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Second-order methods

Use second-order statistics to process data.

Papers

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Showing 51–75 of 181 papers

TitleStatusHype
Curvature-corrected learning dynamics in deep neural networks—0
Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training—0
Debiasing Distributed Second Order Optimization with Surrogate Sketching and Scaled Regularization—0
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold—0
A scaled gradient projection method for Bayesian learning in dynamical systems—0
DDPNOpt: Differential Dynamic Programming Neural Optimizer—0
A Homogenization Approach for Gradient-Dominated Stochastic Optimization—0
Distributed Quasi-Newton Method for Fair and Fast Federated Learning—0
Distributed Second Order Methods with Fast Rates and Compressed Communication—0
Don't Be So Positive: Negative Step Sizes in Second-Order Methods—0
Doubly Adaptive Scaled Algorithm for Machine Learning Using Second-Order Information—0
Approximate Newton Methods and Their Local Convergence—0
Adaptive Second Order Coresets for Data-efficient Machine Learning—0
A comparison of second-order methods for deep convolutional neural networks—0
Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods—0
First and Second Order Methods for Online Convolutional Dictionary Learning—0
Explicit Second-Order Min-Max Optimization Methods with Optimal Convergence Guarantee—0
A Newton-CG based barrier method for finding a second-order stationary point of nonconvex conic optimization with complexity guarantees—0
Adaptive Optimization Algorithms for Machine Learning—0
A Novel Fast Exact Subproblem Solver for Stochastic Quasi-Newton Cubic Regularized Optimization—0
Faster Differentially Private Convex Optimization via Second-Order Methods—0
FedNL: Making Newton-Type Methods Applicable to Federated Learning—0
FedOSAA: Improving Federated Learning with One-Step Anderson Acceleration—0
Fed-Sophia: A Communication-Efficient Second-Order Federated Learning Algorithm—0
GP-FL: Model-Based Hessian Estimation for Second-Order Over-the-Air Federated Learning—0
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