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Second-order methods

Use second-order statistics to process data.

Papers

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Showing 11–20 of 181 papers

TitleStatusHype
Preconditioners for the Stochastic Training of Neural Fields—0
GP-FL: Model-Based Hessian Estimation for Second-Order Over-the-Air Federated Learning—0
A Learn-to-Optimize Approach for Coordinate-Wise Step Sizes for Quasi-Newton Methods—0
Gradient Norm Regularization Second-Order Algorithms for Solving Nonconvex-Strongly Concave Minimax Problems—0
Don't Be So Positive: Negative Step Sizes in Second-Order Methods—0
Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor GeneralizationCode0
Improving Stochastic Cubic Newton with Momentum—0
Second-Order Min-Max Optimization with Lazy Hessians—0
Unlocking FedNL: Self-Contained Compute-Optimized Implementation—0
Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility—0
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