Publications (4)
When Are Trade-Off Functions Testable from Finite Samples?
Kaining Shi, Qiaosen Wang, Cong Ma
We study finite-sample inference for the trade-off function of two unknown probability distributions, the function that traces the optimal type I/type II error frontier in binary t…
Privacy Preserving Adaptive Experiment Design
Jiachun Li, Kaining Shi, David Simchi-Levi
Adaptive experiment is widely adopted to estimate conditional average treatment effect (CATE) in clinical trials and many other scenarios. While the primary goal in experiment is t…
Auditing Differential Privacy in the Black-Box Setting
Kaining Shi, Cong Ma
This paper introduces a novel theoretical framework for auditing differential privacy (DP) in a black-box setting. Leveraging the concept of -differential privacy, we explicitly…
Beyond ATE: Multi-Criteria Design for A/B Testing
Jiachun Li, Kaining Shi, David Simchi-Levi
In the era of large-scale AI deployment and high-stakes clinical trials, adaptive experimentation faces a ``trilemma'' of conflicting objectives: minimizing cumulative regret (welf…