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Abstract: Precision achieved by stochastic sampling algorithms for Bayesian networks typically deteriorates in face of extremely unlikely evidence. To address this problem... (Update)
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BibTeX entry: (Update)
@misc{ yuan-importance,
author = "Changhe Yuan and Marek J. Druzdzel",
title = "An Importance Sampling Algorithm Based on Evidence Pre-Propagation",
booktitle = "Proceedings of the 19th Annual Conference on Uncertainty in Artificial
Intelligence (UAI03)",
url = "citeseer.comp.nus.edu.sg/713590.html" }
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31 line student modeling for coached problem solving using Baye.. - Conati, Gertner et al. - 1997
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4 A Monte Carlo algorithm for probabilistic propagation in bel.. (context) - Hernandez, Moral et al. - 1998
2 Importance sampling in Bayesian networks using probability t.. - Salmeron, Cano et al. - 2000
1 BN-AIS: An adaptive importance sampling algorithm for eviden.. (context) - Cheng, Druzdzel - 2000
1 Bayesian multivariate micro-aggregation under the Hellinger'.. - Kokolakis, Nanopoulos - 2001
Documents on the same site (http://www.sis.pitt.edu/~cyuan/):
Annealed MAP - Yuan, Lu, Druzdzel (Correct)
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