546 citations · 1.2k across the 35 of their papers we have counts for
35 papers
A Flexible Quasi-Copula Distribution for Statistical Modeling
Sarah S. Ji, Benjamin B. Chu, Hua Zhou +1
Copulas, generalized estimating equations, and generalized linear mixed models promote the analysis of grouped data where non-normal responses are correlated. Unfortunately, parame…
Feature Selection for Vertex Discriminant Analysis
Alfonso Landeros, Tong Tong Wu, Kenneth Lange
We revisit vertex discriminant analysis (VDA) from the perspective of proximal distance algorithms. By specifying sparsity sets as constraints that directly control the number of a…
A Sharper Computational Tool for Regression
Xiaoqian Liu, Eric C. Chi, Kenneth Lange
Building on previous research of Chi and Chi (2022), the current paper revisits estimation in robust structured regression under the criterion. We adopt the ma…
Algorithms for Sparse Support Vector Machines
Alfonso Landeros, Kenneth Lange
Many problems in classification involve huge numbers of irrelevant features. Model selection reveals the crucial features, reduces the dimensionality of feature space, and improves…
A Proximal Distance Algorithm for Likelihood-Based Sparse Covariance Estimation
Jason Xu, Kenneth Lange
This paper addresses the task of estimating a covariance matrix under a patternless sparsity assumption. In contrast to existing approaches based on thresholding or shrinkage penal…
Nonconvex Optimization via MM Algorithms: Convergence Theory
Kenneth Lange, Joong-Ho Won, Alfonso Landeros +1
The majorization-minimization (MM) principle is an extremely general framework for deriving optimization algorithms. It includes the expectation-maximization (EM) algorithm, proxim…