Focused Context Balancing for Robust Offline Policy Evaluation
| Autor: | Peng Cui, Hao Zou, Peixuan Chen, Kun Kuang, Boqi Chen |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry Estimator Context (language use) Sample (statistics) 02 engineering and technology Machine learning computer.software_genre Ranking 020204 information systems Propensity score matching 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business computer |
| Zdroj: | KDD |
| DOI: | 10.1145/3292500.3330852 |
| Popis: | Precisely evaluating the effect of new policies (e.g. ad-placement models, recommendation functions, ranking functions) is one of the most important problems for improving interactive systems. The conventional policy evaluation methods rely on online A/B tests, but they are usually extremely expensive and may have undesirable impacts. Recently, Inverse Propensity Score (IPS) estimators are proposed as alternatives to evaluate the effect of new policy with offline logged data that was collected from a different policy in the past. They tend to remove the distribution shift induced by past policy. However, they ignore the distribution shift that would be induced by the new policy, which results in imprecise evaluation. Moreover, their performances rely on accurate estimation of propensity score, which can not be guaranteed or validated in practice. In this paper, we propose a non-parametric method, named Focused Context Balancing (FCB) algorithm, to learn sample weights for context balancing, so that the distribution shift induced by the past policy and new policy can be eliminated respectively. To validate the effectiveness of our FCB algorithm, we conduct extensive experiments on both synthetic and real world datasets. The experimental results clearly demonstrate that our FCB algorithm outperforms existing estimators by achieving more precise and robust results for offline policy evaluation. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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