Regularized Estimation
Regularized Estimation is a parameter estimation method that incorporates a penalty term into the estimation criterion to constrain model complexity and prevent overfitting by biasing estimates toward simpler solutions.
926
Publications
62.2K
Citations
1.9K
Authors
800
Institutions
Publications per year
2017–2026
257
926
Model selection and estimation in the Gaussian graphical model
Ming Yuan, Yi Lin · Biometrika · 2007 · 1.7K citations
Regularized estimation of large covariance matrices
Peter J. Bickel, Elizaveta Levina · 2006 · 1.3K citations
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800
Stanford University
Stanford, United States
23 h-index
59 publications
10K citations
University of California, Berkeley
Berkeley, United States
22 h-index
42 publications
9K citations

Centre National de la Recherche Scientifique
Paris, France
19 h-index
50 publications
2.6K citations
University of Michigan
Ann Arbor, United States
16 h-index
43 publications
6.8K citations
ETH Zurich
Zurich, Switzerland
13 h-index
26 publications
2.7K citations

Linköping University
Linköping, Sweden
13 h-index
22 publications
1.1K citations

University of Minnesota
Minneapolis, United States
13 h-index
34 publications
2.2K citations
University of Wisconsin–Madison
Madison, United States
12 h-index
15 publications
2.4K citations
1–8 of 800
Repository · 82 publications · 3.2K citations
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29 publications · 5.2K citations
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29 publications · 1.9K citations
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CSDA · 17 publications · 480 citations
14
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13 publications · 659 citations
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