16 citations · 21 across the 4 of their papers we have counts for
4 papers
Functional Linear Regression for Partially Observed Functional Data
Yafei Wang, Tingyu Lai, Bei Jiang +2
In the functional linear regression model, many methods have been proposed and studied to estimate the slope function while the functional predictor was observed in the entire doma…
Negative Log Likelihood Ratio Loss for Deep Neural Network Classification
Donglai Zhu, Hengshuai Yao, Bei Jiang +1
In deep neural network, the cross-entropy loss function is commonly used for classification. Minimizing cross-entropy is equivalent to maximizing likelihood under assumptions of un…
Advanced Algorithms for Penalized Quantile and Composite Quantile Regression
Matthew Pietrosanu, Jueyu Gao, Linglong Kong +2
In this paper, we discuss a family of robust, high-dimensional regression models for quantile and composite quantile regression, both with and without an adaptive lasso penalty for…
Sparse Wavelet Estimation in Quantile Regression with Multiple Functional Predictors
Dengdeng Yu, Li Zhang, Ivan Mizera +2
In this manuscript, we study quantile regression in partial functional linear model where response is scalar and predictors include both scalars and multiple functions. Wavelet bas…