Markov Logic Learning Algorithm: Difference between revisions
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A [[Markov Logic Learning Algorithm]] is an [[Learning Algorithm]] for a [[Markov Logic Network]]. | A [[Markov Logic Learning Algorithm]] is an [[Learning Algorithm]] for a [[Markov Logic Network]]. | ||
* <B>AKA:</B> [[Markov Logic Learning]]. | * <B>AKA:</B> [[Markov Logic Learning Algorithm|Markov Logic Learning]]. | ||
* <B>See</U>:</B> [[Markov Logic Inference Algorithm]], [[Markov Logic System]], [[Conditional Likelihood Estimation]], [[Convex Optimization Algorithm]], [[Inductive Logic Programming Algorithm]]. | * <B>See</U>:</B> [[Markov Logic Inference Algorithm]], [[Markov Logic System]], [[Conditional Likelihood Estimation]], [[Convex Optimization Algorithm]], [[Inductive Logic Programming Algorithm]]. | ||
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Revision as of 20:17, 23 December 2019
A Markov Logic Learning Algorithm is an Learning Algorithm for a Markov Logic Network.
- AKA: Markov Logic Learning.
- See: Markov Logic Inference Algorithm, Markov Logic System, Conditional Likelihood Estimation, Convex Optimization Algorithm, Inductive Logic Programming Algorithm.
References
2009
- (Domingos & Lowd, 2009) ⇒ Pedro Domingos, and Daniel Lowd. (2009). “Markov Logic: An Interface Layer for Artificial Intelligence." Morgan & Claypool. doi:10.2200/S00206ED1V01Y200907AIM007
- Learning algorithms make use of conditional likelihood, convex optimization, and inductive logic programming ...