6 papers
Conformalized Large-Scale Selective Inference with Informative and Trustworthy Prediction Sets
Wangcheng Li, Guanlan Zhao, Xu Guo +1
In large-scale prediction problems, exhaustively following up on all test units is often impractical and inefficient, motivating a selective reporting strategy that fulfills the du…
Structure-Adaptive Conformal Inference for Large-Scale Out-of-Distribution Testing
Rongyi Sun, Wenguang Sun, Zinan Zhao
This paper addresses structured out-of-distribution (OOD) testing in high-stakes machine learning applications. Traditional conformal methods rely on joint exchangeability, making…
Nonparametric Empirical Bayes Estimation on Heterogeneous Data
Trambak Banerjee, Luella J. Fu, Gareth M. James +2
The simultaneous estimation of many parameters based on data collected from corresponding studies is a key research problem that has received renewed attention in the high-dimensio…
A Burden Shared is a Burden Halved: A Fairness-Adjusted Approach to Classification
Bradley Rava, Wenguang Sun, Gareth M. James +1
We investigate the fairness issue in classification, where automated decisions are made for individuals from different protected groups. In high-consequence scenarios, decision err…
Empirical Bayes Estimation with Side Information: A Nonparametric Integrative Tweedie Approach
Jiajun Luo, Trambak Banerjee, Gourab Mukherjee +1
We investigate the problem of compound estimation of normal means while accounting for the presence of side information. Leveraging the empirical Bayes framework, we develop a nonp…
A Locally Adaptive Algorithm for Multiple Testing with Network Structure
Ziyi Liang, T. Tony Cai, Wenguang Sun +1
Incorporating auxiliary information alongside primary data can significantly enhance the accuracy of simultaneous inference. However, existing multiple testing methods face challen…