergence rate in terms of the empirical norm of the proposed deep neural networks estimator are provided. I will show how to properly select of the architecture parameters by cross-validation by using our own developed R package. Finally, I will present how to analyze positron emission tomography images of patients with Alzheimer disease obtained from the Alzheimer Disease Neuroimaging Initiative database. 

 

 

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