On the Computational Complexity of High-Dimensional Bayesian Variable Selection

29 May 2015Yun YangMartin J. WainwrightMichael I. Jordan

We study the computational complexity of Markov chain Monte Carlo (MCMC) methods for high-dimensional Bayesian linear regression under sparsity constraints. We first show that a Bayesian approach can achieve variable-selection consistency under relatively mild conditions on the design matrix... (read more)

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