5 papers
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…
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…
Learning to Test: Latent Representation Learning for Dynamic Instability Detection
Minxing Zheng, Zewei Deng, Liyan Xie +1
Stability assessment is central to safety-critical systems governed by differential-algebraic equations (DAEs), whose dynamics are constrained by physical laws and admissibility co…
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 (…
Generative Conformal Prediction with Optimized Coverage Allocation
Minxing Zheng, Shixiang Zhu
Conformal prediction provides model-agnostic uncertainty quantification with guaranteed coverage, but conventional methods often yield overly conservative uncertainty sets, particu…