2 citations · 8 across the 9 of their papers we have counts for
5 papers · 1 filter
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…
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…
Mean field variational Bayesian inference for support vector machine classification
Jan Luts, John T. Ormerod
A mean field variational Bayes approach to support vector machines (SVMs) using the latent variable representation on Polson & Scott (2012) is presented. This representation allows…
On semiparametric regression with O'Sullivan penalised splines
M. P. Wand, J. T. Ormerod
This is an exposé on the use of O'Sullivan penalised splines in contemporary semiparametric regression, including mixed model and Bayesian formulations. O'Sullivan penalised spline…