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Second-order methods

Use second-order statistics to process data.

Papers

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Showing 91–100 of 181 papers

TitleStatusHype
Doubly Adaptive Scaled Algorithm for Machine Learning Using Second-Order Information—0
Structured second-order methods via natural gradient descent—0
M-FAC: Efficient Matrix-Free Approximations of Second-Order InformationCode1
Bilinear Parameterization for Non-Separable Singular Value Penalties—0
LocoProp: Enhancing BackProp via Local Loss Optimization—0
Tensor Normal Training for Deep Learning ModelsCode0
FedNL: Making Newton-Type Methods Applicable to Federated Learning—0
Exact Stochastic Second Order Deep Learning—0
Quasi-Newton Quasi-Monte Carlo for variational Bayes—0
Research of Damped Newton Stochastic Gradient Descent Method for Neural Network Training—0
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