A Riemannian rank-adaptive method for higher-order tensor completion in the tensor-train format
Fuente:
arXiv
Saved in:
| Main Authors: | Vermeylen, Charlotte, Van Barel, Marc |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Generalized cyclic symmetric decompositions for the matrix multiplication tensor
by: Vermeylen, Charlotte, et al.
Published: (2024)
by: Vermeylen, Charlotte, et al.
Published: (2024)
Second-order methods for quartically-regularised cubic polynomials, with applications to high-order tensor methods
by: Cartis, Coralia, et al.
Published: (2023)
by: Cartis, Coralia, et al.
Published: (2023)
Quasioptimal alternating projections and their use in low-rank approximation of matrices and tensors
by: Budzinskiy, Stanislav
Published: (2023)
by: Budzinskiy, Stanislav
Published: (2023)
Subspace power method for symmetric tensor decomposition
by: Kileel, Joe, et al.
Published: (2019)
by: Kileel, Joe, et al.
Published: (2019)
Natural Riemannian gradient for learning functional tensor networks
by: Klug, Nikolas, et al.
Published: (2026)
by: Klug, Nikolas, et al.
Published: (2026)
Tensor-based Dinkelbach method for computing generalized tensor eigenvalues and its applications
by: Chen, Haibin, et al.
Published: (2025)
by: Chen, Haibin, et al.
Published: (2025)
A two-phase rank-based algorithm for low-rank matrix completion
by: Araújo, Tacildo de Souza, et al.
Published: (2022)
by: Araújo, Tacildo de Souza, et al.
Published: (2022)
A Riemannian Rank‐Adaptive Method for Higher‐Order Tensor Completion in the Tensor‐Train Format
by: Charlotte Vermeylen, et al.
Published: (2024)
by: Charlotte Vermeylen, et al.
Published: (2024)
Riemannian optimization using three different metrics for Hermitian PSD fixed-rank constraints: an extended version
by: Zheng, Shixin, et al.
Published: (2022)
by: Zheng, Shixin, et al.
Published: (2022)
Gauss-Southwell type descent methods for low-rank matrix optimization
by: Olikier, Guillaume, et al.
Published: (2023)
by: Olikier, Guillaume, et al.
Published: (2023)
Comparison of two numerical methods for Riemannian cubic polynomials on Stiefel manifolds
by: Simoes, Alexandre Anahory, et al.
Published: (2024)
by: Simoes, Alexandre Anahory, et al.
Published: (2024)
An adaptive heavy ball method for ill-posed inverse problems
by: Jin, Qinian, et al.
Published: (2024)
by: Jin, Qinian, et al.
Published: (2024)
Rank Estimation for Third-Order Tensor Completion in the Tensor-Train Format
by: Vermeylen, Charlotte, et al.
Published: (2023)
by: Vermeylen, Charlotte, et al.
Published: (2023)
An accelerated gradient method with adaptive restart for convex multiobjective optimization problems
by: Luo, Hao, et al.
Published: (2025)
by: Luo, Hao, et al.
Published: (2025)
A thorough study of Riemannian Newton's Method
by: da Silva, Caio O., et al.
Published: (2025)
by: da Silva, Caio O., et al.
Published: (2025)
A unified high-resolution ODE framework for first-order methods
by: Wang, Lixia, et al.
Published: (2026)
by: Wang, Lixia, et al.
Published: (2026)
Riemannian Optimization and the Hartree-Fock Method
by: da Silva, Caio O.
Published: (2024)
by: da Silva, Caio O.
Published: (2024)
A multilevel stochastic regularized first-order method with application to finite sum minimization
by: Marini, Filippo, et al.
Published: (2024)
by: Marini, Filippo, et al.
Published: (2024)
Minimizing point configurations for tensor product energies on the torus
by: Bilyk, Dmitriy, et al.
Published: (2025)
by: Bilyk, Dmitriy, et al.
Published: (2025)
Fenchel Duality Theory and A Primal-Dual Algorithm on Riemannian Manifolds
by: Bergmann, Ronny, et al.
Published: (2019)
by: Bergmann, Ronny, et al.
Published: (2019)
Preconditioned iterative solvers for constrained high-order implicit shock tracking methods
by: Vandergrift, Jakob, et al.
Published: (2024)
by: Vandergrift, Jakob, et al.
Published: (2024)
First-order methods on bounded-rank tensors converging to stationary points
by: Gao, Bin, et al.
Published: (2025)
by: Gao, Bin, et al.
Published: (2025)
Inexact Newton Methods for Solving Generalized Equations on Riemannian Manifolds
by: Louzeiro, Mauricio S., et al.
Published: (2023)
by: Louzeiro, Mauricio S., et al.
Published: (2023)
Reduced order method based Anderson-type acceleration method for nonlinear least square problems and large scale ill-posed problems
by: Ito, Kazufumi, et al.
Published: (2025)
by: Ito, Kazufumi, et al.
Published: (2025)
Global Convergence and Error Propagation in Neural Gradient Flows: A Riemannian Optimization Framework
by: Zheng, Shixin, et al.
Published: (2026)
by: Zheng, Shixin, et al.
Published: (2026)
IRKA is a Riemannian Gradient Descent Method
by: Mlinarić, Petar, et al.
Published: (2023)
by: Mlinarić, Petar, et al.
Published: (2023)
RGNMR: A Gauss-Newton method for robust matrix completion with theoretical guarantees
by: Laufer, Eilon Vaknin, et al.
Published: (2025)
by: Laufer, Eilon Vaknin, et al.
Published: (2025)
Numerical analysis of a first-order computational algorithm for reaction-diffusion equations via the primal-dual hybrid gradient method
by: Liu, Shu, et al.
Published: (2024)
by: Liu, Shu, et al.
Published: (2024)
Variable projection framework for the reduced-rank matrix approximation problem by weighted least-squares
by: Terray, Pascal
Published: (2025)
by: Terray, Pascal
Published: (2025)
An adaptive importance sampling algorithm for risk-averse optimization
by: Pieraccini, Sandra, et al.
Published: (2025)
by: Pieraccini, Sandra, et al.
Published: (2025)
HOSCF: Efficient decoupling algorithms for finding the best rank-one approximation of higher-order tensors
by: Xiao, Chuanfu, et al.
Published: (2024)
by: Xiao, Chuanfu, et al.
Published: (2024)
Introduction to optimization methods for training SciML models
by: Kopaničáková, Alena, et al.
Published: (2026)
by: Kopaničáková, Alena, et al.
Published: (2026)
Optimization over bounded-rank matrices through a desingularization enables joint global and local guarantees
by: Rebjock, Quentin, et al.
Published: (2024)
by: Rebjock, Quentin, et al.
Published: (2024)
A reduced-order model for parametrized Optimal Transport problems
by: Bonnet-Weill, Elise, et al.
Published: (2026)
by: Bonnet-Weill, Elise, et al.
Published: (2026)
A preconditioned second-order convex splitting algorithm with extrapolation
by: Shen, Xinhua, et al.
Published: (2025)
by: Shen, Xinhua, et al.
Published: (2025)
A kernel-based method for Schrödinger bridges
by: Nakano, Yumiharu
Published: (2023)
by: Nakano, Yumiharu
Published: (2023)
The Riemannian Convex Bundle Method
by: Bergmann, Ronny, et al.
Published: (2024)
by: Bergmann, Ronny, et al.
Published: (2024)
Spiking Neural Networks: a theoretical framework for Universal Approximation and training
by: Biccari, Umberto
Published: (2025)
by: Biccari, Umberto
Published: (2025)
A boosted second-order convex splitting algorithm based on gradient flows
by: Shen, Xinhua, et al.
Published: (2024)
by: Shen, Xinhua, et al.
Published: (2024)
Tensor train based sampling algorithms for approximating regularized Wasserstein proximal operators
by: Han, Fuqun, et al.
Published: (2024)
by: Han, Fuqun, et al.
Published: (2024)
Similar Items
-
Generalized cyclic symmetric decompositions for the matrix multiplication tensor
by: Vermeylen, Charlotte, et al.
Published: (2024) -
Second-order methods for quartically-regularised cubic polynomials, with applications to high-order tensor methods
by: Cartis, Coralia, et al.
Published: (2023) -
Quasioptimal alternating projections and their use in low-rank approximation of matrices and tensors
by: Budzinskiy, Stanislav
Published: (2023) -
Subspace power method for symmetric tensor decomposition
by: Kileel, Joe, et al.
Published: (2019) -
Natural Riemannian gradient for learning functional tensor networks
by: Klug, Nikolas, et al.
Published: (2026)