Causal machine learning

Policy Learning with Abstention
We study policy learning with the ability to abstain, and demonstrate its usefulness in ensuring safety.
Ayush Sawarni, Jikai Jin, Justin Whitehouse, Vasilis Syrgkanis
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Learning Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity
We study the best-achievable identification guarantees and provable identification algorithms for causal representation learning when hard interventions are not available.
Jikai Jin, Vasilis Syrgkanis
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