Lifted probabilistic relational inference for uncertain networks
作者： Wen Pu
DOI:
关键词: Probabilistic logic 、 Exponential random graph models 、 Markov logic network 、 Inference 、 Computer science 、 Probabilistic logic network 、 Artificial intelligence
摘要:
参考文章(64)
Tom A. B. Snijders, Markov chain Monte Carlo estimation of exponential random graph models Journal of Social Structure. ,vol. 2, ,(2002)
S. L. Lauritzen, D. J. Spiegelhalter, Local computations with probabilities on graphical structures and their application to expert systems Journal of the royal statistical society series b-methodological. ,vol. 50, pp. 415- 448 ,(1990) , 10.1111/J.2517-6161.1988.TB01721.X
Mathias Niepert, Markov Chains on Orbits of Permutation Groups arXiv: Artificial Intelligence. ,(2012)
Babak Ahmadi, Sriraam Natarajan, Kristian Kersting, Counting belief propagation uncertainty in artificial intelligence. pp. 277- 284 ,(2009)
Lise Getoor, Amol Deshpande, Prithviraj Sen, Bisimulation-based approximate lifted inference uncertainty in artificial intelligence. pp. 496- 505 ,(2009)
Dan Roth, On the hardness of approximate reasoning Artificial Intelligence. ,vol. 82, pp. 273- 302 ,(1996) , 10.1016/0004-3702(94)00092-1
Eyal Amir, Approximation Algorithms for Treewidth Algorithmica. ,vol. 56, pp. 448- 479 ,(2010) , 10.1007/S00453-008-9180-4
David R. Hunter, Pavel N. Krivitsky, Michael Schweinberger, Computational Statistical Methods for Social Network Models Journal of Computational and Graphical Statistics. ,vol. 21, pp. 856- 882 ,(2012) , 10.1080/10618600.2012.732921
Matthew Richardson, Pedro Domingos, Markov logic networks Machine Learning. ,vol. 62, pp. 107- 136 ,(2006) , 10.1007/S10994-006-5833-1
Gregory F. Cooper, The computational complexity of probabilistic inference using bayesian belief networks Artificial Intelligence. ,vol. 42, pp. 393- 405 ,(1990) , 10.1016/0004-3702(90)90060-D