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Second-order methods

Use second-order statistics to process data.

Papers

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Showing 151–175 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
Large Scale Empirical Risk Minimization via Truncated Adaptive Newton Method—0
Nestrov's Acceleration For Second Order Method—0
Biologically inspired protection of deep networks from adversarial attacks—0
Highly Efficient Hierarchical Online Nonlinear Regression Using Second Order Methods—0
Oracle Complexity of Second-Order Methods for Finite-Sum Problems—0
Stochastic Heavy Ball—0
Sub-sampled Newton Methods with Non-uniform Sampling—0
A Decentralized Quasi-Newton Method for Dual Formulations of Consensus Optimization—0
Second-Order Stochastic Optimization for Machine Learning in Linear TimeCode1
Stochastic Quasi-Newton Langevin Monte Carlo—0
Sub-Sampled Newton Methods II: Local Convergence Rates—0
Newton-Stein Method: A Second Order Method for GLMs via Stein's Lemma—0
Alternating direction method of multipliers for regularized multiclass support vector machines—0
Newton-Stein Method: An optimization method for GLMs via Stein's Lemma—0
Saddle-free Hessian-free Optimization—0
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