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001     957675
005     20260306144849.0
024 7 _ |2 arXiv
|a arXiv:1910.07052
024 7 _ |2 DOI
|a 10.48550/ARXIV.1910.07052
037 _ _ |a RWTH-2023-04916
041 _ _ |a English
100 1 _ |0 P:(DE-82)IDM00424
|a Bachmayr, Markus
|b 0
245 _ _ |a Adaptive Low-Rank Approximations for Operator Equations: Accuracy Control and Computational Complexity
|h online
260 _ _ |c 2019
336 7 _ |0 28
|2 EndNote
|a Electronic Article
336 7 _ |0 PUB:(DE-HGF)25
|2 PUB:(DE-HGF)
|a Preprint
|b preprint
|m preprint
|s 1683121794_9360
336 7 _ |2 BibTeX
|a ARTICLE
336 7 _ |2 DRIVER
|a preprint
336 7 _ |2 DataCite
|a Output Types/Working Paper
336 7 _ |2 ORCID
|a WORKING_PAPER
588 _ _ |a Dataset connected to arXivarXiv
591 _ _ |a Germany
653 _ 7 |a Nonlinear approximation, Tensor formats, low-rank approximation, hard and soft thresholding, high-dimensional diffusion equations, parametric PDEs, approximation classes, a posteriori error bounds, convergence and complexity
700 1 _ |a Dahmen, Wolfgang
|b 1
914 1 _ |y 2019
980 1 _ |a EXTERN4VITA
980 _ _ |a I:(DE-82)110000_20140620
980 _ _ |a I:(DE-82)111410_20170801
980 _ _ |a UNRESTRICTED
980 _ _ |a preprint


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21