Learning and testing causal models with interventions
© 2018 Curran Associates Inc.All rights reserved. We consider testing and learning problems on causal Bayesian networks as defined by Pearl [Pea09]. Given a causal Bayesian network M on a graph with n discrete variables and bounded in-degree and bounded “confounded components”, we show that O(log n)...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2022
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| Online Access: | https://hdl.handle.net/1721.1/143123 |