937 citations · 8.2k across the 142 of their papers we have counts for
155 papers
When is the estimated propensity score better? High-dimensional analysis and bias correction
Fangzhou Su, Wenlong Mou, Peng Ding +1
Anecdotally, using an estimated propensity score is superior to the true propensity score in estimating the average treatment effect based on observational data. However, this clai…
Noisy recovery from random linear observations: Sharp minimax rates under elliptical constraints
Reese Pathak, Martin J. Wainwright, Lin Xiao
Estimation problems with constrained parameter spaces arise in various settings. In many of these problems, the observations available to the statistician can be modelled as arisin…
Semi-parametric inference based on adaptively collected data
Licong Lin, Koulik Khamaru, Martin J. Wainwright
Many standard estimators, when applied to adaptively collected data, fail to be asymptotically normal, thereby complicating the construction of confidence intervals. We address thi…
Kernel-based off-policy estimation without overlap: Instance optimality beyond semiparametric efficiency
Wenlong Mou, Peng Ding, Martin J. Wainwright +1
We study optimal procedures for estimating a linear functional based on observational data. In many problems of this kind, a widely used assumption is strict overlap, i.e., uniform…
Policy evaluation from a single path: Multi-step methods, mixing and mis-specification
Yaqi Duan, Martin J. Wainwright
We study non-parametric estimation of the value function of an infinite-horizon -discounted Markov reward process (MRP) using observations from a single trajectory. We provide n…
Krylov-Bellman boosting: Super-linear policy evaluation in general state spaces
Eric Xia, Martin J. Wainwright
We present and analyze the Krylov-Bellman Boosting (KBB) algorithm for policy evaluation in general state spaces. It alternates between fitting the Bellman residual using non-param…