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Poster
Cost-effectively Identifying Causal Effects When Only Response Variable is Observable
Tian-Zuo Wang · Xi-Zhu Wu · Sheng-Jun Huang · Zhi-Hua Zhou

Thu Jul 16 05:00 PM -- 05:45 PM & Fri Jul 17 04:00 AM -- 04:45 AM (PDT) @
in Poster Session 49 »

In many real tasks, we care about how to make decisions rather than mere predictions on an event, e.g. how to increase the revenue next month instead of merely knowing it will drop. The key is to identify the causal effects on the desired event. It is achievable with do-calculus if the causal structure is known; however, in many real tasks it is not easy to infer the whole causal structure with the observational data. Introducing external interventions is needed to achieve it. In this paper, we study the situation where only the response variable is observable under intervention. We propose a novel approach which is able to cost-effectively identify the causal effects, by an active strategy introducing limited interventions, and thus guide decision-making. Theoretical analysis and empirical studies validate the effectiveness of the proposed approach.

Keywords: Causality

Author Information

Tian-Zuo Wang (Nanjing University)
Xi-Zhu Wu (Nanjing University)
Sheng-Jun Huang (Nanjing University of Aeronautics and Astronautics)
Zhi-Hua Zhou (Nanjing University)

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