conftrace_

hessian eigenvalue

26 papers

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Co-occurring keywords

gradient descent (1144) edge of stability (14) neural network optimization (1293) neural network (6616) loss landscape (149) non-convex optimization (547) stochastic gradient descent (1091) implicit regularization (93) eigenvalue spectrum (7) flat minimum (15)

Papers

Foreseeing Reconstruction Quality of Gradient Inversion: An Optimization Perspective AAAI 2024
Minimizing Layerwise Activation Norm Improves Generalization in Federated Learning WACV 2024
Deep linear networks for regression are implicitly regularized towards flat minima NIPS 2024
Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization NIPS 2024
Sharpness-Aware Minimization and the Edge of Stability JMLR 2024
Phase diagram of early training dynamics in deep neural networks: effect of the learning rate, depth, and width NIPS 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 NIPS 2023
Learning to Generalize Provably in Learning to Optimize AISTATS 2023
Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization CVPR 2023
Understanding Gradient Descent on the Edge of Stability in Deep Learning ICML 2022
Approximate Secular Equations for the Cubic Regularization Subproblem NIPS 2022
Power-Law Escape Rate of SGD ICML 2022
Does the Data Induce Capacity Control in Deep Learning? ICML 2022
Analyzing Sharpness along GD Trajectory: Progressive Sharpening and Edge of Stability NIPS 2022
The Heavy-Tail Phenomenon in SGD ICML 2021
Learning with Gradient Descent and Weakly Convex Losses AISTATS 2021
Label Noise SGD Provably Prefers Flat Global Minimizers NIPS 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 NIPS 2020
An Investigation into Neural Net Optimization via Hessian Eigenvalue Density ICML 2019
The Goldilocks Zone: Towards Better Understanding of Neural Network Loss Landscapes AAAI 2019
Adaptive Negative Curvature Descent with Applications in Non-convex Optimization NIPS 2018
Natasha: Faster Non-Convex Stochastic Optimization via Strongly Non-Convex Parameter ICML 2017