Cover Image

An Accelerated Newton-GMRES Method for Multilinear PageRank

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Boubekraoui, Maryam, Tahiri, Ridwane
Format:	Preprint
Published:	2025
Subjects:	Numerical Analysis Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

An Accelerated Newton‐GMRES Method for Multilinear PageRank
by: Maryam Boubekraoui, et al.
Published: (2026)

Multidimensional extrapolated global proximal gradient and applications for image processing
by: Bentbib, Abdeslem Hafid, et al.
Published: (2024)

Enhanced preprocessed multi-step splitting iterations for computing PageRank
by: Meng, Guangcong, et al.
Published: (2024)

Learning incomplete factorization preconditioners for GMRES
by: Häusner, Paul, et al.
Published: (2024)

Linking PageRank, Time Reversal, and Policy Evaluation
by: Avrachenkov, Konstantin, et al.
Published: (2026)

A Kernelizable Primal-Dual Formulation of the Multilinear Singular Value Decomposition
by: Wesel, Frederiek, et al.
Published: (2024)

Finding Koopman Invariant Subspaces via Personalized PageRank
by: Hong, Hyukpyo, et al.
Published: (2026)

Accuracy and componentwise accuracy in multilinear PageRank
by: Kalyani, Mehdi Najafi, et al.
Published: (2025)

Symmetric Rank-One Quasi-Newton Methods for Deep Learning Using Cubic Regularization
by: Ranganath, Aditya, et al.
Published: (2025)

Accelerating Power Method with Fast Sketching for Stronger Low-Rank Approximation
by: Chenakkod, Shabarish, et al.
Published: (2026)

Acceleration Methods
by: d'Aspremont, Alexandre, et al.
Published: (2021)

Online Covariance Matrix Estimation in Sketched Newton Methods
by: Kuang, Wei, et al.
Published: (2025)

Stabilizing randomized GMRES through flexible GMRES
by: Güttel, Stefan, et al.
Published: (2025)

Domain decomposition architectures and Gauss-Newton training for physics-informed neural networks
by: Heinlein, Alexander, et al.
Published: (2025)

Newton Informed Neural Operator for Computing Multiple Solutions of Nonlinear Partials Differential Equations
by: Hao, Wenrui, et al.
Published: (2024)

A fast neural hybrid Newton solver adapted to implicit methods for nonlinear dynamics
by: Jin, Tianyu, et al.
Published: (2024)

Preconditioning Low Rank Generalized Minimal Residual Method (GMRES) for Implicit Discretizations of Matrix Differential Equations
by: Meng, Shixu, et al.
Published: (2024)

Universal Approximation of Operators with Transformers and Neural Integral Operators
by: Zappala, Emanuele, et al.
Published: (2024)

Score Operator Newton transport
by: Chandramoorthy, Nisha, et al.
Published: (2023)

Dual-Domain Deep Learning Method to Accelerate Local Basis Functions Computation for Reservoir Simulation in High-Contrast Porous Media
by: Li, Peiqi, et al.
Published: (2025)

State-Dependent Lyapunov Method for Rank-1 Matrix Factorization
by: Moon, Jaehong
Published: (2026)

Sketching Low-Rank Plus Diagonal Matrices
by: Fernandez, Andres, et al.
Published: (2025)

Enforcing Katz and PageRank Centrality Measures in Complex Networks
by: Cipolla, Stefano, et al.
Published: (2024)

Random Subspace Cubic-Regularization Methods, with Applications to Low-Rank Functions
by: Cartis, Coralia, et al.
Published: (2025)

IFNSO: Iteration-Free Newton-Schulz Orthogonalization
by: Hu, Chen, et al.
Published: (2026)

Structured Variational $D$-Decomposition for Accurate and Stable Low-Rank Approximation
by: Katende, Ronald
Published: (2025)

Operator SVD with Neural Networks via Nested Low-Rank Approximation
by: Ryu, J. Jon, et al.
Published: (2024)

Nonconvex Approach for Sparse and Low-Rank Constrained Models with Dual Momentum
by: Wu, Cho-Ying, et al.
Published: (2019)

Accelerated Evolving Set Processes for Local PageRank Computation
by: Huang, Binbin, et al.
Published: (2025)

Streaming Krylov-Accelerated Stochastic Gradient Descent
by: Thomas, Stephen
Published: (2025)

Preconditioned Additive Gaussian Processes with Fourier Acceleration
by: Wagner, Theresa, et al.
Published: (2025)

Preconditioning for Accelerated Gradient Descent Optimization and Regularization
by: Ye, Qiang
Published: (2024)

An Augmented Backward-Corrected Projector Splitting Integrator for Dynamical Low-Rank Training
by: Kusch, Jonas, et al.
Published: (2025)

Dynamical Low-Rank Compression of Neural Networks with Robustness under Adversarial Attacks
by: Schotthöfer, Steffen, et al.
Published: (2025)

Cubic regularized subspace Newton for non-convex optimization
by: Zhao, Jim, et al.
Published: (2024)

Accelerating Fractional PINNs using Operational Matrices of Derivative
by: Taheri, Tayebeh, et al.
Published: (2024)

Number Theoretic Accelerated Learning of Physics-Informed Neural Networks
by: Matsubara, Takashi, et al.
Published: (2023)

Provable Emergence of Deep Neural Collapse and Low-Rank Bias in $L^2$-Regularized Nonlinear Networks
by: Zangrando, Emanuele, et al.
Published: (2024)

Accelerating Natural Gradient Descent for PINNs with Randomized Numerical Linear Algebra
by: Bioli, Ivan, et al.
Published: (2025)

A Microstructure-based Graph Neural Network for Accelerating Multiscale Simulations
by: Storm, J., et al.
Published: (2024)