Name
Title | ||
|---|---|---|
Probabilistic Graphical Models Specified by Probabilistic Logic Programs: Semantics and Complexity. |
Abstract | ||
|---|---|---|
We look at probabilistic logic programs as a specification language for probabilistic models, and study their interpretation and complexity. Acyclic programs specify Bayesian networks, and, depending on constraints on logical atoms, their inferential complexity reaches complexity classes #P, #NP, and even #EXP. We also investigate (cyclic) stratified probabilistic logic programs, showing that they have the same complexity as acyclic probabilistic logic programs, and that they can be depicted using chain graphs. |
Year | Venue | Field |
|---|---|---|
2016 | Probabilistic Graphical Models | Complexity class,Probabilistic logic network,Computer science,Probabilistic CTL,Probabilistic analysis of algorithms,Theoretical computer science,Descriptive complexity theory,Artificial intelligence,Probabilistic logic,Probabilistic argumentation,Graphical model,Machine learning |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
16 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fábio Cozman | 1 | 18 | 10.16 |
| Denis Deratani Mauá | 2 | 165 | 24.64 |