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
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…
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…