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Learning Functional Dependencies with Sparse Regression
We show that discovering FDs from a noisy dataset is equivalent to learning the structure of a graphical model over binary random variables, where each random variable corresponds to a functional of the dataset attributes.
Unsupervised Functional Dependency Discovery for Data Preparation
We study the problem of functional dependency (FD) discovery to impose domain knowledge for downstream data preparation tasks.
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