Exploiting symmetries for scaling loopy belief propagation and relational training

Author:

Ahmadi Babak,Kersting Kristian,Mladenov Martin,Natarajan Sriraam

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference92 articles.

1. Acar, U., Ihler, A., Mettu, R., & Sumer, O. (2008). Adaptive inference on general graphical models. In UAI-08, Corvallis, Oregon: AUAI Press.

2. Ahmadi, B., Kersting, K., & Sanner, S. (2011). Multi-evidence lifted message passing, with application to pagerank and the Kalman filter. In IJCAI.

3. Ahmadi, B., Kersting, K., & Natarajan, S. (2012). Lifted online training of relational models with stochastic gradient methods. In Proceedings ECML-PKDD, Bristol, UK, September 24–28. Berlin: Springer.

4. Amari, S. (1998). Natural gradient works efficiently in learning. Neural Computation, 10, 251–276.

5. Besag, J. (1975). Statistical analysis of non-lattice data. Journal of the Royal Statistical Society. Series D. The Statistician, 24(3), 179–195.

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