Graph-Based Perspective on Variable Elimination

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Compétences que vous apprendrez

Inference, Gibbs Sampling, Markov Chain Monte Carlo (MCMC), Belief Propagation

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LL

Mar 12, 2017

Thanks a lot for professor D.K.'s great course for PGM inference part. Really a very good starting point for PGM model and preparation for learning part.

YP

May 29, 2017

I learned pretty much from this course. It answered my quandaries from the representation course, and as well deepened my understanding of PGM.

À partir de la leçon
Variable Elimination
This module presents the simplest algorithm for exact inference in graphical models: variable elimination. We describe the algorithm, and analyze its complexity in terms of properties of the graph structure.

Enseigné par

  • Daphne Koller

    Daphne Koller

    Professor

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