8 papers
Cubic-Root Gaussian Approximation under Unrestricted Covariance
Zijun Gao, Weihan Zhang
For Gaussian approximation over high-dimensional rectangles under unrestricted covariance, Chernozhukov et al. (2023b) conjectured that the rate, up to logarithmic facto…
Flexible Inference for Winners with Conditional Validity
Soham Bakshi, Lingjun Gao, Zijun Gao +1
Researchers often select top-performing options or winners, based on a data-driven criterion, such as treatments, models, or model features and then report effect estimates for the…
Reliable conformal novelty detection at the decision boundary
Zijun Gao, Etienne Roquain, Daniel Xiang
Novelty detection via conformal -values and BH procedure provides distribution-free global false discovery rate (FDR) control. We present here fundamental limits of this approac…
Estimation and Inference for Causal Explainability
Weihan Zhang, Zijun Gao
Understanding how much each variable contributes to an outcome is a central question across disciplines. A causal view of explainability is favorable for its ability in uncovering…
Reliable Selection of Heterogeneous Treatment Effect Estimators
Jiayi Guo, Zijun Gao
We study the problem of selecting the best heterogeneous treatment effect (HTE) estimator from a collection of candidates in settings where the treatment effect is fundamentally un…
MUSE: Multi-Treatment Experiment Design for Winner Selection and Effect Estimation
Jiachen Xu, Jian Qian, Zijun Gao
We study the design of experiments with multiple treatment levels, a setting common in clinical trials and online A/B/n testing. Unlike single-treatment studies, practical analyses…