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Recursive conditioning

Artificial Intelligence 126 (1-2):5-41 (2001)

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  1. Decomposition and tractability in qualitative spatial and temporal reasoning.Jinbo Huang, Jason Jingshi Li & Jochen Renz - 2013 - Artificial Intelligence 195 (C):140-164.
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  • Memory intensive AND/OR search for combinatorial optimization in graphical models.Radu Marinescu & Rina Dechter - 2009 - Artificial Intelligence 173 (16-17):1492-1524.
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  • Importance sampling-based estimation over AND/OR search spaces for graphical models.Vibhav Gogate & Rina Dechter - 2012 - Artificial Intelligence 184-185 (C):38-77.
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  • AND/OR search spaces for graphical models.Rina Dechter & Robert Mateescu - 2007 - Artificial Intelligence 171 (2-3):73-106.
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  • Learning tractable Bayesian networks in the space of elimination orders.Marco Benjumeda, Concha Bielza & Pedro Larrañaga - 2019 - Artificial Intelligence 274 (C):66-90.
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  • A new probabilistic constraint logic programming language based on a generalised distribution semantics.Steffen Michels, Arjen Hommersom, Peter J. F. Lucas & Marina Velikova - 2015 - Artificial Intelligence 228 (C):1-44.
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  • Solving infinite-domain CSPs using the patchwork property.Konrad K. Dabrowski, Peter Jonsson, Sebastian Ordyniak & George Osipov - 2023 - Artificial Intelligence 317 (C):103880.
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  • AND/OR Branch-and-Bound search for combinatorial optimization in graphical models.Radu Marinescu & Rina Dechter - 2009 - Artificial Intelligence 173 (16-17):1457-1491.
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  • On probabilistic inference by weighted model counting.Mark Chavira & Adnan Darwiche - 2008 - Artificial Intelligence 172 (6-7):772-799.
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  • Algorithms and complexity results for persuasive argumentation.Eun Jung Kim, Sebastian Ordyniak & Stefan Szeider - 2011 - Artificial Intelligence 175 (9-10):1722-1736.
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  • Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering.Ole J. Mengshoel, David C. Wilkins & Dan Roth - 2006 - Artificial Intelligence 170 (16-17):1137-1174.
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