Robust Matrix Factorization is a matrix factorization method that explicitly models and mitigates the influence of outliers or gross corruptions in the observed data by incorporating sparse error regularization within the decomposition process.
291
Publications
16.7K
Citations
762
Authors
355
Institutions
Publications per year
2017–2026
138
Parents
Publications
291
Novel Methods for Multilinear Data Completion and De-noising Based on Tensor-SVD
Zemin Zhang, Gregory Ely, Shuchin Aeron et al. · 2014 · 786 citations
Yu‐Ru Lin, Yün Chi, Shenghuo Zhu et al. · 2008 · 409 citations
Robust nonnegative matrix factorization using L21-norm
Deguang Kong, Chris Ding, Heng Huang · 2011 · 331 citations
1–5 of 291
Authors
762
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- ZL
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- HH
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- CD
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1–5 of 762
Institutions
355
Chinese Academy of Sciences
Beijing, China
11 h-index
23 publications
1.4K citations
Xi'an Jiaotong University
Xi'an, China
11 h-index
24 publications
1.8K citations
National University of Singapore
Singapore, Singapore
10 h-index
16 publications
859 citations
University of Minnesota
Minneapolis, United States
10 h-index
19 publications
810 citations
Tsinghua University
Beijing, China
8 h-index
13 publications
335 citations
Hong Kong Polytechnic University
Hong Kong, Hong Kong
8 h-index
12 publications
873 citations
The University of Texas at Arlington
Arlington, United States
8 h-index
19 publications
2.5K citations
National University of Defense Technology
Changsha, China
7 h-index
18 publications
1.1K citations
1–8 of 355
Venues
- arXiv (Cornell University)
Repository · 20 publications · 599 citations
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- IEEE Transactions on Signal Processing
10 publications · 446 citations
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- Information Sciences
9 publications · 601 citations
9
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- Knowledge-Based Systems
7 publications · 317 citations
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- IEEE Transactions on Pattern Analysis and Machine Intelligence
TPAMI · 7 publications · 862 citations
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