Courtney Paquette

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 20

Top Topics

High Dimensions

Top Venues

Publications

Tomás González, Cristóbal Guzmán, Courtney Paquette
Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems extended abstract. COLT (2024)
Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet
Implicit Diffusion: Efficient Optimization through Stochastic Sampling. CoRR (2024)
Tomás González, Cristóbal Guzmán, Courtney Paquette
Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems. CoRR (2024)
Elliot Paquette, Courtney Paquette, Lechao Xiao, Jeffrey Pennington
4+3 Phases of Compute-Optimal Neural Scaling Laws. CoRR (2024)
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)
Leonardo Cunha, Gauthier Gidel, Fabian Pedregosa, Damien Scieur, Courtney Paquette
Only Tails Matter: Average-Case Universality and Robustness in the Convex Regime. CoRR (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)
Leonardo Cunha, Gauthier Gidel, Fabian Pedregosa, Damien Scieur, Courtney Paquette
Only tails matter: Average-Case Universality and Robustness in the Convex Regime. ICML (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)
Courtney Paquette, Katya Scheinberg
A Stochastic Line Search Method with Expected Complexity Analysis. SIAM J. Optim. 30 (1) (2020)
Dmitriy Drusvyatskiy, Courtney Paquette
Efficiency of minimizing compositions of convex functions and smooth maps. Math. Program. 178 (1-2) (2019)
Courtney Paquette, Hongzhou Lin, Dmitriy Drusvyatskiy, Julien Mairal, Zaïd Harchaoui
Catalyst for Gradient-based Nonconvex Optimization. AISTATS (2018)
Damek Davis, Dmitriy Drusvyatskiy, Kellie J. MacPhee, Courtney Paquette
Subgradient Methods for Sharp Weakly Convex Functions. J. Optim. Theory Appl. 179 (3) (2018)