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Second-order methods

Use second-order statistics to process data.

Papers

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Showing 26–50 of 181 papers

TitleStatusHype
Stochastic Newton Proximal Extragradient Method—0
Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks—0
A Gauss-Newton Approach for Min-Max Optimization in Generative Adversarial NetworksCode0
Inverse-Free Fast Natural Gradient Descent Method for Deep Learning—0
SGD with Partial Hessian for Deep Neural Networks OptimizationCode0
Second Order Methods for Bandit Optimization and Control—0
The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks—0
Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order PerspectiveCode1
On The Temporal Domain of Differential Equation Inspired Graph Neural Networks—0
Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate—0
Structured Inverse-Free Natural Gradient: Memory-Efficient & Numerically-Stable KFACCode1
Adapting Newton's Method to Neural Networks through a Summary of Higher-Order DerivativesCode0
Adaptive Optimization Algorithms for Machine Learning—0
A Computationally Efficient Sparsified Online Newton MethodCode0
AdaSub: Stochastic Optimization Using Second-Order Information in Low-Dimensional SubspacesCode0
Studying K-FAC Heuristics by Viewing Adam through a Second-Order LensCode0
Stochastic Optimization for Non-convex Problem with Inexact Hessian Matrix, Gradient, and Function—0
Jorge: Approximate Preconditioning for GPU-efficient Second-order Optimization—0
A Homogenization Approach for Gradient-Dominated Stochastic Optimization—0
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold—0
Convolutions and More as Einsum: A Tensor Network Perspective with Advances for Second-Order Methods—0
Near-Optimal Nonconvex-Strongly-Convex Bilevel Optimization with Fully First-Order Oracles—0
Error Feedback Can Accurately Compress PreconditionersCode0
MKOR: Momentum-Enabled Kronecker-Factor-Based Optimizer Using Rank-1 UpdatesCode1
Minibatching Offers Improved Generalization Performance for Second Order Optimizers—0
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