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Second-order methods

Use second-order statistics to process data.

Papers

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Showing 151–160 of 181 papers

TitleStatusHype
Block-diagonal Hessian-free Optimization for Training Neural Networks—0
Efficient Second-Order Online Kernel Learning with Adaptive Embedding—0
Nesterov's Acceleration For Approximate Newton—0
Accelerating SGD for Distributed Deep-Learning Using Approximated Hessian Matrix—0
A Generic Approach for Escaping Saddle points—0
First and Second Order Methods for Online Convolutional Dictionary Learning—0
Second-Order Optimization for Non-Convex Machine Learning: An Empirical Study—0
Approximate Newton Methods and Their Local Convergence—0
Optimization Methods for Supervised Machine Learning: From Linear Models to Deep LearningCode0
Second-Order Kernel Online Convex Optimization with Adaptive Sketching—0
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