3 citations · 3 across the 5 of their papers we have counts for
5 papers
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…
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…
Efficient Estimation for Functional Accelerated Failure Time Model
Changyu Liu, Wen Su, Kin-Yat Liu +2
We propose a functional accelerated failure time model to characterize effects of both functional and scalar covariates on the time to event of interest, and provide regularity con…
Non-Asymptotic Bounds for Adversarial Excess Risk under Misspecified Models
Changyu Liu, Yuling Jiao, Junhui Wang +1
We propose a general approach to evaluating the performance of robust estimators based on adversarial losses under misspecified models. We first show that adversarial risk is equiv…
Deep Generative Survival Analysis: Nonparametric Estimation of Conditional Survival Function
Xingyu Zhou, Wen Su, Changyu Liu +3
We propose a deep generative approach to nonparametric estimation of conditional survival and hazard functions with right-censored data. The key idea of the proposed method is to f…