Preventing Unnecessary Groundings in the Lifted Dynamic Junction Tree Algorithm
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The lifted dynamic junction tree algorithm (LDJT) answers filtering and prediction queries efficiently for probabilistic relational temporal models by building and then reusing a first-order cluster representation of a knowledge base for multiple queries and time steps. Unfortunately, a non-ideal elimination order can lead to groundings. We extend LDJT (i) to identify unnecessary groundings and (ii) to prevent groundings by delaying eliminations through changes in a temporal first-order cluster representation. The extended version of LDJT answers multiple temporal queries orders of magnitude faster than the original version.
- 3.Taghipour, N.: Lifted probabilistic inference by variable elimination. Ph.D. thesis, KU Leuven (2013)Google Scholar