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Second-order methods

Use second-order statistics to process data.

Papers

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Showing 51–60 of 181 papers

TitleStatusHype
FLeNS: Federated Learning with Enhanced Nesterov-Newton SketchCode0
Stochastic Newton and Cubic Newton Methods with Simple Local Linear-Quadratic RatesCode0
A Mini-Block Fisher Method for Deep Neural Networks—0
Distributed Second Order Methods with Fast Rates and Compressed Communication—0
Alternating direction method of multipliers for regularized multiclass support vector machines—0
Distributed Quasi-Newton Method for Fair and Fast Federated Learning—0
A Homogenization Approach for Gradient-Dominated Stochastic Optimization—0
DDPNOpt: Differential Dynamic Programming Neural Optimizer—0
Gram-Gauss-Newton Method: Learning Overparameterized Neural Networks for Regression Problems—0
Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization—0
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