2 citations · 8 across the 9 of their papers we have counts for
9 papers
The Lasso Distribution: Properties, Sampling Methods, and Applications in Bayesian Lasso Regression
Mohammad Javad Davoudabadi, Jonathon Tidswell, Samuel Muller +2
In this paper, we introduce a new probability distribution, the Lasso distribution. We derive several fundamental properties of the distribution, including closed-form expressions…
Skew-Normal Posterior Approximations
Jackson Zhou, Clara Grazian, John Ormerod
Many approximate Bayesian inference methods assume a particular parametric form for approximating the posterior distribution. A multivariate Gaussian distribution provides a conven…
Moment Propagation
John Ormerod, Weichang Yu, Mohammad Javad Davoudabadi +1
Mean-field variational Bayes is a fast and scalable approach to approximate Bayesian inference, but its independence assumptions often lead to underestimated posterior uncertainty.…
Variational Discriminant Analysis with Variable Selection
Weichang Yu, John T. Ormerod, Michael Stewart
A fast Bayesian method that seamlessly fuses classification and hypothesis testing via discriminant analysis is developed. Building upon the original discriminant analysis classifi…
Variational Nonparametric Discriminant Analysis
Weichang Yu, Lamiae Azizi, John T. Ormerod
Variable selection and classification are common objectives in the analysis of high-dimensional data. Most such methods make distributional assumptions that may not be compatible w…
Diagonal Discriminant Analysis with Feature Selection for High Dimensional Data
Sarah Elizabeth Romanes, John Thomas Ormerod, Jean YH Yang
We introduce a new method of performing high dimensional discriminant analysis, which we call multiDA. We achieve this by constructing a hybrid model that seamlessly integrates a m…