1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Benign Overfitting in Out-of-Distribution Generalization of Linear Models
Shange Tang, Jiayun Wu, Jianqing Fan +1
Benign overfitting refers to the phenomenon where an over-parameterized model fits the training data perfectly, including noise in the data, but still generalizes well to the unsee…
stat.ME2024
Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift
Jiawei Ge, Debarghya Mukherjee, Jianqing Fan
As machine learning models are increasingly deployed in dynamic environments, it becomes paramount to assess and quantify uncertainties associated with distribution shifts. A distr…
stat.ML2023★ 1 cited
Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift
Jiawei Ge, Shange Tang, Jianqing Fan +2
A key challenge of modern machine learning systems is to achieve Out-of-Distribution (OOD) generalization -- generalizing to target data whose distribution differs from that of sou…