973 citations · 4.4k across the 28 of their papers we have counts for
28 papers
Enhanced Response Envelope via Envelope Regularization
Oh-Ran Kwon, Hui Zou
The response envelope model provides substantial efficiency gains over the standard multivariate linear regression by identifying the material part of the response to the model and…
High-dimensional Censored Regression via the Penalized Tobit Likelihood
Tate Jacobson, Hui Zou
High-dimensional regression and regression with a left-censored response are each well-studied topics. In spite of this, few methods have been proposed which deal with both of thes…
Enveloped Huber Regression
Le Zhou, R. Dennis Cook, Hui Zou
Huber regression (HR) is a popular robust alternative to the least squares regression when the error follows a heavy-tailed distribution. We propose a new method called the envelop…
An Alternating Manifold Proximal Gradient Method for Sparse PCA and Sparse CCA
Shixiang Chen, Shiqian Ma, Lingzhou Xue +1
Sparse principal component analysis (PCA) and sparse canonical correlation analysis (CCA) are two essential techniques from high-dimensional statistics and machine learning for ana…
Bayesian Inference for High Dimensional Changing Linear Regression with Application to Minnesota House Price Index Data
Abhirup Datta, Hui Zou, Sudipto Banerjee
In many applications, the dataset under investigation exhibits heterogeneous regimes that are more appropriately modeled using piece-wise linear models for each of the data segment…
CoCoLasso for High-dimensional Error-in-variables Regression
Abhirup Datta, Hui Zou
Much theoretical and applied work has been devoted to high-dimensional regression with clean data. However, we often face corrupted data in many applications where missing data and…