Nick Vannieuwenhoven

Orcid: 0000-0001-5692-4163

According to our database1, Nick Vannieuwenhoven authored at least 29 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Approximating maps into manifolds with lower curvature bounds.
CoRR, 2024

2023
Group-Invariant Tensor Train Networks for Supervised Learning.
SIAM J. Math. Data Sci., December, 2023

The condition number of many tensor decompositions is invariant under Tucker compression.
Numer. Algorithms, October, 2023

Algorithm 1036: ATC, An Advanced Tucker Compression Library for Multidimensional Data.
ACM Trans. Math. Softw., June, 2023

The Average Condition Number of Most Tensor Rank Decomposition Problems is Infinite.
Found. Comput. Math., April, 2023

Hadamard-Hitchcock decompositions: identifiability and computation.
CoRR, 2023

What part of a numerical problem is ill-conditioned?
CoRR, 2023

2022
A Normal Form Algorithm for Tensor Rank Decomposition.
ACM Trans. Math. Softw., December, 2022

Sensitivity of low-rank matrix recovery.
Numerische Mathematik, 2022

Tensor completion using geodesics on Segre manifolds.
Numer. Linear Algebra Appl., 2022

The condition number of singular subspaces.
CoRR, 2022

2021
The Condition Number of Riemannian Approximation Problems.
SIAM J. Optim., 2021

Three decompositions of symmetric tensors have similar condition numbers.
CoRR, 2021

Relative-error stability of numerical algorithms.
CoRR, 2021

Algebraic compressed sensing.
CoRR, 2021

ATC: an Advanced Tucker Compression library for multidimensional data.
CoRR, 2021

Normal Forms for Tensor Rank Decomposition.
CoRR, 2021

2019
Pencil-Based Algorithms for Tensor Rank Decomposition are not Stable.
SIAM J. Matrix Anal. Appl., 2019

A theory of condition for unconstrained perturbations.
CoRR, 2019

Analyzing Soccer Players' Skill Ratings Over Time Using Tensor-Based Methods.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

2018
The Condition Number of Join Decompositions.
SIAM J. Matrix Anal. Appl., 2018

A Riemannian Trust Region Method for the Canonical Tensor Rank Approximation Problem.
SIAM J. Optim., 2018

Convergence analysis of Riemannian Gauss-Newton methods and its connection with the geometric condition number.
Appl. Math. Lett., 2018

2017
Effective Criteria for Specific Identifiability of Tensors and Forms.
SIAM J. Matrix Anal. Appl., 2017

2015
Computing the Gradient in Optimization Algorithms for the CP Decomposition in Constant Memory through Tensor Blocking.
SIAM J. Sci. Comput., 2015

2014
On Generic Nonexistence of the Schmidt-Eckart-Young Decomposition for Complex Tensors.
SIAM J. Matrix Anal. Appl., 2014

An Algorithm For Generic and Low-Rank Specific Identifiability of Complex Tensors.
SIAM J. Matrix Anal. Appl., 2014

2013
IMF: An Incomplete Multifrontal LU-Factorization for Element-Structured Sparse Linear Systems.
SIAM J. Sci. Comput., 2013

2012
A New Truncation Strategy for the Higher-Order Singular Value Decomposition.
SIAM J. Sci. Comput., 2012


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