Publications (14)
On the failure of the bootstrap for Chatterjee's rank correlation
Zhexiao Lin, Fang Han
While researchers commonly use the bootstrap for statistical inference, many of us have realized that the standard bootstrap, in general, does not work for Chatterjee's rank correl…
Variance reduction combining pre-experiment and in-experiment data
Zhexiao Lin, Pablo Crespo
Online controlled experiments (A/B testing) are fundamental to data-driven decision-making in many companies. Improving the sensitivity of these experiments under fixed sample size…
Domain-Shift-Aware Conformal Prediction for Large Language Models
Zhexiao Lin, Yuanyuan Li, Neeraj Sarna +2
Large language models have achieved impressive performance across diverse tasks. However, their tendency to produce overconfident and factually incorrect outputs, known as hallucin…
Limit theorems of Chatterjee's rank correlation
Zhexiao Lin, Fang Han
Establishing the limiting distribution of Chatterjee's rank correlation for a general, possibly non-independent, pair of random variables has been eagerly awaited by many. This pap…
Introducing the b-value: combining unbiased and biased estimators from a sensitivity analysis perspective
Zhexiao Lin, Peter J. Bickel, Peng Ding
In empirical research, when we have multiple estimators for the same parameter of interest, a central question arises: how do we combine unbiased but less precise estimators with b…
Nearest-Neighbor Radii under Dependent Sampling
Yuanyuan Gao, Yilong Hou, Zhexiao Lin
Nearest-neighbor methods are fundamental to classical and modern machine learning, yet their geometric properties are typically analyzed under independent sampling. In this paper,…