activity
20192026
most citedFedSplit: An algorithmic framework for fast federated optimization

81 citations · 130 across the 17 of their papers we have counts for

collaborators

17 papers

math.ST2026

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…

math.MG2026

Optimal mean width and metric entropy estimates for convex bodies

Grigoris Paouris, Reese Pathak

We show that for any and any convex body , there exists such that \[ \mathrm{diam}(TK) \lesssim \sqrt{n} \mathrm{vr}(K), \…

math.ST2026

Minimum Norm Interpolation via The Local Theory of Banach Spaces: The Role of Gaussianity

Gil Kur, Reese Pathak

We study minimum-norm interpolation (MNI) in overparameterized linear regression with isotropic Gaussian covariates, in settings where the MNI has no closed-form formula. Whereas m…

math.MG2026

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 measur…

math.PR2026

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{…

math.PR2026

Gaussian Width of Convex Sets via Integral Decompositions, Projections, and the Distribution of Intrinsic Volumes

Reese Pathak, Nikita Zhivotovskiy

We revisit the problem of bounding the expected supremum of a canonical Gaussian process indexed by a convex set . We develop two decompositions for the Gau…