Regularized Matrix Factorization
Regularized Matrix Factorization is a matrix factorization method that incorporates penalty terms into the optimization objective to constrain model parameters, thereby reducing overfitting by explicitly differentiating it from standard matrix factorization techniques through the inclusion of regularization terms such as L2 or sparsity constraints.
383
Publications
32.6K
Citations
1.1K
Authors
426
Institutions
Publications per year
2017–2026
223
Parents
383
Weighted Nuclear Norm Minimization with Application to Image Denoising
Shuhang Gu, Lei Zhang, Wangmeng Zuo et al. · 2014 · 2.3K citations
Natural Sciences, Biomedical Engineering, Computer Vision +15
Recommender systems with social regularization
Hao Ma, Dengyong Zhou, Chao Liu et al. · 2011 · 1.7K citations
1–5 of 383
1.1K
8
h-index
7
h-index
6
h-index
6
h-index
University of Electronic Science and Technology of China, China
5 publications · 202 citations
5
h-index
1–5 of 1.1K
426

University of Electronic Science and Technology of China
Chengdu, China
16 h-index
39 publications
1.5K citations
Wuhan University
Wuhan, China
12 h-index
30 publications
5K citations

Zhejiang University
Hangzhou, China
12 h-index
27 publications
6.2K citations

Chinese Academy of Sciences
Beijing, China
11 h-index
26 publications
1.3K citations

Harbin Institute of Technology
Harbin, China
10 h-index
26 publications
5.4K citations

Xidian University
Xi'an, China
10 h-index
30 publications
3.7K citations
Qufu Normal University
Qufu, China
9 h-index
29 publications
1K citations
Guangdong University of Technology
Guangzhou, China
9 h-index
24 publications
1.7K citations
1–8 of 426
17 publications · 882 citations
16
h-index
Repository · 15 publications · 1K citations
13
h-index
10 publications · 723 citations
10
h-index
8 publications · 588 citations
8
h-index
8 publications · 1.5K citations
8
h-index
1–5