Ultra-scalable and efficient methods for hybrid observational and experimental local causal pathway discovery

JOURNAL OF MACHINE LEARNING RESEARCH, pp. 3219.0-3267.0, 2015.

Cited by: 14|Views42
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Abstract:

Discovery of causal relations from data is a fundamental objective of several scientific disciplines. Most causal discovery algorithms that use observational data can infer causality only up to a statistical equivalency class, thus leaving many causal relations undetermined. In general, complete identification of causal relations requires...More

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