Paquette, Courtney

13 publications

NeurIPS 2025 Dimension-Adapted Momentum Outscales SGD Damien Ferbach, Katie Everett, Gauthier Gidel, Elliot Paquette, Courtney Paquette

AISTATS 2025 Implicit Diffusion: Efficient Optimization Through Stochastic Sampling Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet

NeurIPS 2024 4+3 Phases of Compute-Optimal Neural Scaling Laws Elliot Paquette, Courtney Paquette, Lechao Xiao, Jeffrey Pennington

NeurIPSW 2024 High Dimensional First Order Mini-Batch Algorithms on Quadratic Problems Andrew Nicholas Cheng, Kiwon Lee, Courtney Paquette

ICMLW 2024 Implicit Diffusion: Efficient Optimization Through Stochastic Sampling Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet

COLT 2024 Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems Extended Abstract Tomas Gonzalez, Cristobal Guzman, Courtney Paquette

NeurIPS 2024 The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms Elizabeth Collins-Woodfin, Inbar Seroussi, Begoña García Malaxechebarría, Andrew W. Mackenzie, Elliot Paquette, Courtney Paquette

NeurIPS 2022 Implicit Regularization or Implicit Conditioning? Exact Risk Trajectories of SGD in High Dimensions Courtney Paquette, Elliot Paquette, Ben Adlam, Jeffrey Pennington

ICML 2022 Only Tails Matter: Average-Case Universality and Robustness in the Convex Regime Leonardo Cunha, Gauthier Gidel, Fabian Pedregosa, Damien Scieur, Courtney Paquette

NeurIPS 2022 Trajectory of Mini-Batch Momentum: Batch Size Saturation and Convergence in High Dimensions Kiwon Lee, Andrew Cheng, Elliot Paquette, Courtney Paquette

NeurIPS 2021 Dynamics of Stochastic Momentum Methods on Large-Scale, Quadratic Models Courtney Paquette, Elliot Paquette

COLT 2021 SGD in the Large: Average-Case Analysis, Asymptotics, and Stepsize Criticality Courtney Paquette, Kiwon Lee, Fabian Pedregosa, Elliot Paquette

AISTATS 2018 Catalyst for Gradient-Based Nonconvex Optimization Courtney Paquette, Hongzhou Lin, Dmitriy Drusvyatskiy, Julien Mairal, Zaïd Harchaoui