Performance guarantees of transformed Schatten-1 regularization for exact low-rank matrix recovery

International Journal of Machine Learning and Cybernetics ◽

10.1007/s13042-021-01361-1 ◽

2021 ◽

Author(s):

Zhi Wang ◽

Dong Hu ◽

Xiaohu Luo ◽

Wendong Wang ◽

Jianjun Wang ◽

...

Keyword(s):

Low Rank ◽

Matrix Recovery ◽

Performance Guarantees ◽

Rank Matrix ◽

Low Rank Matrix Recovery ◽

Low Rank Matrix

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Lunar Hyperspectral Image Destriping Method Using Low-Rank Matrix Recovery and Guided Profile

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss39084.2020.9323799 ◽

2020 ◽

Author(s):

Shuheng Zhao ◽

Qiangqiang Yuan ◽

Jie Li ◽

Huanfeng Shen ◽

Liangpei Zhang

Keyword(s):

Hyperspectral Image ◽

Low Rank ◽

Matrix Recovery ◽

Rank Matrix ◽

Low Rank Matrix Recovery ◽

Low Rank Matrix

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Low-Rank Matrix Recovery with Composite Optimization: Good Conditioning and Rapid Convergence

Foundations of Computational Mathematics ◽

10.1007/s10208-020-09490-9 ◽

2021 ◽

Author(s):

Vasileios Charisopoulos ◽

Yudong Chen ◽

Damek Davis ◽

Mateo Díaz ◽

Lijun Ding ◽

...

Keyword(s):

Low Rank ◽

Rapid Convergence ◽

Composite Optimization ◽

Matrix Recovery ◽

Rank Matrix ◽

Low Rank Matrix Recovery ◽

Low Rank Matrix ◽

Good Conditioning

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Modal-Regression-Based Structured Low-Rank Matrix Recovery for Multiview Learning

IEEE Transactions on Neural Networks and Learning Systems ◽

10.1109/tnnls.2020.2980960 ◽

2020 ◽

pp. 1-13

Author(s):

Jiamiao Xu ◽

Fangzhao Wang ◽

Qinmu Peng ◽

Xinge You ◽

Shuo Wang ◽

...

Keyword(s):

Low Rank ◽

Matrix Recovery ◽

Multiview Learning ◽

Rank Matrix ◽

Modal Regression ◽

Low Rank Matrix Recovery ◽

Low Rank Matrix

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Localizing scene texts by fuzzy inference systems and low rank matrix recovery model

Computer Vision and Image Understanding ◽

10.1016/j.cviu.2015.10.002 ◽

2016 ◽

Vol 142 ◽

pp. 94-110 ◽

Author(s):

Shaho Ghanei ◽

Karim Faez

Keyword(s):

Fuzzy Inference ◽

Low Rank ◽

Fuzzy Inference Systems ◽

Recovery Model ◽

Matrix Recovery ◽

Rank Matrix ◽

Inference Systems ◽

Low Rank Matrix Recovery ◽

Low Rank Matrix

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A Hyperspectral Image Denoising Approach via Low-Rank Matrix Recovery and Greedy Bilateral

10.1109/rivf51545.2021.9642145 ◽

2021 ◽

Author(s):

Anh Tuan Vuong ◽

Van Ha Tang ◽

Long Thanh Ngo

Keyword(s):

Image Denoising ◽

Hyperspectral Image ◽

Low Rank ◽

Matrix Recovery ◽

Rank Matrix ◽

Low Rank Matrix Recovery ◽

Low Rank Matrix

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Low-Rank Matrix Recovery With Simultaneous Presence of Outliers and Sparse Corruption

IEEE Journal of Selected Topics in Signal Processing ◽

10.1109/jstsp.2018.2876604 ◽

2018 ◽

Vol 12 (6) ◽

pp. 1170-1181

Author(s):

Mostafa Rahmani ◽

George K. Atia

Keyword(s):

Low Rank ◽

Simultaneous Presence ◽

Matrix Recovery ◽

Rank Matrix ◽

Low Rank Matrix Recovery ◽

Low Rank Matrix

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Robust Multi-view Subspace Learning Through Structured Low-Rank Matrix Recovery

Pattern Recognition and Computer Vision - Lecture Notes in Computer Science ◽

10.1007/978-3-030-03338-5_36 ◽

2018 ◽

pp. 427-439

Author(s):

Jiamiao Xu ◽

Xinge You ◽

Qi Zheng ◽

Fangzhao Wang ◽

Peng Zhang

Keyword(s):

Subspace Learning ◽

Low Rank ◽

Matrix Recovery ◽

Rank Matrix ◽

Low Rank Matrix Recovery ◽

Low Rank Matrix

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Low-rank Matrix Recovery via Iteratively Reweighted Least Squares Minimization

SIAM Journal on Optimization ◽

10.1137/100811404 ◽

2011 ◽

Vol 21 (4) ◽

pp. 1614-1640 ◽

Author(s):

Massimo Fornasier ◽

Holger Rauhut ◽

Rachel Ward

Keyword(s):

Least Squares ◽

Low Rank ◽

Iteratively Reweighted Least Squares ◽

Matrix Recovery ◽

Rank Matrix ◽

Low Rank Matrix Recovery ◽

Low Rank Matrix ◽

Least Squares Minimization

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Design strategy of thresholding operator for low-rank matrix recovery problem

Signal Processing ◽

10.1016/j.sigpro.2020.107510 ◽

2020 ◽

Vol 171 ◽

pp. 107510 ◽

Author(s):

Fujun Zhao ◽

Jigen Peng ◽

Angang Cui

Keyword(s):

Design Strategy ◽

Low Rank ◽

Matrix Recovery ◽

Rank Matrix ◽

Low Rank Matrix Recovery ◽

Low Rank Matrix ◽

Recovery Problem

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From co-saliency detection to object co-segmentation: A unified multi-stage low-rank matrix recovery approach

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO) ◽

10.1109/robio.2015.7419000 ◽

2015 ◽

Author(s):

Hao Chen ◽

Panbing Wang ◽

Ming Liu

Keyword(s):

Saliency Detection ◽

Low Rank ◽

Matrix Recovery ◽

Multi Stage ◽

Rank Matrix ◽

Low Rank Matrix Recovery ◽

Low Rank Matrix ◽

Recovery Approach

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