Bayesian Structure Learning for Markov Random Fields with a Spike and Slab Prior

9 Aug 2014Yutian ChenMax Welling

In recent years a number of methods have been developed for automatically learning the (sparse) connectivity structure of Markov Random Fields. These methods are mostly based on L1-regularized optimization which has a number of disadvantages such as the inability to assess model uncertainty and expensive crossvalidation to find the optimal regularization parameter... (read more)

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