LBFGS-B

Algorithm 778: L-BFGS-B Fortran subroutines for large-scale bound-constrained optimization L-BFGS-B is a limited-memory algorithm for solving large nonlinear optimization problems subject to simple bounds on the variables. It is intended for problems in which information on the Hessian matrix is difficult to obtain, or for large dense problems. L-BFGS-B can also be used for unconstrained problems and in this case performs similarly to its predecessor, algorithm L-BFGS (Harwell routine VA15). The algorithm is implemened in Fortran 77. (Source: http://plato.asu.edu)


References in zbMATH (referenced in 293 articles , 1 standard article )

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  1. Fischbacher, Thomas: The many vacua of gauged extended supergravities (2009)
  2. Groenwold, Albert A.; Etman, L. F. P.; Kok, Schalk; Wood, Derren W.; Tosserams, Simon: An augmented Lagrangian approach to non-convex SAO using diagonal quadratic approximations (2009) ioport
  3. Lim, Yong B.; Park, Yeo Jung; Huh, Myung-Hoe: D-optimality criterion for weighting variables in K-means clustering (2009)
  4. Sainvitu, Caroline: How much do approximate derivatives hurt filter methods? (2009)
  5. Schwarz, Roland; Wolf, Matthias; Müller, Tobias: A probabilistic model of cell size reduction in \textitPseudo-nitzschia delicatissima (Bacillariophyta) (2009)
  6. Srinath, D. N.; Mittal, S.: Optimal airfoil shapes for low Reynolds number flows (2009)
  7. Sun, Li; He, Guoping; Wang, Yongli; Fang, Liang: An active set quasi-Newton method with projected search for bound constrained minimization (2009)
  8. Wood, Derren W.; Groenwold, Albert A.: Non-convex dual forms based on exponential intervening variables, with application to weight minimization (2009)
  9. Birgin, E. G.; Martínez, J. M.: Structured minimal-memory inexact quasi-Newton method and secant preconditioners for augmented Lagrangian optimization (2008)
  10. Carmichael, Gregory R.; Sandu, Adrian; Chai, Tianfeng; Daescu, Dacian N.; Constantinescu, Emil M.; Tang, Youhua: Predicting air quality: Improvements through advanced methods to integrate models and measurements (2008)
  11. Chen, Jein-Shan; Pan, Shaohua: A descent method for a reformulation of the second-order cone complementarity problem (2008)
  12. El Serafy, G. Y.; Heemink, A. W.; van Geer, F. C.: Identification of ground water flow patterns using particle models (2008)
  13. Eydinov, Dmitry; Aanonsen, Sigurd Ivar; Haukås, Jarle; Aavatsmark, Ivar: A method for automatic history matching of a compositional reservoir simulator with multipoint flux approximation (2008)
  14. Groenwold, Albert A.; Etman, L. F. P.: Sequential approximate optimization using dual subproblems based on incomplete series expansions (2008)
  15. Li, Yiming; Yu, Shao-Ming; Li, Yih-Lang: Electronic design automation using a unified optimization framework (2008)
  16. Ma, Lin; Klug, William S.: Viscous regularization and r-adaptive remeshing for finite element analysis of lipid membrane mechanics (2008)
  17. Sandu, Adrian; Zhang, Lin: Discrete second order adjoints in atmospheric chemical transport modeling (2008)
  18. Tian, Guo-Liang; Tang, Man-Lai; Fang, Hong-Bin; Tan, Ming: Efficient methods for estimating constrained parameters with applications to regularized (lasso) logistic regression (2008)
  19. Xiao, Yunhai; Hu, Qingjie: Subspace Barzilai-Borwein gradient method for large-scale bound constrained optimization (2008)
  20. Xiao, Yunhai; Li, Dong-Hui: An active set limited memory BFGS algorithm for large-scale bound constrained optimization (2008)

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