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Second-order methods

Use second-order statistics to process data.

Papers

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Showing 61–70 of 181 papers

TitleStatusHype
Doubly Adaptive Scaled Algorithm for Machine Learning Using Second-Order Information—0
Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization—0
Accelerating Stochastic Probabilistic Inference—0
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold—0
Debiasing Distributed Second Order Optimization with Surrogate Sketching and Scaled Regularization—0
Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training—0
Curvature-corrected learning dynamics in deep neural networks—0
A Generic Approach for Escaping Saddle points—0
Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses—0
Convolutions and More as Einsum: A Tensor Network Perspective with Advances for Second-Order Methods—0
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