Approximate inference algorithms for two-layer Bayesian networks (2000)  (Make Corrections)  (1 citation)
Andrew Y. Ng Computer Science Division UC Berkeley Berkeley, CA 94720...

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Abstract: We present a class of approximate inference algorithms for graphical models of the QMR-DT type. We give convergence rates for these algorithms and for the Jaakkola and Jordan (1999) algorithm, and verify these theoretical predictions empirically. We also present empirical results on the difficult QMR-DT network problem, obtaining performance of the new algorithms roughly comparable to the Jaakkola and Jordan algorithm. 1 Introduction The graphical models formalism provides an appealing... (Update)

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.... widely used as a benchmark for approximate inference algorithms [Shwe and Cooper, 1991, D Ambrosio, 1994, Murphy et al. 1999, Ng and Jordan, 2000] The set of observable nodes in the QMR DT are called ndings 1 and the unobservable nodes are diseases. When evaluating...

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BibTeX entry:   (Update)

Ng, A. Y. and Jordan, M. I. (2000). Approximate inference algorithms for two{ layer Bayesian networks. In Advances in Neural Information Processing Systems, volume 12. MIT Press. http://citeseer.ist.psu.edu/article/ng00approximate.html   More

@misc{ ng00approximate,
  author = "A. Ng and M. Jordan",
  title = "Approximate inference algorithms for two{ layer Bayesian networks",
  text = "Ng, A. Y. and Jordan, M. I. (2000). Approximate inference algorithms for
    two{ layer Bayesian networks. In Advances in Neural Information Processing
    Systems, volume 12. MIT Press.",
  year = "2000",
  url = "citeseer.ist.psu.edu/article/ng00approximate.html" }
Citations (may not include all citations):
192   An introduction to variational methods for graphical models - Jordan, Ghahramani et al. - 1998  ACM   DBLP
72   Loopy belief propagation for approximate inference: An empir.. - Murphy, Weiss et al. - 1999  DBLP
21   A tractable inference algorithm for diagnosing multiple dise.. (context) - Heckerman - 1989  ACM   DBLP
19   Variational probabilistic inference and the QMR-DT network - Jaakkola, Jordan - 1999  DBLP
6   Large deviation methods for approximate probabilistic infere.. - Kearns, Saul - 1998  DBLP
6   Convergence condition of the TAP equation for the infinite-r.. (context) - Plefka - 1982
2   Variational cumulant expansions for intractable distribution.. - Barber, van de - 1999  DBLP

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