Decoupling shrinkage and selection in Bayesian linear models: a   posterior summary perspective
  Selecting a subset of variables for linear models remains an active area of research. This paper reviews many of the recent contributions to the Bayesian model selection and shrinkage prior literature. A posterior variable selection summary is proposed, which distills a full posterior distribution over regression coefficients into a sequence of sparse linear predictors. 
P. Richard Hahn and Carlos M. Carvalho
stat.ME