Libra

author: Daniel Lowd, Department of Computer and Information Science, University of Oregon
published: July 20, 2010,   recorded: June 2010,   views: 108
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Description

The Libra machine learning toolkit includes implementations of a variety of algorithms for learning and inference with Bayesian networks and arithmetic circuits:

Learning algorithms -- Structure learning for BNs and ACs; Chow-Liu algorithm; AC weight learning

Inference algorithms - Mean field, belief propagation, Gibbs sampling, AC variable elimination, AC exact inference

Libra's strength is exploiting context-specific independence (such as decision tree CPDs) to allow exact inference in models with high treewidth.

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Download slides icon Download slides: icml2010_lowd_libra_01.pdf (797.0 KB)

Download slides icon Download slides: icml2010_lowd_libra_01.pptx (122.2 KB)


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