Statistical relational learning

April 26, 2020 — November 22, 2022

causality
networks
statistics
stringology

Suspiciously similar content

Figure 1

Placeholder.

I cannot help but notice that the discussions of changing probabilistic domain, and unusual assumptions about exchangeability and projectivity are reminiscent of inference on social graphs. Connections?

See the big book of SRL.

1 Lifted inference

2 References

Braz, Amir, and Roth. 2008. “A Survey of First-Order Probabilistic Models.” In Innovations in Bayesian Networks.
Crane, and Dempsey. 2019. “Relational Exchangeability.” Journal of Applied Probability.
De Raedt, Kersting, Natarajan, et al. 2016. Statistical relational artificial intelligence: logic, probability, and computation. Synthesis lectures on artificial intelligence and machine learning #32.
Dehbi, Hadiji, Gröger, et al. 2017. “Statistical Relational Learning of Grammar Rules for 3D Building Reconstruction.” Transactions in GIS.
Getoor, Friedman, Koller, et al. 2001. “Learning Probabilistic Relational Models.” In Relational Data Mining.
Getoor, and Taskar, eds. 2007. Introduction to Statistical Relational Learning. Adaptive Computation and Machine Learning.
Jaeger, and Schulte. 2021. “A Complete Characterization of Projectivity for Statistical Relational Models.” In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence. IJCAI’20.
Jha, Gogate, Meliou, et al. 2010. “Lifted Inference Seen from the Other Side : The Tractable Features.” In Advances in Neural Information Processing Systems.
Khosravi, and Bina. 2010. “A Survey on Statistical Relational Learning.” In Advances in Artificial Intelligence.
Raedt, and Kersting. 2010. “Statistical Relational Learning.” In Encyclopedia of Machine Learning.
Riguzzi, Bellodi, Zese, et al. 2017. “A Survey of Lifted Inference Approaches for Probabilistic Logic Programming Under the Distribution Semantics.” International Journal of Approximate Reasoning.
van den Broeck, Kersting, Natarajan, et al., eds. 2021. An Introduction to Lifted Probabilistic Inference.
van den Broeck, and Niepert. 2014. “Lifted Probabilistic Inference for Asymmetric Graphical Models.”
Weitkämper. 2023. “Projectivity Revisited.” International Journal of Approximate Reasoning.