activity
20232026
collaborators

6 papers

stat.ME2026

Beyond Prediction: Conformal Inference for Latent Distributional Parameters

Minxing Zheng, Wenbin Zhou, Shixiang Zhu

Many prediction problems seek to infer an unobserved, instance-specific parameter that governs the distribution of an observable response, even though the latent parameter is unava…

stat.ML2026

Deciding When to Decide: Testing Operational Suboptimality Under Distributional Shift

Minxing Zheng, Holly Wiberg, Shixiang Zhu

Deployed decisions are often optimized once and retained because updates impose operational, regulatory, or switching costs. As operating conditions change, when should such decisi…

cs.LG2026

Learning to Test: Physics-Informed Representation for Dynamical Instability Detection

Minxing Zheng, Zewei Deng, Liyan Xie +1

Many safety-critical scientific and engineering systems evolve according to differential-algebraic equations (DAEs), where dynamical behavior is constrained by physical laws and ad…

cs.CR2025

MISLEADER: Defending against Model Extraction with Ensembles of Distilled Models

Xueqi Cheng, Minxing Zheng, Shixiang Zhu +1

Model extraction attacks aim to replicate the functionality of a black-box model through query access, threatening the intellectual property (IP) of machine-learning-as-a-service (…

cs.LG2024

Generative Conformal Prediction with Vectorized Non-Conformity Scores

Minxing Zheng, Shixiang Zhu

Conformal prediction (CP) provides model-agnostic uncertainty quantification with guaranteed coverage, but conventional methods often produce overly conservative uncertainty sets,…

stat.ME2023

Change Point Inference for Non-Euclidean Data Sequences using Distance Profiles

Paromita Dubey, Minxing Zheng

We introduce a powerful scan statistic and the corresponding test for detecting the presence and pinpointing the location of a change point within the distribution of a data sequen…