Subspace Methods with Local Refinements for Eigenvalue Computation Using Low-Rank Tensor-Train Format

Journal of Scientific Computing ◽

10.1007/s10915-016-0255-0 ◽

2016 ◽

Vol 70 (2) ◽

pp. 478-499 ◽

Author(s):

Junyu Zhang ◽

Zaiwen Wen ◽

Yin Zhang

Keyword(s):

Low Rank ◽

Subspace Methods ◽

Eigenvalue Computation ◽

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Low-Rank Tensor Krylov Subspace Methods for Parametrized Linear Systems

SIAM Journal on Matrix Analysis and Applications ◽

10.1137/100799010 ◽

2011 ◽

Vol 32 (4) ◽

pp. 1288-1316 ◽

Author(s):

Daniel Kressner ◽

Christine Tobler

Keyword(s):

Linear Systems ◽

Krylov Subspace ◽

Krylov Subspace Methods ◽

Low Rank ◽

Subspace Methods ◽

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

IEEE Transactions on Circuits and Systems for Video Technology ◽

10.1109/tcsvt.2021.3055625 ◽

2021 ◽

pp. 1-1

Author(s):

Yongyong Chen ◽

Xiaolin Xiao ◽

Chong Peng ◽

Guangming Lu ◽

Yicong Zhou

Keyword(s):

Subspace Clustering ◽

Low Rank ◽

Graph Learning ◽

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An accurate prediction method of multiple deterioration forms of tool based on multitask learning with low rank tensor constraint

Journal of Manufacturing Systems ◽

10.1016/j.jmsy.2020.11.018 ◽

2021 ◽

Vol 58 ◽

pp. 193-204

Author(s):

Changqing Liu ◽

Jincheng Ni ◽

Peng Wan

Keyword(s):

Prediction Method ◽

Multitask Learning ◽

Accurate Prediction ◽

Low Rank ◽

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

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) ◽

10.1109/iros45743.2020.9341464 ◽

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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Adaptive Dimension-Discriminative Low-Rank Tensor Recovery for Computational Hyperspectral Imaging

International Journal of Computer Vision ◽

10.1007/s11263-021-01481-9 ◽

2021 ◽

Author(s):

Lizhi Wang ◽

Shipeng Zhang ◽

Hua Huang

Keyword(s):

Hyperspectral Imaging ◽

Low Rank ◽

Rank Tensor ◽

Tensor Recovery

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Low Rank Tensor Completion with Poisson Observations

IEEE Transactions on Pattern Analysis and Machine Intelligence ◽

10.1109/tpami.2021.3059299 ◽

2021 ◽

pp. 1-1

Author(s):

Xiongjun Zhang ◽

Michael Kwok-Po Ng

Keyword(s):

Low Rank ◽

Tensor Completion ◽

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Computation of low-rank tensor approximation under existence constraint via a forward-backward algorithm

Signal Processing ◽

10.1016/j.sigpro.2021.108178 ◽

2021 ◽

pp. 108178

Author(s):

Marouane Nazih ◽

Khalid Minaoui ◽

Elaheh Sobhani ◽

Pierre Comon

Keyword(s):

Low Rank ◽

Rank Tensor ◽

Tensor Approximation

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Low-rank tensor completion based on non-convex logDet function and Tucker decomposition

Signal Image and Video Processing ◽

10.1007/s11760-020-01845-7 ◽

2021 ◽

Author(s):

Chengfei Shi ◽

Zhengdong Huang ◽

Li Wan ◽

Tifan Xiong

Keyword(s):

Low Rank ◽

Tensor Completion ◽

Tucker Decomposition ◽

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Robust low-rank tensor completion via transformed tensor nuclear norm with total variation regularization

Neurocomputing ◽

10.1016/j.neucom.2020.12.110 ◽

2021 ◽

Vol 435 ◽

pp. 197-215

Author(s):

Duo Qiu ◽

Minru Bai ◽

Michael K. Ng ◽

Xiongjun Zhang

Keyword(s):

Total Variation ◽

Nuclear Norm ◽

Low Rank ◽

Total Variation Regularization ◽

Tensor Completion ◽

Rank Tensor ◽

Tensor Nuclear Norm

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Robust low-rank tensor reconstruction using high-order t-SVD

Journal of Electronic Imaging ◽

10.1117/1.jei.30.6.063016 ◽

2021 ◽

Vol 30 (06) ◽

Author(s):

Wenjin Qin ◽

Hailin Wang ◽

Feng Zhang ◽

Mingwei Dai ◽

Jianjun Wang

Keyword(s):

Low Rank ◽

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