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Daniel Kressner

Publications associées (130)

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MATHICSE Technical Report : A novel iterative method to approximate structured singular values

Daniel Kressner

A novel method for approximating structured singular values (also known as

\mu

- values) is proposed and investigated. These quantities constitute an important tool in the stability analysis of uncertain linear control systems as well as in structured eig ...

MATHICSE2016

Daniel Kressner

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Projection Methods For Large-Scale T-Sylvester Equations

MATHICSE Technical Report : A novel iterative method to approximate structured singular values

MATHICSE Technical Report : Fast computation of the matrix exponential for a Toeplitz matrix

MATHICSE Technical Report : Structure-preserving low multilinear rank approximation of antisymmetric tensors

MATHICSE Technical Report : Perturbation of higher-order singular values

Low-rank tensor approximation for high-order correlation functions of Gaussian random fields

MATHICSE Technical Report : Preconditioned low-rank Riemannian optimization for linear systems with tensor product structure

Truncated low-rank methods for solving general linear matrix equations

MATHICSE Technical Report : Subspace acceleration for large-scale parameter-dependent Hermitian eigenproblems

MATHICSE Technical Report: Reduced basis methods: from low-rank matrices to low-rank tensor

MATHICSE Technical Report : Fast computation of the matrix exponential for a Toeplitz matrix

MATHICSE Technical Report : A novel iterative method to approximate structured singular values

Low-rank tensor approximation for high-order correlation functions of Gaussian random fields

Truncated low-rank methods for solving general linear matrix equations

MATHICSE Technical Report : Subspace acceleration for large-scale parameter-dependent Hermitian eigenproblems

MATHICSE Technical Report : Structure-preserving low multilinear rank approximation of antisymmetric tensors

MATHICSE Technical Report : Perturbation of higher-order singular values

MATHICSE Technical Report : Preconditioned low-rank Riemannian optimization for linear systems with tensor product structure

Projection Methods For Large-Scale T-Sylvester Equations

MATHICSE Technical Report: Reduced basis methods: from low-rank matrices to low-rank tensor