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cs.DB2021★ 21 cited
Accelerating Approximate Aggregation Queries with Expensive Predicates
Daniel Kang, John Guibas, Peter Bailis +3
Researchers and industry analysts are increasingly interested in computing aggregation queries over large, unstructured datasets with selective predicates that are computed using e…
math.ST2021
Proof: Accelerating Approximate Aggregation Queries with Expensive Predicates
Daniel Kang, John Guibas, Peter Bailis +3
Given a dataset , we are interested in computing the mean of a subset of which matches a predicate. ABae leverages stratified sampling and proxy models t…