Exploiting Evidence in Probabilistic Inference
Abstract
We define the notion of compiling a Bayesian network with evidence and provide a specific approach for evidence-based compilation, which makes use of logical processing. The approach is practical and advantageous in a number of application areas-including maximum likelihood estimation, sensitivity analysis, and MAP computations-and we provide specific empirical results in the domain of genetic linkage analysis. We also show that the approach is applicable for networks that do not contain determinism, and show that it empirically subsumes the performance of the quickscore algorithm when applied to noisy-or networks.
- Publication:
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arXiv e-prints
- Pub Date:
- July 2012
- DOI:
- 10.48550/arXiv.1207.1372
- arXiv:
- arXiv:1207.1372
- Bibcode:
- 2012arXiv1207.1372C
- Keywords:
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- Computer Science - Artificial Intelligence
- E-Print:
- Appears in Proceedings of the Twenty-First Conference on Uncertainty in Artificial Intelligence (UAI2005)