95 citations · 196 across the 14 of their papers we have counts for
14 papers
Learning Topic Models: Identifiability and Finite-Sample Analysis
Yinyin Chen, Shishuang He, Yun Yang +1
Topic models provide a useful text-mining tool for learning, extracting, and discovering latent structures in large text corpora. Although a plethora of methods have been proposed…
Bayesian Regularization for Graphical Models with Unequal Shrinkage
Lingrui Gan, Naveen N. Narisetty, Feng Liang
We consider a Bayesian framework for estimating a high-dimensional sparse precision matrix, in which adaptive shrinkage and sparsity are induced by a mixture of Laplace priors. Bes…
Discriminative Similarity for Clustering and Semi-Supervised Learning
Yingzhen Yang, Feng Liang, Nebojsa Jojic +3
Similarity-based clustering and semi-supervised learning methods separate the data into clusters or classes according to the pairwise similarity between the data, and the pairwise…
An Empirical Bayes Approach for High Dimensional Classification
Yunbo Ouyang, Feng Liang
We propose an empirical Bayes estimator based on Dirichlet process mixture model for estimating the sparse normalized mean difference, which could be directly applied to the high d…
A Nonparametric Bayesian Approach for Sparse Sequence Estimation
Yunbo Ouyang, Feng Liang
A nonparametric Bayes approach is proposed for the problem of estimating a sparse sequence based on Gaussian random variables. We adopt the popular two-group prior with one compone…
An Ensemble EM Algorithm for Bayesian Variable Selection
Jin Wang, Feng Liang, Yuan Ji
We study the Bayesian approach to variable selection in the context of linear regression. Motivated by a recent work by Rockova and George (2014), we propose an EM algorithm that r…