4 papers
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…
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…
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…
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…