3 papers
cs.LG2025
Dependency-aware synthetic tabular data generation
Chaithra Umesh, Kristian Schultz, Manjunath Mahendra +2
Synthetic tabular data is increasingly used in privacy-sensitive domains such as health care, but existing generative models often fail to preserve inter-attribute relationships. I…
cs.LG2025
Convex space learning for tabular synthetic data generation
Manjunath Mahendra, Chaithra Umesh, Saptarshi Bej +2
Generating synthetic samples from the convex space of the minority class is a popular oversampling approach for imbalanced classification problems. Recently, deep-learning approach…
cs.LG2024
Preserving logical and functional dependencies in synthetic tabular data
Chaithra Umesh, Kristian Schultz, Manjunath Mahendra +2
Dependencies among attributes are a common aspect of tabular data. However, whether existing tabular data generation algorithms preserve these dependencies while generating synthet…