Second-order Optimization
Second-Order Optimization is a gradient-based optimization method that employs second-order derivatives, specifically the Hessian matrix, to determine the curvature of the objective function and thereby achieve faster convergence compared to first-order methods.
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2017–2026
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Variants
Second-order Optimization Methods
784
Practical methods of optimization
Mathematics and Computers in Simulation · 1988 · 5.9K citations
Applications of second-order cone programming
Miguel Sousa Lobo, Lieven Vandenberghe, Stephen Boyd et al. · Linear Algebra and its Applications · 1998 · 2.4K citations
On the Implementation of a Primal-Dual Interior Point Method
Sanjay Mehrotra · SIAM Journal on Optimization · 1992 · 1.6K citations
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University of California, Berkeley
Berkeley, United States
16 h-index
28 publications
2.6K citations
Massachusetts Institute of Technology
Cambridge, United States
13 h-index
23 publications
1.7K citations
Stanford University
Stanford, United States
13 h-index
21 publications
7.9K citations
Princeton University
Princeton, United States
12 h-index
20 publications
3.5K citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
11 h-index
18 publications
2.1K citations

Rutherford Appleton Laboratory
Didcot, United Kingdom
10 h-index
11 publications
963 citations
UCLouvain
Louvain-la-Neuve, Belgium
10 h-index
13 publications
1.1K citations

University of Namur
Namur, Belgium
10 h-index
12 publications
1.5K citations
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57 publications · 5.8K citations
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46 publications · 2.7K citations
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Repository · 51 publications · 2.8K citations
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51 publications · 2.7K citations
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