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20172026
most citedStructure-Adaptive Sequential Testing for Online False Discovery Rate Control

4 citations · 4 across the 8 of their papers we have counts for

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9 papers · 1 filter

stat.ME2026

COINS: Any-Stage-Valid and Utility-Oriented Sequential Conformal Prediction

Wangcheng Li, Nan Qiao, Xu Guo +1

Many predictive workflows update uncertainty as information is acquired and use intermediate reports to determine whether to stop or deploy further resources. We study conformal in…

stat.ME2026

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…

stat.ME2023

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…

stat.ME2023

Ranking and Selection in Large-Scale Inference of Heteroscedastic Units

Bowen Gang, Luella Fu, Gareth James +1

The allocation of limited resources to a large number of potential candidates presents a pervasive challenge. In the context of ranking and selecting top candidates from heterosced…

stat.ME2022

A Locally Adaptive Shrinkage Approach to False Selection Rate Control in High-Dimensional Classification

Bowen Gang, Yuantao Shi, Wenguang Sun

The uncertainty quantification and error control of classifiers are crucial in many high-consequence decision-making scenarios. We propose a selective classification framework that…

stat.ME2020

Large-Scale Shrinkage Estimation under Markovian Dependence

Bowen Gang, Gourab Mukherjee, Wenguang Sun

We consider the problem of simultaneous estimation of a sequence of dependent parameters that are generated from a hidden Markov model. Based on observing a noise contaminated vect…