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Many queries require statistical guarantees on accuracy
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Efficient Query Processing for Unstructured Data Using Machine Learning
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- 1 Intro
- 2 Unstructured data is ubiquitous and cheap
- 3 ML models can perform well on a range of benchmark tasks
- 4 My work: how can we use unreliable and expensive ML models in query processing?
- 5 Two key ideas: sampling and proxy scores
- 6 Many queries require statistical guarantees on accuracy
- 7 Prior work using proxies fail to achieve statistical guarantees on failure probability!
- 8 Example query: finding hummingbirds with high recall
- 9 Query type two: aggregation Query: "what is the average number of cars per frame?"
