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Second-order methods
Second-order methods
Use second-order statistics to process data.
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Showing 1–10 of 181 papers
Title
Date
Tasks
Status
Hype
Towards Practical Second-Order Optimizers in Deep Learning: Insights from Fisher Information Analysis
Apr 26, 2025
Computational Efficiency
image-classification
Code
Code Available
2
Automatic Gradient Descent: Deep Learning without Hyperparameters
Apr 11, 2023
Deep Learning
Second-order methods
Code
Code Available
2
Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization
Jun 9, 2020
Bayesian Optimization
Second-order methods
Code
Code Available
2
MKOR: Momentum-Enabled Kronecker-Factor-Based Optimizer Using Rank-1 Updates
Jun 2, 2023
Second-order methods
Code
Code Available
1
Low Rank Saddle Free Newton: A Scalable Method for Stochastic Nonconvex Optimization
Feb 7, 2020
Second-order methods
Code
Code Available
1
MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation
Mar 27, 2020
Bilevel Optimization
Neural Architecture Search
Code
Code Available
1
Communication-Efficient Stochastic Zeroth-Order Optimization for Federated Learning
Jan 24, 2022
Federated Learning
Second-order methods
Code
Code Available
1
ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning
Jun 1, 2020
BIG-bench Machine Learning
Second-order methods
Code
Code Available
1
Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective
Feb 5, 2024
Second-order methods
Code
Code Available
1
M-FAC: Efficient Matrix-Free Approximations of Second-Order Information
Jul 7, 2021
Network Pruning
Second-order methods
Code
Code Available
1
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