33 citations · 133 across the 43 of their papers we have counts for
5 papers · 1 filter
Dyson Equation for Correlated Linearizations and Test Error of Random Features Regression
Hugo Latourelle-Vigeant, Elliot Paquette
This paper develops some theory of the Dyson equation for correlated linearizations and uses it to solve a problem on asymptotic deterministic equivalent for the test error in rand…
Hitting the High-Dimensional Notes: An ODE for SGD learning dynamics on GLMs and multi-index models
Elizabeth Collins-Woodfin, Courtney Paquette, Elliot Paquette +1
We analyze the dynamics of streaming stochastic gradient descent (SGD) in the high-dimensional limit when applied to generalized linear models and multi-index models (e.g. logistic…
Differentially Private Linear Regression with Linked Data
Shurong Lin, Elliot Paquette, Eric D. Kolaczyk
There has been increasing demand for establishing privacy-preserving methodologies for modern statistics and machine learning. Differential privacy, a mathematical notion from comp…
Fitting an ellipsoid to a quadratic number of random points
Afonso S. Bandeira, Antoine Maillard, Shahar Mendelson +1
We consider the problem of fitting standard Gaussian random vectors in to the boundary of a centered ellipsoid, as . This problem…
High-dimensional limit of one-pass SGD on least squares
Elizabeth Collins-Woodfin, Elliot Paquette
We give a description of the high-dimensional limit of one-pass single-batch stochastic gradient descent (SGD) on a least squares problem. This limit is taken with non-vanishing st…