1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Breaking the Quality-Privacy Tradeoff in Tabular Data Generation via In-Context Learning
Xinyan Han, Yan Lu, Xiaoyu Lin +5
Tabular data synthesis aims to generate high-quality data while preserving privacy. However, we find that existing tabular generative models exhibit a clear tradeoff in the small-d…
cs.LG2021
A Unified and Fast Interpretable Model for Predictive Analytics
Yuanyuan Jiang, Rui Ding, Tianchi Qiao +3
Predictive analytics aims to build machine learning models to predict behavior patterns and use predictions to guide decision-making. Predictive analytics is human involved, thus t…
cs.LG2021★ 1 cited
ML4C: Seeing Causality Through Latent Vicinity
Haoyue Dai, Rui Ding, Yuanyuan Jiang +2
Supervised Causal Learning (SCL) aims to learn causal relations from observational data by accessing previously seen datasets associated with ground truth causal relations. This pa…