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Papers
Universal Sharpness Dynamics in Neural Network Training: Fixed Point Analysis, Edge of Stability, and Route to Chaos
ICLR 2025
Deep linear networks for regression are implicitly regularized towards flat minima
NeurIPS 2024
Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization
NeurIPS 2024
Foreseeing Reconstruction Quality of Gradient Inversion: An Optimization Perspective
AAAI 2024
Minimizing Layerwise Activation Norm Improves Generalization in Federated Learning
WACV 2024
Sharpness-Aware Minimization and the Edge of Stability
JMLR 2024
Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization
CVPR 2023
Learning to Generalize Provably in Learning to Optimize
AISTATS 2023
Phase diagram of early training dynamics in deep neural networks: effect of the learning rate, depth, and width
NeurIPS 2023
SAM operates far from home: eigenvalue regularization as a dynamical phenomenon
ICML 2023
Second-order regression models exhibit progressive sharpening to the edge of stability
ICML 2023
Trajectory Alignment: Understanding the Edge of Stability Phenomenon via Bifurcation Theory
NeurIPS 2023
Understanding Edge-of-Stability Training Dynamics with a Minimalist Example
ICLR 2023
Analyzing Sharpness along GD Trajectory: Progressive Sharpening and Edge of Stability
NeurIPS 2022
Approximate Secular Equations for the Cubic Regularization Subproblem
NeurIPS 2022
Does the Data Induce Capacity Control in Deep Learning?
ICML 2022
Power-Law Escape Rate of SGD
ICML 2022
Understanding Gradient Descent on the Edge of Stability in Deep Learning
ICML 2022
Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability
ICLR 2021
Label Noise SGD Provably Prefers Flat Global Minimizers
NeurIPS 2021
Learning with Gradient Descent and Weakly Convex Losses
AISTATS 2021
The Heavy-Tail Phenomenon in SGD
ICML 2021
Tilting the playing field: Dynamical loss functions for machine learning
ICML 2021
Analytic Characterization of the Hessian in Shallow ReLU Models: A Tale of Symmetry
NeurIPS 2020
An Investigation into Neural Net Optimization via Hessian Eigenvalue Density
ICML 2019