Learning max-weight discriminative forests

  title={Learning max-weight discriminative forests},
  author={Vincent Y. F. Tan and John W. Fisher and Alan S. Willsky},
  journal={2008 IEEE International Conference on Acoustics, Speech and Signal Processing},
We present a method for sequential learning of increasingly complex graphical models for discriminating between two hypotheses. We generate forests for each hypothesis, each with no more edges than a spanning tree, which optimize an information-theoretic criteria. The method relies on a straightforward extension of the efficient max-weight spanning tree (MWST) algorithm by incorporating multivalued edge-weights. Each iteration produces nested forests with increasing number of edges; each… CONTINUE READING

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