Explaining Inference Queries with Bayesian Optimization

@article{Lockhart2021ExplainingIQ,
  title={Explaining Inference Queries with Bayesian Optimization},
  author={Brandon Lockhart and Jinglin Peng and Weiyuan Wu and Jiannan Wang and Eugene Wu},
  journal={Proc. VLDB Endow.},
  year={2021},
  volume={14},
  pages={2576-2585}
}
Obtaining an explanation for an SQL query result can enrich the analysis experience, reveal data errors, and provide deeper insight into the data. Inference query explanation seeks to explain unexpected aggregate query results on inference data; such queries are challenging to explain because an explanation may need to be derived from the source, training, or inference data in an ML pipeline. In this paper, we model an objective function as a black-box function and propose BOExplain, a novel… 

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