Towards High-Level Probabilistic Reasoning with Lifted Inference (bibtex)
by Guy Van den Broeck
Abstract:
High-level representations of uncertainty, such as probabilistic logics and programs, have been around for decades. Lifted inference was initially motivated by the need to make reasoning algorithms high-level as well. While the lifted inference community focused on machine learning applications, the high-level reasoning goal has received less attention recently. We revisit the idea and look at the capabilities of the latest techniques in lifted inference. This lets us conclude that lifted inference is strictly more powerful than propositional inference on high-level reasoning tasks.
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Reference:
Guy Van den Broeck. Towards High-Level Probabilistic Reasoning with Lifted Inference, In Proceedings of the AAAI Spring Symposium on KRR, 2015.
Bibtex Entry:
@inproceedings{VdBKRR15,
author = {Van den Broeck, Guy},
title = {Towards High-Level Probabilistic Reasoning with Lifted Inference},
booktitle = {Proceedings of the AAAI Spring Symposium on KRR},
year = {2015},
url = {http://starai.cs.ucla.edu/papers/VdBKRR15.pdf},
keywords = {workshop}
}PDF Preview:
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