In this paper we pursue a Bayesian interpretation of sparsity in the kernel setting by making use of a mix- ture of a point-mass distribution and prior that we ...

'' We provide a theoretical analysis of the posterior consistency of a Bayesian model choice procedure based on this prior. We also establish the asymptotic ...

In this paper we pursue a Bayesian interpretation of sparsity in the kernel setting by making use of a mix- ture of a point-mass distribution and prior that we ...

A Bayesian interpretation of sparsity in the kernel setting is pursued by making use of a mixture of a point-mass distribution and prior that is referred to ...

In this paper we pursue a Bayesian interpretation of sparsity in the kernel setting by making use of a mixture of a point-mass distribution and prior that we ...

... Silverman's g-prior", which provides a theoretical analysis of the posterior consistency of a Bayesian model choice procedure based on this prior. Expand. 11 ...

Abstract. We examine necessary and sufficient conditions for posterior consis- tency under g-priors, including extensions to hierarchical and empirical ...

Posterior consistency of the Silverman g-prior in Bayesian model choice. Author(s): Zhang, Zhihua ; Jordan, Michael ; Yeung, Dit Yan. Source: Twenty-Second ...

» Posterior Consistency of the Silverman g-prior in Bayesian M... ... This paper describes a technique for learning both the number of states and the topologyof ...

Posterior Consistency of the Silverman g-prior in Bayesian Model Choice. Zhihua Zhang, Michael I. Jordan, Dit-Yan Yeung. 2008 Neural Information Processing ...