576 citations · 1k across the 23 of their papers we have counts for
6 papers · 1 filter
Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo
Qiang Heng, Hua Zhou, Eric C. Chi
Proximal Markov Chain Monte Carlo is a novel construct that lies at the intersection of Bayesian computation and convex optimization, which helped popularize the use of nondifferen…
MM Algorithms for Variance Components Models
Hua Zhou, Liuyi Hu, Jin Zhou +1
Variance components estimation and mixed model analysis are central themes in statistics with applications in numerous scientific disciplines. Despite the best efforts of generatio…
A Generic Path Algorithm for Regularized Statistical Estimation
Hua Zhou, Yichao Wu
Regularization is widely used in statistics and machine learning to prevent overfitting and gear solution towards prior information. In general, a regularized estimation problem mi…
Path Following and Empirical Bayes Model Selection for Sparse Regression
Hua Zhou, Artin Armagan, David B. Dunson
In recent years, a rich variety of regularization procedures have been proposed for high dimensional regression problems. However, tuning parameter choice and computational efficie…
A Path Algorithm for Constrained Estimation
Hua Zhou, Kenneth Lange
Many least squares problems involve affine equality and inequality constraints. Although there are variety of methods for solving such problems, most statisticians find constrained…
Graphics Processing Units and High-Dimensional Optimization
Hua Zhou, Kenneth Lange, Marc A. Suchard
This paper discusses the potential of graphics processing units (GPUs) in high-dimensional optimization problems. A single GPU card with hundreds of arithmetic cores can be inserte…