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)
Incoming Non-self Citations Over Time
Authors
- 1. Yunjia Zhang
- 2. Zhihan Guo
- 3. Theodoros Rekatsinas
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