10 citations · 21 across the 7 of their papers we have counts for
8 papers
Nonparametric Quantile Regression: Non-Crossing Constraints and Conformal Prediction
Wenlu Tang, Guohao Shen, Yuanyuan Lin +1
We propose a nonparametric quantile regression method using deep neural networks with a rectified linear unit penalty function to avoid quantile crossing. This penalty function is…
Statistical Inference in High-dimensional Generalized Linear Models with Streaming Data
Lan Luo, Ruijian Han, Yuanyuan Lin +1
In this paper we develop an online statistical inference approach for high-dimensional generalized linear models with streaming data for real-time estimation and inference. We prop…
Deep Quantile Regression: Mitigating the Curse of Dimensionality Through Composition
Guohao Shen, Yuling Jiao, Yuanyuan Lin +2
This paper considers the problem of nonparametric quantile regression under the assumption that the target conditional quantile function is a composition of a sequence of low-dimen…
Robust Nonparametric Regression with Deep Neural Networks
Guohao Shen, Yuling Jiao, Yuanyuan Lin +1
In this paper, we study the properties of robust nonparametric estimation using deep neural networks for regression models with heavy tailed error distributions. We establish the n…
Combining case-control studies for identifiability and efficiency improvement in logistic regression
Wenlu Tang, Yuanyuan Lin, Linlin Dai +1
Can two separate case-control studies, one about Hepatitis disease and the other about Fibrosis, for example, be combined together? It would be hugely beneficial if two or more sep…
Online Debiased Lasso for Streaming Data
Ruijian Han, Lan Luo, Yuanyuan Lin +1
We propose an online debiased lasso (ODL) method for statistical inference in high-dimensional linear models with streaming data. The proposed ODL consists of an efficient computat…