Zobrazeno 1 - 10
of 151
pro vyhledávání: '"Lieven De Lathauwer"'
Autor:
Stijn Hendrikx, Lieven De Lathauwer
Publikováno v:
Frontiers in Applied Mathematics and Statistics, Vol 8 (2022)
Several problems in compressed sensing and randomized tensor decomposition can be formulated as a structured linear system with a constrained tensor as the solution. In particular, we consider block row Kronecker-structured linear systems with a low
Externí odkaz:
https://doaj.org/article/41991d44d3f847e5beaf55f48be2134f
Autor:
Muzaffer Ayvaz, Lieven De Lathauwer
Publikováno v:
Frontiers in Applied Mathematics and Statistics, Vol 8 (2022)
We introduce the Tensor-Based Multivariate Optimization (TeMPO) framework for use in nonlinear optimization problems commonly encountered in signal processing, machine learning, and artificial intelligence. Within our framework, we model nonlinear re
Externí odkaz:
https://doaj.org/article/1984d372cd5f48d88b8e26eb5f9b7b07
Publikováno v:
Frontiers in Big Data, Vol 5 (2022)
We introduce a supervised learning framework for target functions that are well approximated by a sum of (few) separable terms. The framework proposes to approximate each component function by a B-spline, resulting in an approximant where the underly
Externí odkaz:
https://doaj.org/article/cf1916e2c0744377ba5d97370d072fcc
Autor:
Katrijn Van Deun, Iven Van Mechelen, Lieven Thorrez, Martijn Schouteden, Bart De Moor, Mariët J van der Werf, Lieven De Lathauwer, Age K Smilde, Henk A L Kiers
Publikováno v:
PLoS ONE, Vol 7, Iss 5, p e37840 (2012)
BACKGROUND: In systems biology it is common to obtain for the same set of biological entities information from multiple sources. Examples include expression data for the same set of orthologous genes screened in different organisms and data on the sa
Externí odkaz:
https://doaj.org/article/89e4d78e52694422b57f7b1cf519b971
Publikováno v:
IEEE Transactions on Signal Processing. 71:1712-1724
Nonnegative Matrix Factorization (NMF) models are widely used to recover linearly mixed nonnegative data. When the data is made of samplings of continuous signals, the factors in NMF can be constrained to be samples of nonnegative rational functions,
Publikováno v:
SIAM Journal on Matrix Analysis and Applications. 43:912-938
ispartof: Siam Journal On Matrix Analysis And Applications vol:43 issue:2 pages:912-938 status: published
Publikováno v:
SIAM Journal on Matrix Analysis and Applications. 43:274-300
The canonical polyadic decomposition (CPD) is a compact decomposition which expresses a tensor as a sum of its rank-1 components. A common step in the computation of a CPD is computing a generalized eigenvalue decomposition (GEVD) of the tensor. A GE
Publikováno v:
IEEE Transactions on Signal Processing. 70:3551-3565
Publikováno v:
Calphad
CALPHAD-COMPUTER COUPLING OF PHASE DIAGRAMS AND THERMOCHEMISTRY
Ghent University Academic Bibliography
CALPHAD-COMPUTER COUPLING OF PHASE DIAGRAMS AND THERMOCHEMISTRY
Ghent University Academic Bibliography
High temperature oxidic systems are encountered in nature (magma chambers) and pyrometallurgical processes. In these systems, the solidification of the oxidic liquids influences the flow, the cooling after tapping, the viscosity and rheological behav
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b284363cba7367a4c105a6e0eab4e00
https://lirias.kuleuven.be/handle/20.500.12942/695081
https://lirias.kuleuven.be/handle/20.500.12942/695081
Publikováno v:
SIAM Journal on Matrix Analysis and Applications. 42:913-953