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Second-order methods

Use second-order statistics to process data.

Papers

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Showing 141–150 of 181 papers

TitleStatusHype
Stochastic Trust Region Inexact Newton Method for Large-scale Machine LearningCode0
Bilinear Parameterization For Differentiable Rank-Regularization—0
Deep Reinforcement Learning via L-BFGS Optimization—0
Large batch size training of neural networks with adversarial training and second-order informationCode0
Stochastic Second-order Methods for Non-convex Optimization with Inexact Hessian and Gradient—0
A Distributed Second-Order Algorithm You Can Trust—0
Online Second Order Methods for Non-Convex Stochastic Optimizations—0
GPU Accelerated Sub-Sampled Newton's Method—0
The Many Faces of Exponential Weights in Online Learning—0
A comparison of second-order methods for deep convolutional neural networks—0
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