Pesme, Scott

9 publications

NeurIPS 2025 A Theoretical Framework for Grokking: Interpolation Followed by Riemannian Norm Minimisation Etienne Boursier, Scott Pesme, Radu-Alexandru Dragomir

NeurIPS 2025 MAP Estimation with Denoisers: Convergence Rates and Guarantees Scott Pesme, Giacomo Meanti, Michael Arbel, Julien Mairal

NeurIPS 2024 Implicit Bias of Mirror Flow on Separable Data Scott Pesme, Radu-Alexandru Dragomir, Nicolas Flammarion

AISTATS 2024 Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks Hristo Papazov, Scott Pesme, Nicolas Flammarion

NeurIPS 2023 (S)GD over Diagonal Linear Networks: Implicit Bias, Large Stepsizes and Edge of Stability Mathieu Even, Scott Pesme, Suriya Gunasekar, Nicolas Flammarion

NeurIPS 2023 Saddle-to-Saddle Dynamics in Diagonal Linear Networks Scott Pesme, Nicolas Flammarion

NeurIPS 2021 Implicit Bias of SGD for Diagonal Linear Networks: A Provable Benefit of Stochasticity Scott Pesme, Loucas Pillaud-Vivien, Nicolas Flammarion

ICML 2020 On Convergence-Diagnostic Based Step Sizes for Stochastic Gradient Descent Scott Pesme, Aymeric Dieuleveut, Nicolas Flammarion

NeurIPS 2020 Online Robust Regression via SGD on the L1 Loss Scott Pesme, Nicolas Flammarion