3 papers
math.ST2026
Adaptive Confidence Intervals in Efron's Gaussian Two-Groups Model
Qiaosen Wang, Shuwen Chai, Chao Gao
Robust uncertainty quantification is increasingly important in modern data analysis and is often formalized under Huber's model, which allows an -fraction of arbitrary…
math.ST2025
Confidence Intervals for Linear Models with Arbitrary Noise Contamination
Dong Xie, Chao Gao, John Lafferty
We study confidence interval construction for linear regression under Huber's contamination model, where an unknown fraction of noise variables is arbitrarily corrupted. While robu…
cs.DS2025
Information-Computation Tradeoffs for Noiseless Linear Regression with Oblivious Contamination
Ilias Diakonikolas, Chao Gao, Daniel M. Kane +2
We study the task of noiseless linear regression under Gaussian covariates in the presence of additive oblivious contamination. Specifically, we are given i.i.d.\ samples from a di…