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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
Adaptive Optimization Algorithms for Machine Learning—0
Adaptive Second Order Coresets for Data-efficient Machine Learning—0
Adaptive Single-Pass Stochastic Gradient Descent in Input Sparsity Time—0
A Decentralized Quasi-Newton Method for Dual Formulations of Consensus Optimization—0
A Distributed Optimisation Framework Combining Natural Gradient with Hessian-Free for Discriminative Sequence Training—0
A Distributed Second-Order Algorithm You Can Trust—0
Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility—0
A Flexible Tensor Block Coordinate Ascent Scheme for Hypergraph Matching—0
A Generic Approach for Escaping Saddle points—0
Gram-Gauss-Newton Method: Learning Overparameterized Neural Networks for Regression Problems—0
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