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A Statistical Perspective on Discovering Functional Dependencies in Noisy Data

Summary: FD discovery under noise as structure learning on binary variables; variables are data functions. FDX: sparse-regression framework turning FD discovery into regression; robust to noise/missing data, scalable to large datasets with ~2x F1 gains. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5964
Venue
SIGMOD
Year
2020
Pagerank
6.4310458e-05
Overall Rank
4,127 | 71.30%
DOI
10.1145/3318464.3389749

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