1 citations · 1 across the 6 of their papers we have counts for
4 papers · 1 filter
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},…
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…
Batched Nonparametric Contextual Bandits
Rong Jiang, Cong Ma
We study nonparametric contextual bandits under batch constraints, where the expected reward for each action is modeled as a smooth function of covariates, and the policy updates a…
On the design-dependent suboptimality of the Lasso
Reese Pathak, Cong Ma
This paper investigates the effect of the design matrix on the ability (or inability) to estimate a sparse parameter in linear regression. More specifically, we characterize the op…