Counterfactual Reasoning and Learning Systems
2012
This work shows how to leverage causal inference to understand the behavior of complex learning systems interacting with their environment and predict the consequences of changes to the system. Such predictions allow both humans and algorithms to select the changes that would have improved the system performance. This work is illustrated by experiments carried out on the ad placement system associated with the Bing search engine.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
69
References
17
Citations
NaN
KQI