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Conformance Constraint Discovery: Measuring Trust in Data-Driven Systems

Summary: Conformance constraints: a data-profiling primitive to quantify non-conformance between serving data and training assumptions. Low-variance projections yield strong constraints; linear-in-data, cubic-in-attributes discovery with a quantitative non-conformance score supports trusted ML and drift detection. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6077
Venue
SIGMOD
Year
2021
Pagerank
4.6931274e-05
Overall Rank
7,607 | 47.14%
DOI
10.1145/3448016.3452795

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