Elliot Paquette

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 18

Top Topics

High Dimensions

Covariance Matrices

Differentially Private

Top Venues

Comb. Probab. Comput.

J. Optim. Theory Appl.

Publications

Elliot Paquette, Courtney Paquette, Lechao Xiao, Jeffrey Pennington
4+3 Phases of Compute-Optimal Neural Scaling Laws. CoRR (2024)
Noah Marshall, Ke Liang Xiao, Atish Agarwala, Elliot Paquette
A Clipped Trip: the Dynamics of SGD with Gradient Clipping in High-Dimensions. CoRR (2024)
Shurong Lin, Elliot Paquette, Eric D. Kolaczyk
Differentially Private Linear Regression with Linked Data. CoRR (2023)
Afonso S. Bandeira, Antoine Maillard, Shahar Mendelson, Elliot Paquette
Fitting an ellipsoid to a quadratic number of random points. CoRR (2023)
Tim Hoheisel, Elliot Paquette
Uniqueness in Nuclear Norm Minimization: Flatness of the Nuclear Norm Sphere and Simultaneous Polarization. J. Optim. Theory Appl. 197 (1) (2023)
Courtney Paquette, Bart van Merriënboer, Elliot Paquette, Fabian Pedregosa
Halting Time is Predictable for Large Models: A Universality Property and Average-Case Analysis. Found. Comput. Math. 23 (2) (2023)
Elizabeth Collins-Woodfin, Courtney Paquette, Elliot Paquette, Inbar Seroussi
Hitting the High-Dimensional Notes: An ODE for SGD learning dynamics on GLMs and multi-index models. CoRR (2023)
Courtney Paquette, Elliot Paquette, Ben Adlam, Jeffrey Pennington
Implicit Regularization or Implicit Conditioning? Exact Risk Trajectories of SGD in High Dimensions. CoRR (2022)
Courtney Paquette, Elliot Paquette, Ben Adlam, Jeffrey Pennington
Implicit Regularization or Implicit Conditioning? Exact Risk Trajectories of SGD in High Dimensions. NeurIPS (2022)
Kiwon Lee, Andrew N. Cheng, Elliot Paquette, Courtney Paquette
Trajectory of Mini-Batch Momentum: Batch Size Saturation and Convergence in High Dimensions. NeurIPS (2022)
Kiwon Lee, Andrew N. Cheng, Courtney Paquette, Elliot Paquette
Trajectory of Mini-Batch Momentum: Batch Size Saturation and Convergence in High Dimensions. CoRR (2022)
Courtney Paquette, Elliot Paquette
Dynamics of Stochastic Momentum Methods on Large-scale, Quadratic Models. NeurIPS (2021)
Courtney Paquette, Kiwon Lee, Fabian Pedregosa, Elliot Paquette
SGD in the Large: Average-case Analysis, Asymptotics, and Stepsize Criticality. COLT (2021)
Courtney Paquette, Kiwon Lee, Fabian Pedregosa, Elliot Paquette
SGD in the Large: Average-case Analysis, Asymptotics, and Stepsize Criticality. CoRR (2021)
Courtney Paquette, Elliot Paquette
Dynamics of Stochastic Momentum Methods on Large-scale, Quadratic Models. CoRR (2021)
Elliot Paquette, Thomas Trogdon
Universality for the conjugate gradient and MINRES algorithms on sample covariance matrices. CoRR (2020)
Hoi. H. Nguyen, Elliot Paquette
Surjectivity of near-square random matrices. Comb. Probab. Comput. 29 (2) (2020)
Christopher Hoffman, Matthew Kahle, Elliot Paquette
The Threshold for Integer Homology in Random d-Complexes. Discret. Comput. Geom. 57 (4) (2017)
Tamás Keleti, Elliot Paquette
gons. Am. Math. Mon. 117 (2) (2010)