Estimating Dependency Structure as a Hidden Variable

Part of Advances in Neural Information Processing Systems 10 (NIPS 1997)

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Marina Meila, Michael Jordan


This paper introduces a probability model, the mixture of trees that can account for sparse, dynamically changing dependence relationships. We present a family of efficient algorithms that use EM and the Minimum Spanning Tree algorithm to find the ML and MAP mixture of trees for a variety of priors, including the Dirichlet and the MDL priors.