A note on efficient minimum cost adjustment sets in causal graphical models.
Ezequiel SmuclerAndrea RotnitzkyPublished in: CoRR (2022)
Keyphrases
- graphical models
- minimum cost
- bayesian networks
- belief propagation
- probabilistic model
- probabilistic inference
- probabilistic graphical models
- random variables
- np hard
- approximate inference
- conditional independence
- network flow
- structure learning
- approximation algorithms
- belief networks
- factor graphs
- spanning tree
- conditional random fields
- network flow problem
- markov networks
- models with hidden variables
- statistical relational learning
- loopy belief propagation
- graph structure
- linear programming
- possibilistic networks
- relational databases