Finding a low-rank basis in a matrix subspace

Finding a low-rank basis in a matrix subspace

For a given matrix subspace, how can we find a basis that consists of low-rank matrices? This is a generalization of the sparse vector problem. It turns out that when the subspace is spanned by rank-1 matrices, the matrices can be obtained by the tensor CP decomposition. For the higher rank case, th...

Deskribapen osoa

Xehetasun bibliografikoak
Egile Nagusiak:	Nakatsukasa, Y, Soma, T, Uschmajew, A
Formatua:	Journal article
Hizkuntza:	English
Argitaratua:	Springer Verlag 2016

Antzeko izenburuak

On orthogonal tensors and best rank-one approximation ratio
nork: Li, Z, et al.
Argitaratua: (2018)

Low-rank matrix approximations over canonical subspaces
nork: Achiya Dax
Argitaratua: (2020-09-01)

Low-rank matrix approximations over canonical subspaces
nork: Achiya Dax
Argitaratua: (2020-09-01)

Low-rank matrix approximations over canonical subspaces
nork: Achiya Dax
Argitaratua: (2020-09-01)

Low-rank matrix approximations over canonical subspaces
nork: Achiya Dax
Argitaratua: (2020-09-01)

Continual learning in low-rank orthogonal subspaces
nork: Chaudhry, A, et al.
Argitaratua: (2020)

A theory of quantum subspace diagonalization
nork: Epperly, EN, et al.
Argitaratua: (2022)

Low-rank sparse subspace clustering with a clean dictionary
nork: Cong-Zhe You, et al.
Argitaratua: (2021-01-01)

Fast randomized numerical rank estimation for numerically low-rank matrices
nork: Meier, M, et al.
Argitaratua: (2024)

Subspace Segmentation by Low Rank Representation via the Sparse-Prompting Quasi-Rank Function
nork: Haiyang Li, et al.
Argitaratua: (2022-01-01)

Subspace-constrained approaches to low-rank fMRI acceleration
nork: Mason, HT, et al.
Argitaratua: (2021)

Intra-class Low-Rank Subspace Learning for Face Recognition
nork: CAI Yuhong, WU Xiaojun
Argitaratua: (2022-12-01)

WITHDRAWN–Low-rank sparse subspace clustering with a clean dictionary
nork: Cong-Zhe You, et al.
Argitaratua: (2021-03-01)

Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling: A Subspace Approach to Improved MRF Reconstruction
nork: Zhao, Bo, et al.
Argitaratua: (2021)

Simultaneous multislice magnetic resonance fingerprinting with low-rank and subspace modeling
nork: Zhao, Bo, et al.
Argitaratua: (2020)

Subspace-constrained approaches to low-rank fMRI acceleration datasets
nork: Mason, H
Argitaratua: (2020)

Exploring subspace-constrained approaches to low-rank fMRI acceleration
nork: Mason, HT
Argitaratua: (2020)

Unified Low-Rank Subspace Clustering with Dynamic Hypergraph for Hyperspectral Image
nork: Jinhuan Xu, et al.
Argitaratua: (2021-04-01)

Weighted Low-Rank Tensor Representation for Multi-View Subspace Clustering
nork: Shuqin Wang, et al.
Argitaratua: (2021-01-01)

Low-rank approximation of parameter-dependent matrices via CUR decomposition
nork: Park, T, et al.
Argitaratua: (2025)

Some insights into rank conditions of vector subspaces
nork: Zoran Z. Petrović, et al.
Argitaratua: (2024-08-01)

Efficient bounds and estimates for canonical angles in randomized subspace approximations
nork: Dong, Y, et al.
Argitaratua: (2024)

Low-Rank Methods in Event Detection With Subsampled Point-to-Subspace Proximity Tests
nork: Jakub Marecek, et al.
Argitaratua: (2022-01-01)

Fast Superpixel Based Subspace Low Rank Learning Method for Hyperspectral Denoising
nork: Le Sun, et al.
Argitaratua: (2018-01-01)

Randomized low-rank approximation for symmetric indefinite matrice
nork: Taejun, P, et al.
Argitaratua: (2023)

WITHDRAWAL – Administrative Duplicate Publication: Low-rank sparse subspace clustering with a clean dictionary
Argitaratua: (2021-03-01)

Hyperspectral anomaly detection via low-rank and sparse decomposition with cluster subspace accumulation
nork: Baozhi Cheng, et al.
Argitaratua: (2024-11-01)

Sample Latent Feature-Associated Low-Rank Subspace Clustering for Hyperspectral Band Selection
nork: Yujie Guo, et al.
Argitaratua: (2024-01-01)

Discriminant Subspace Low-Rank Representation Algorithm for Electroencephalography-Based Alzheimer’s Disease Recognition
nork: Tusheng Tang, et al.
Argitaratua: (2022-06-01)

Non-Convex Sparse and Low-Rank Based Robust Subspace Segmentation for Data Mining
nork: Wenlong Cheng, et al.
Argitaratua: (2017-07-01)

Identifying subspace gene clusters from microarray data using low-rank representation.
nork: Yan Cui, et al.
Argitaratua: (2013-01-01)

Sparse Signal Recovery from Fixed Low-Rank Subspace via Compressive Measurement
nork: Jun He, et al.
Argitaratua: (2013-12-01)

Reduced-Rank Adaptive Filtering Using Krylov Subspace
nork: Burykh Sergueï, et al.
Argitaratua: (2002-01-01)

Robust Subspace Discovery via Relaxed Rank Minimization
nork: Wang, Xinggang, et al.
Argitaratua: (2014)

Speeding up Krylov subspace methods for computing f(A)b via randomization
nork: Cortinovis, A, et al.
Argitaratua: (2024)

Chordal decomposition in rank minimized semidefinite programs with applications to subspace clustering
nork: Miller, J, et al.
Argitaratua: (2020)

Low rank matrix completion
nork: Nan, Feng, S.M. Massachusetts Institute of Technology
Argitaratua: (2010)

Spatiotemporal traffic data imputation by synergizing low tensor ring rank and nonlocal subspace regularization
nork: Peng‐Ling Wu, et al.
Argitaratua: (2023-09-01)

Low-Rank Subspace Learning of Multikernel Based on Weighted Truncated Nuclear Norm for Image Segmentation
nork: Li Li, et al.
Argitaratua: (2022-01-01)

Generalized gene co-expression analysis via subspace clustering using low-rank representation
nork: Tongxin Wang, et al.
Argitaratua: (2019-05-01)