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Second-order methods

Use second-order statistics to process data.

Papers

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Showing 1–10 of 181 papers

TitleStatusHype
NysAct: A Scalable Preconditioned Gradient Descent using Nystrom ApproximationCode0
KOALA++: Efficient Kalman-Based Optimization of Neural Networks with Gradient-Covariance Products—0
Accelerated Training of Federated Learning via Second-Order Methods—0
Towards Practical Second-Order Optimizers in Deep Learning: Insights from Fisher Information AnalysisCode2
Representation Meets Optimization: Training PINNs and PIKANs for Gray-Box Discovery in Systems Pharmacology—0
FedOSAA: Improving Federated Learning with One-Step Anderson Acceleration—0
SASSHA: Sharpness-aware Adaptive Second-order Optimization with Stable Hessian ApproximationCode1
Online Covariance Matrix Estimation in Sketched Newton MethodsCode0
A Survey of Optimization Methods for Training DL Models: Theoretical Perspective on Convergence and Generalization—0
Distributed Quasi-Newton Method for Fair and Fast Federated Learning—0
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