3 papers
math.ST2026
Early-stopped aggregation: Adaptive inference with computational efficiency
Ilsang Ohn, Shitao Fan, Jungbin Jun +1
When considering a model selection or, more generally, an aggregation approach for adaptive statistical inference, it is often necessary to compute estimators over a wide range of…
math.ST2025
Variational bagging: a robust approach for Bayesian uncertainty quantification
Shitao Fan, Ilsang Ohn, David Dunson +1
Variational Bayes methods are popular due to their computational efficiency and adaptability to diverse applications. In specifying the variational family, mean-field classes are c…
stat.ML2025
Robust and Scalable Variational Bayes
Carlos Misael Madrid Padilla, Shitao Fan, Lizhen Lin
We propose a robust and scalable framework for variational Bayes (VB) that effectively handles outliers and contamination of arbitrary nature in large datasets. Our approach divide…