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- research-articleMarch 2024
Controllable Tabular Data Synthesis Using Diffusion Models
Proceedings of the ACM on Management of Data (PACMMOD), Volume 2, Issue 1Article No.: 28, Pages 1–29https://doi.org/10.1145/3639283Controllable tabular data synthesis plays a crucial role in numerous applications by allowing users to generate synthetic data with specific conditions. These conditions can include synthesizing tuples with predefined attribute values or creating tuples ...
- short-paperOctober 2022
An Empirical Study on the Membership Inference Attack against Tabular Data Synthesis Models
CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge ManagementOctober 2022, Pages 4064–4068https://doi.org/10.1145/3511808.3557546Tabular data typically contains private and important information; thus, precautions must be taken before they are shared with others. Although several methods (e.g., differential privacy and k-anonymity) have been proposed to prevent information ...
- research-articleAugust 2022
SOS: Score-based Oversampling for Tabular Data
KDD '22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2022, Pages 762–772https://doi.org/10.1145/3534678.3539454Score-based generative models (SGMs) are a recent breakthrough in generating fake images. SGMs are known to surpass other generative models, e.g., generative adversarial networks (GANs) and variational autoencoders (VAEs). Being inspired by their big ...