23 citations · 149 across the 33 of their papers we have counts for
4 papers · 1 filter
Sparse High-Dimensional Linear Regression. Algorithmic Barriers and a Local Search Algorithm
David Gamarnik, Ilias Zadik
We consider a sparse high dimensional regression model where the goal is to recover a -sparse unknown vector from noisy linear observations of the form $Y=Xβ^*+W \in \…
Orthogonal Machine Learning: Power and Limitations
Lester Mackey, Vasilis Syrgkanis, Ilias Zadik
Double machine learning provides -consistent estimates of parameters of interest even when high-dimensional or nonparametric nuisance parameters are estimated at an $n^{-…
Mixed-integer convex representability
Miles Lubin, Juan Pablo Vielma, Ilias Zadik
Motivated by recent advances in solution methods for mixed-integer convex optimization (MICP), we study the fundamental and open question of which sets can be represented exactly a…
High-Dimensional Regression with Binary Coefficients. Estimating Squared Error and a Phase Transition
David Gamarnik, Ilias Zadik
We consider a sparse linear regression model Y=Xβ^{*}+W where X has a Gaussian entries, W is the noise vector with mean zero Gaussian entries, and β^{*} is a binary vector with sup…