33 citations · 133 across the 43 of their papers we have counts for
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math.PR2021
Random geometric graphs and the spherical Wishart matrix
Elliot Paquette, Andrew Vander Werf
We consider the random geometric graph on vertices drawn uniformly from a --dimensional sphere. We focus on the sparse regime, when the expected degree is constant independe…
math.OC2021
Dynamics of Stochastic Momentum Methods on Large-scale, Quadratic Models
Courtney Paquette, Elliot Paquette
We analyze a class of stochastic gradient algorithms with momentum on a high-dimensional random least squares problem. Our framework, inspired by random matrix theory, provides an…
math.OC2021★ 4 cited
SGD in the Large: Average-case Analysis, Asymptotics, and Stepsize Criticality
Courtney Paquette, Kiwon Lee, Fabian Pedregosa +1
We propose a new framework, inspired by random matrix theory, for analyzing the dynamics of stochastic gradient descent (SGD) when both number of samples and dimensions are large.…