L-bfgs Optimization
L-BFGS Optimization is a limited-memory quasi-Newton method for numerical optimization that approximates the Broyden–Fletcher–Goldfarb–Shanno algorithm using a reduced set of past iterations to efficiently minimize smooth functions in high-dimensional spaces.
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2017–2026
52
Variants
Limited-memory BfgsLimited-memory Broyden–fletcher–goldfarb–shanno Algorithm
Parents
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Ciyou Zhu, Richard H. Byrd, Peihuang Lu et al. · ACM Transactions on Mathematical Software · 1997 · 3.4K citations · Full text
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Northwestern University
Evanston, United States
5 h-index
8 publications
11.1K citations
Florida State University
Tallahassee, United States
3 h-index
3 publications
67 citations

University of Manchester
Manchester, United Kingdom
3 h-index
5 publications
115 citations
University of Patras
Pátrai, Greece
3 h-index
4 publications
143 citations

Pennsylvania State University
State College, United States
2 h-index
4 publications
46 citations
Karlsruhe Institute of Technology
Karlsruhe, Germany
2 h-index
4 publications
222 citations

Oklahoma State University
Stillwater, United States
2 h-index
2 publications
23 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
6 publications
209 citations
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Repository · 6 publications · 290 citations
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6 publications · 2.1K citations
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TOMS · 3 publications · 3.9K citations
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Conference · 2 publications · 963 citations
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