Learning and testing causal models with interventions

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)...

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Bibliographic Details
Main Authors: Acharya, J, Bhattacharyya, A, Daskalakis, C, Kandasamy, S
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:English
Published: 2022
Online Access:https://hdl.handle.net/1721.1/143123

Internet

https://hdl.handle.net/1721.1/143123

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