Low-Rank Tensor Methods with Subspace Correction for Symmetric Eigenvalue Problems

2014 ◽  
Vol 36 (5) ◽  
pp. A2346-A2368 ◽  
Author(s):  
Daniel Kressner ◽  
Michael Steinlechner ◽  
André Uschmajew
Keyword(s):  
Eigenvalue Problems ◽  
Low Rank ◽  
Tensor Methods ◽  
Rank Tensor ◽  
Subspace Correction ◽  
Symmetric Eigenvalue Problems

scholarly journals Low rank tensor methods in Galerkin-based isogeometric analysis

2017 ◽  
Vol 316 ◽  
pp. 1062-1085 ◽  
Author(s):  
Angelos Mantzaflaris ◽  
Bert Jüttler ◽  
Boris N. Khoromskij ◽  
Ulrich Langer
Keyword(s):  
Isogeometric Analysis ◽  
Low Rank ◽  
Tensor Methods ◽  
Rank Tensor

Robust Low Transformed Multi-Rank Tensor Methods for Image Alignment

2021 ◽  
Vol 87 (1) ◽  
Author(s):  
Duo Qiu ◽  
Minru Bai ◽  
Michael K. Ng ◽  
Xiongjun Zhang
Keyword(s):  
Image Alignment ◽  
Tensor Methods ◽  
Rank Tensor

Low-Rank Tensor Graph Learning for Multi-view Subspace Clustering

2021 ◽  
pp. 1-1
Author(s):  
Yongyong Chen ◽  
Xiaolin Xiao ◽  
Chong Peng ◽  
Guangming Lu ◽  
Yicong Zhou
Keyword(s):  
Subspace Clustering ◽  
Low Rank ◽  
Graph Learning ◽  
Rank Tensor

TT-TSDF: Memory-Efficient TSDF with Low-Rank Tensor Train Decomposition

2020 ◽  
Author(s):  
Alexey I. Boyko ◽  
Mikhail P. Matrosov ◽  
Ivan V. Oseledets ◽  
Dzmitry Tsetserukou ◽  
Gonzalo Ferrer
Keyword(s):  
Low Rank ◽  
Rank Tensor ◽  
Memory Efficient
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