2 papers
stat.ML2026
A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel
Yindong Chen, Yiwei Wang, Lulu Kang +1
We propose a novel deterministic sampling method, EVI-MMD, to approximate a target distribution by minimizing the kernel discrepancy, also known as the Maximum Mean Discrepa…
stat.ME2025
Kernel Discrepancy-Based Rerandomization for Controlled Experiments
Yiou Li, Lulu Kang
This paper introduces a kernel discrepancy-based framework for rerandomization to enhance the precision of causal inference in controlled experiments. We demonstrate that the kerne…