3 papers
stat.ML2026
Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations
Changyu Liu, Yuling Jiao, Jian Huang
Conditional generative modeling remains a challenging problem in semi-supervised settings where labeled data is scarce but unlabeled samples are abundant. To effectively leverage s…
stat.ML2025
Boosting Statistic Learning with Synthetic Data from Pretrained Large Models
Jialong Jiang, Wenkang Hu, Jian Huang +2
The rapid advancement of generative models, such as Stable Diffusion, raises a key question: how can synthetic data from these models enhance predictive modeling? While they can ge…
stat.ML2025
Wasserstein Distributionally Robust Nonparametric Regression
Changyu Liu, Yuling Jiao, Junhui Wang +1
Wasserstein distributionally robust optimization (WDRO) strengthens statistical learning under model uncertainty by minimizing the local worst-case risk within a prescribed ambigui…