3 papers
math.ST2025
Learning bounds for doubly-robust covariate shift adaptation
Jeonghwan Lee, Cong Ma
Distribution shift between the training domain and the test domain poses a key challenge for modern machine learning. An extensively studied instance is the \emph{covariate shift},…
math.ST2025
The Adaptivity Barrier in Batched Nonparametric Bandits: Sharp Characterization of the Price of Unknown Margin
Rong Jiang, Cong Ma
We study batched nonparametric contextual bandits under a margin condition when the margin parameter is unknown. To capture the statistical cost of this ignorance, we introduce…
stat.ME2025
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…