D. Kressner

Publications156
h-index30
Citations3,360
Highly Influential Citations207
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Low-rank tensor completion by Riemannian optimization
In tensor completion, the goal is to fill in missing entries of a partially known tensor under a low-rank constraint. We propose a new algorithm that performs Riemannian optimization techniques on… Expand
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Low-Rank Tensor Krylov Subspace Methods for Parametrized Linear Systems
TLDR
Low-rank tensor variants of short-recurrence Krylov subspace methods are developed that benefit from the fact that x(\alpha) can be well approximated by a tensor of low rank. Expand
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A literature survey of low‐rank tensor approximation techniques
TLDR
A literature overview of low-rank tensor approximation, with an emphasis on function-related tensors. Expand
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Algorithm 941
TLDR
We present a Matlab toolbox, along with the underlying methodology and algorithms, which provides a convenient way to work with this format. Expand
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A block Newton method for nonlinear eigenvalue problems
  • D. Kressner
  • Mathematics, Computer Science
  • Numerische Mathematik
  • 13 November 2009
TLDR
We consider matrix eigenvalue problems that are nonlinear in the eigen value parameter. Expand
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Krylov Subspace Methods for Linear Systems with Tensor Product Structure
TLDR
The numerical solution of linear systems with certain tensor product structures is considered. Expand
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Learning Heat Diffusion Graphs
TLDR
In this paper, we propose to represent structured data as a sparse combination of localized functions that live on a graph that is a priori unknown. Expand
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Parallel algorithms for tensor completion in the CP format
TLDR
We propose novel, highly scalable algorithms based on a combination of the canonical polyadic (CP) tensor format with block coordinate descent methods. Expand
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  • 7
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Preconditioned Low-Rank Methods for High-Dimensional Elliptic PDE Eigenvalue Problems
TLDR
We use the hierarchical Tucker decomposition to develop a low-rank variant of LOBPCG, a classical preconditioned eigenvalue solver. Expand
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Accelerated filtering on graphs using Lanczos method
Signal-processing on graphs has developed into a very active field of research during the last decade. In particular, the number of applications using frames constructed from graphs, like wavelets on… Expand
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