Learning directed acyclic graph models based on sparsest permutations
We consider the problem of learning a Bayesian network or directed acyclic graph model from observational data. A number of constraint-based, score-based and hybrid algorithms have been developed for this purpose. Statistical consistency guarantees of these algorithms rely on the faithfulness assump...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021
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| Online Access: | https://hdl.handle.net/1721.1/130118 |