Publications (17)
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…
On Identifying and Mitigating Bias in the Estimation of the COVID-19 Case Fatality Rate
Anastasios Nikolas Angelopoulos, Reese Pathak, Rohit Varma +1
The relative case fatality rates (CFRs) between groups and countries are key measures of relative risk that guide policy decisions regarding scarce medical resource allocation duri…
On the metric projection onto a convex set: reverse Hölder inequalities and upper bounds
Reese Pathak
We study the -norm of the metric projection onto a closed, convex set when is the uniform measure on the sphere or the standard Gaussian meas…
Beyond Modern Asymptotics for Log-Likelihood Ratios in Logistic Regression
Hugo Chardon, Reese Pathak, Nikita Zhivotovskiy
We characterize the finite sample behavior of the log-likelihood ratio statistic in binary logistic regression, uniformly over both the design and the target parameter. For $n\geq…
A remark on the majorizing measures theorem for general processes
Reese Pathak, Nikita Zhivotovskiy
We show that the lower bound in the majorizing measures theorem holds for a large class of random vectors. Specifically, suppose is a centered random vector in $\mathbf…
A new similarity measure for covariate shift with applications to nonparametric regression
Reese Pathak, Cong Ma, Martin J. Wainwright
We study covariate shift in the context of nonparametric regression. We introduce a new measure of distribution mismatch between the source and target distributions that is based o…