no code implementations • 4 May 2019 • Zhihan Guo, Theodoros Rekatsinas
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.
no code implementations • ICLR Workshop LLD 2019 • Zhihan Guo, Theodoros Rekatsinas
We study the problem of functional dependency (FD) discovery to impose domain knowledge for downstream data preparation tasks.