Co-occurring keywords · papers mentioning both
Papers
Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods
NeurIPS 2022
FedNL: Making Newton-Type Methods Applicable to Federated Learning
ICML 2022
Gradient Descent on Neurons and its Link to Approximate Second-order Optimization
ICML 2022
Second-Order Sensitivity Analysis for Bilevel Optimization
AISTATS 2022
SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning
ICLR 2022
Symmetry Teleportation for Accelerated Optimization
NeurIPS 2022
The Hessian Screening Rule
NeurIPS 2022
The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models
EMNLP 2022
ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning
AAAI 2021
Analytic Insights into Structure and Rank of Neural Network Hessian Maps
NeurIPS 2021
An Inertial Newton Algorithm for Deep Learning
JMLR 2021
A Trace-restricted Kronecker-Factored Approximation to Natural Gradient
AAAI 2021
LocalNewton: Reducing communication rounds for distributed learning
UAI 2021
M-FAC: Efficient Matrix-Free Approximations of Second-Order Information
NeurIPS 2021
Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update
NeurIPS 2021
On the Variance of the Fisher Information for Deep Learning
NeurIPS 2021
Second-Order Neural ODE Optimizer
NeurIPS 2021
Second Order Techniques for Learning Time-series with Structural Breaks
AAAI 2021
SKFAC: Training Neural Networks With Faster Kronecker-Factored Approximate Curvature
CVPR 2021
SONIA: A Symmetric Blockwise Truncated Optimization Algorithm
AISTATS 2021
Tensor Normal Training for Deep Learning Models
NeurIPS 2021
THOR, Trace-based Hardware-driven Layer-Oriented Natural Gradient Descent Computation
AAAI 2021
Tractable structured natural-gradient descent using local parameterizations
ICML 2021
Whitening and Second Order Optimization Both Make Information in the Dataset Unusable During Training, and Can Reduce or Prevent Generalization
ICML 2021
Curvature-corrected learning dynamics in deep neural networks
ICML 2020