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Second-order methods

Use second-order statistics to process data.

Papers

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Showing 21–30 of 181 papers

TitleStatusHype
FLeNS: Federated Learning with Enhanced Nesterov-Newton SketchCode0
Alternating Iteratively Reweighted _1 and Subspace Newton Algorithms for Nonconvex Sparse OptimizationCode0
Fed-Sophia: A Communication-Efficient Second-Order Federated Learning Algorithm—0
Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement LearningCode1
Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization—0
Stochastic Newton Proximal Extragradient Method—0
Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks—0
A Gauss-Newton Approach for Min-Max Optimization in Generative Adversarial NetworksCode0
Inverse-Free Fast Natural Gradient Descent Method for Deep Learning—0
SGD with Partial Hessian for Deep Neural Networks OptimizationCode0
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