collaborators

7 papers

stat.ME2026

Enhanced localized conformal prediction with imperfect auxiliary information

Yinjie Min, Liuhua Peng, Changliang Zou

There is growing interest in constructing conformal prediction sets that provide approximate or asymptotic conditional coverage guarantees, capturing local data heterogeneity. Howe…

stat.ME2026

Efficient Federated Estimation and Inference for High-Dimensional Tail Index Regression

Haoyu Geng, Liuhua Peng, Changliang Zou +1

Tail index regression studies how covariates affect tail heaviness in heavy-tailed data. In many applications, data are distributed across heterogeneous sources, where direct pooli…

stat.ME2026

A Unified Theory of Conditional Coverage in Conformal Prediction with Applications

Yinjie Min, Liuhua Peng, Changliang Zou

Conformal prediction provides prediction sets with finite-sample marginal coverage, but many applications require coverage guarantees that adapt to individual test points, a subpop…

stat.ML2026

Learning U-Statistics with Active Inference

Xiaoning Wang, Yuyang Huo, Liuhua Peng +1

-statistics play a central role in statistical inference. In many modern applications, however, acquiring the labels required for -statistics is costly. Motivated by recent a…

stat.ME2026

Generalized Boundary FDR Control under Arbitrary Dependence: An Approach on Closure Principle

Yifan Zhang, Wentao Zhang, Changliang Zou +1

False discovery rate (FDR) is a cornerstone of modern multiple testing. However, it often fails to guarantee the reliability of "marginal" discoveries that lie at the boundary of t…

stat.ME2026

Stable Localized Conformal Prediction via Transduction

Yinjie Min, Liuhua Peng, Changliang Zou

Existing evaluations of conformal prediction, such as prediction efficiency and test-conditional coverage, are defined in expectation over the calibration data. In practice, when o…