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Zhu, Yujin (author)
Tabular data synthesis is a promising approach to circumvent strict regulations on data privacy. Although the state-of-the-art tabular data synthesizers, e.g., table-GAN, CTGAN, TVAE, and CTAB-GAN, are effective at generating synthetic tabular data, they are sensitive to column permutations of input data. In this work, we conduct an impact and...
master thesis 2022