Well File:
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- Wellbore Schematic ( results)
- Directional Survey ( results)
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- Density ( results)
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Jayadev Acharya
Learning and Testing Causal Models with Interventions
Jayadev Acharya, Arnab Bhattacharyya, Constantinos Daskalakis, Saravanan Kandasamy
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) interventions on an unknown causal Bayesian network X on the same graph, and O(n/ɛ
Learning and Testing Causal Models with Interventions
Jayadev Acharya, Arnab Bhattacharyya, Constantinos Daskalakis, Saravanan Kandasamy
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) interventions on an unknown causal Bayesian network X on the same graph, and O(n/ɛ