Inside-Outside Probability Computation for Belief Propagation
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 2605-2609.
Abstract
In this paper we prove that the well-known correspondence between the forward-backward algorithm for hidden Markov models (HMMs) and belief propagation (BP) applied to HMMs can be generalized to one between BP for junction trees and the generalized inside-outside probability computation for probabilistic logic programs applied to junction trees.
Taisuke Sato. 2007. Inside-Outside Probability Computation for Belief Propagation. In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07. IJCAI, 2605–2609. https://ijcai.org/proceedings/2007/419
Sato, T. (2007). Inside-Outside Probability Computation for Belief Propagation. In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 (pp. 2605–2609). IJCAI. https://ijcai.org/proceedings/2007/419
@inproceedings{ijcai2007p419,
title = {Inside-Outside Probability Computation for Belief Propagation},
author = {Sato, Taisuke},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {2605--2609},
year = {2007},
url = {https://ijcai.org/proceedings/2007/419},
}
TY - CPAPER TI - Inside-Outside Probability Computation for Belief Propagation AU - Sato, Taisuke T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 2605 EP - 2609 UR - https://ijcai.org/proceedings/2007/419 ER -Copied
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