53 citations · 177 across the 34 of their papers we have counts for
5 papers · 1 filter
When is it worthwhile to jackknife? Breaking the quadratic barrier for Z-estimators
Licong Lin, Fangzhou Su, Wenlong Mou +2
Resampling methods are especially well-suited to inference with estimators that provide only "black-box'' access. Jackknife is a form of resampling, widely used for bias correction…
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…
Off-policy estimation of linear functionals: Non-asymptotic theory for semi-parametric efficiency
Wenlong Mou, Martin J. Wainwright, Peter L. Bartlett
The problem of estimating a linear functional based on observational data is canonical in both the causal inference and bandit literatures. We analyze a broad class of two-stage pr…
Optimal variance-reduced stochastic approximation in Banach spaces
Wenlong Mou, Koulik Khamaru, Martin J. Wainwright +2
We study the problem of estimating the fixed point of a contractive operator defined on a separable Banach space. Focusing on a stochastic query model that provides noisy evaluatio…
A Diffusion Process Perspective on Posterior Contraction Rates for Parameters
Wenlong Mou, Nhat Ho, Martin J. Wainwright +2
We analyze the posterior contraction rates of parameters in Bayesian models via the Langevin diffusion process, in particular by controlling moments of the stochastic process and t…