collaborators

10 papers

stat.ML2026

Minimum Volume Optimal Transport for Multivariate Conformal Prediction

Chuchen Zhang, Haojie Ren, Zhaojun Wang +2

Optimal transport (OT) enables multivariate conformal prediction (CP) to construct flexible prediction sets that reflect the underlying complex distributional geometry while retain…

stat.ME2026

Conformalized Safe Feasible Sets in Uncertain Decision Systems

Yajie Bao, Yinjie Min, Haojie Ren +1

Safety-critical decision systems often require a downstream optimizer to choose from an unknown feasible set determined by an unobserved label . Given a context , the goal is…

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

Shape-Adaptive Conditional Calibration for Conformal Prediction via Minimax Optimization

Yajie Bao, Chuchen Zhang, Zhaojun Wang +2

Achieving valid conditional coverage in conformal prediction is challenging due to the theoretical difficulty of satisfying pointwise constraints in finite samples. Building upon t…

stat.ME2025

Aggregating Conformal Prediction Sets via α-Allocation

Congbin Xu, Yue Yu, Haojie Ren +2

Conformal prediction offers a distribution-free framework for constructing prediction sets with finite-sample coverage. Yet, efficiently leveraging multiple conformity scores to re…

stat.ME2025

Feedback-Enhanced Online Multiple Testing with Applications to Conformal Selection

Lin Lu, Yuyang Huo, Haojie Ren +2

This work studies online multiple testing with feedback, where decisions are made sequentially, and the true state of the hypothesis is revealed after decisions are made, either in…

stat.ME2025

Unified Conformalized Multiple Testing with Full Data Efficiency

Yuyang Huo, Xiaoyang Wu, Changliang Zou +1

Conformalized multiple testing offers a model-free way to control predictive uncertainty in decision-making. Existing methods typically use only part of the available data to build…

stat.ML2025

Optimal Model Selection for Conformalized Robust Optimization

Yajie Bao, Yang Hu, Haojie Ren +2

In decision-making under uncertainty, Contextual Robust Optimization (CRO) provides reliability by minimizing the worst-case decision loss over a prediction set. While recent advan…

stat.ME2025

e-GAI: e-value-based Generalized -Investing for Online False Discovery Rate Control

Yifan Zhang, Zijian Wei, Haojie Ren +1

Online multiple hypothesis testing has attracted a lot of attention in many applications, e.g., anomaly status detection and stock market price monitoring. The state-of-the-art gen…

stat.ML2025

Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach

Qian Peng, Yajie Bao, Haojie Ren +2

Conformal prediction is a powerful tool for constructing prediction intervals for black-box models, providing a finite sample coverage guarantee for exchangeable data. However, thi…