Name
Title | ||
|---|---|---|
Inference with Aggregation Parfactors: Lifted Elimination with First-Order d-Separation. |
Abstract | ||
|---|---|---|
In this paper we focus on lifted inference for statistical relational models; that is, inference that avoids complete grounding, in models that combine logical and probabilistic assertions. We focus on relational Bayesian networks that can be represented through parfactors and aggregation parfactors. We present a new elimination rule for lifted variable elimination, and show how to use first-order d-separation to extend the reach of existing elimination rules. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/BRACIS.2014.75 | BRACIS |
Keywords | Field | DocType |
bayesian networks | Variable elimination,Frequentist inference,Bayesian inference,Inference,Fiducial inference,Probabilistic logic network,Theoretical computer science,Predictive inference,Artificial intelligence,Statistical inference,Machine learning,Mathematics | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Felipe Iwao Takiyama | 1 | 0 | 0.34 |
| Fábio Cozman | 2 | 18 | 10.16 |