doi.org/10.1007/s10543-013-0454-0
Preview meta tags from the doi.org website.
Linked Hostnames
21- 32 links todoi.org
- 14 links toscholar.google.com
- 13 links tolink.springer.com
- 10 links towww.springernature.com
- 9 links towww.emis.de
- 8 links towww.ams.org
- 2 links tocitation-needed.springer.com
- 2 links toscholar.google.co.uk
Thumbnail

Search Engine Appearance
https://doi.org/10.1007/s10543-013-0454-0
A projector-splitting integrator for dynamical low-rank approximation - BIT Numerical Mathematics
The dynamical low-rank approximation of time-dependent matrices is a low-rank factorization updating technique. It leads to differential equations for fact
Bing
A projector-splitting integrator for dynamical low-rank approximation - BIT Numerical Mathematics
https://doi.org/10.1007/s10543-013-0454-0
The dynamical low-rank approximation of time-dependent matrices is a low-rank factorization updating technique. It leads to differential equations for fact
DuckDuckGo
A projector-splitting integrator for dynamical low-rank approximation - BIT Numerical Mathematics
The dynamical low-rank approximation of time-dependent matrices is a low-rank factorization updating technique. It leads to differential equations for fact
General Meta Tags
84- titleA projector-splitting integrator for dynamical low-rank approximation | BIT Numerical Mathematics
- charsetUTF-8
- X-UA-CompatibleIE=edge
- applicable-devicepc,mobile
- viewportwidth=device-width, initial-scale=1
Open Graph Meta Tags
6- og:urlhttps://link.springer.com/article/10.1007/s10543-013-0454-0
- og:typearticle
- og:site_nameSpringerLink
- og:titleA projector-splitting integrator for dynamical low-rank approximation - BIT Numerical Mathematics
- og:descriptionThe dynamical low-rank approximation of time-dependent matrices is a low-rank factorization updating technique. It leads to differential equations for factors of the matrices, which need to be solved numerically. We propose and analyze a fully explicit, computationally inexpensive integrator that is based on splitting the orthogonal projector onto the tangent space of the low-rank manifold. As is shown by theory and illustrated by numerical experiments, the integrator enjoys robustness properties that are not shared by any standard numerical integrator. This robustness can be exploited to change the rank adaptively. Another application is in optimization algorithms for low-rank matrices where truncation back to the given low rank can be done efficiently by applying a step of the integrator proposed here.
Twitter Meta Tags
6- twitter:site@SpringerLink
- twitter:cardsummary_large_image
- twitter:image:altContent cover image
- twitter:titleA projector-splitting integrator for dynamical low-rank approximation
- twitter:descriptionBIT Numerical Mathematics - The dynamical low-rank approximation of time-dependent matrices is a low-rank factorization updating technique. It leads to differential equations for factors of the...
Item Prop Meta Tags
3- position1
- position2
- position3
Link Tags
9- apple-touch-icon/oscar-static/img/favicons/darwin/apple-touch-icon-6ef0829b9c.png
- canonicalhttps://link.springer.com/article/10.1007/s10543-013-0454-0
- icon/oscar-static/img/favicons/darwin/android-chrome-192x192.png
- icon/oscar-static/img/favicons/darwin/favicon-32x32.png
- icon/oscar-static/img/favicons/darwin/favicon-16x16.png
Emails
1Links
105- http://scholar.google.com/scholar_lookup?&title=A%20new%20scheme%20for%20the%20tensor%20representation&journal=J.%20Fourier%20Anal.%20Appl.&doi=10.1007%2Fs00041-009-9094-9&volume=15&pages=706-722&publication_year=2009&author=Hackbusch%2CW.&author=K%C3%BChn%2CS.
- http://scholar.google.com/scholar_lookup?&title=Dynamical%20approximation%20of%20hierarchical%20Tucker%20and%20tensor-train%20tensors&journal=SIAM%20J.%20Matrix%20Anal.%20Appl.&doi=10.1137%2F120885723&volume=34&pages=470-494&publication_year=2013&author=Lubich%2CC.&author=Rohwedder%2CT.&author=Schneider%2CR.&author=Vandereycken%2CB.
- http://scholar.google.com/scholar_lookup?&title=Dynamical%20low-rank%20approximation%3A%20applications%20and%20numerical%20experiments&journal=Math.%20Comput.%20Simul.&doi=10.1016%2Fj.matcom.2008.03.007&volume=79&pages=1346-1357&publication_year=2008&author=Nonnenmacher%2CA.&author=Lubich%2CC.
- http://scholar.google.com/scholar_lookup?&title=Dynamical%20low-rank%20approximation&journal=SIAM%20J.%20Matrix%20Anal.%20Appl.&doi=10.1137%2F050639703&volume=29&pages=434-454&publication_year=2007&author=Koch%2CO.&author=Lubich%2CC.
- http://scholar.google.com/scholar_lookup?&title=Dynamical%20tensor%20approximation&journal=SIAM%20J.%20Matrix%20Anal.%20Appl.&doi=10.1137%2F09076578X&volume=31&pages=2360-2375&publication_year=2010&author=Koch%2CO.&author=Lubich%2CC.