Large-Scale Quadratic Programming is a specialized form of quadratic programming characterized by optimization problems involving a large number of variables and/or constraints, where computational efficiency and memory management necessitate tailored algorithms and solution techniques distinct from those used in small- or medium-scale problems.
99
Publications
11K
Citations
230
Authors
104
Institutions
Publications per year
2017–2026
12
Parents
Publications
99
Making Large-Scale SVM Learning Practical
Thorsten Joachims · Technical reports · 2006 · 4.3K citations · Full text
Large-Scale Portfolio Optimization
André F. Perold · Management Science · 1984 · 425 citations
1–5 of 99
Authors
230
- LT
5
h-index
- LZ
4
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- JWJon W. Tolle
University of North Carolina at Chapel Hill, United States
3 publications · 393 citations
3
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- SA
3
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- JB
3
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1–5 of 230
Institutions
104
University of Ferrara
Ferrara, Italy
5 h-index
6 publications
446 citations
Carnegie Mellon University
Pittsburgh, United States
5 h-index
9 publications
594 citations
ETH Zurich
Zurich, Switzerland
4 h-index
6 publications
227 citations
University of Minnesota
Minneapolis, United States
4 h-index
6 publications
392 citations
Stanford University
Stanford, United States
4 h-index
10 publications
273 citations
University of Modena and Reggio Emilia
Modena, Italy
4 h-index
6 publications
490 citations
Rutherford Appleton Laboratory
Didcot, United Kingdom
3 h-index
3 publications
295 citations
University of Iowa
Iowa City, United States
3 h-index
6 publications
700 citations
1–8 of 104
Venues
- SIAM Journal on Optimization
8 publications · 1.4K citations
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- Optimization methods & software
6 publications · 276 citations
6
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- Mathematical Programming
4 publications · 471 citations
4
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- ACM Transactions on Mathematical Software
TOMS · 4 publications · 300 citations
4
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- Journal of Optimization Theory and Applications
3 publications · 67 citations
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1–5