• BRENT

  • Referenced in 432 articles [sw14021]
  • BRENT Algorithms for Minimization Without Derivatives. BRENT is a C library which contains algorithms...
  • GQTPAR

  • Referenced in 322 articles [sw07451]
  • step We propose an algorithm for the problem of minimizing a quadratic function subject ... also consider the use of this algorithm in a trust region Newton’s method ... second order necessary conditions for a minimizer of the objective function. Numerical results for GQTPAR ... which is a Fortran implementation of our algorithm, show that GQTPAR is quite successful...
  • ve08

  • Referenced in 148 articles [sw05141]
  • computing time by using a minimization algorithm that exploits some special structure ... clustered eigenvalues at a minimizer x *, in which case conjugate gradient and limited memory variable...
  • fminsearch

  • Referenced in 267 articles [sw07467]
  • dimensions The Nelder--Mead simplex algorithm, first published in 1965, is an enormously popular direct ... search method for multidimensional unconstrained minimization. Despite its widespread use, essentially no theoretical results have ... been proved explicitly for the Nelder--Mead algorithm. This paper presents convergence properties ... Nelder--Mead algorithm applied to strictly convex functions in dimensions 1 and 2. We prove...
  • MAXFLOW

  • Referenced in 132 articles [sw13223]
  • Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision.” Yuri Boykov and Vladimir...
  • KELLEY

  • Referenced in 628 articles [sw04829]
  • optimization methods for unconstrained and bound constrained minimization problems. The style of the book ... complete generality and confine our scope to algorithms that are easy to implement ... such cases the noise often introduces artificial minimizers. Gradient information, even if available, cannot expected ... used to demonstrate the behavior of optimization algorithms. Chapter 7 introduces implicit filtering, a technique...
  • AdaGrad

  • Referenced in 144 articles [sw22202]
  • hindsight. We give several efficient algorithms for empirical risk minimization problems with common and important ... adaptive, subgradient algorithms...
  • QMRPACK

  • Referenced in 78 articles [sw00754]
  • QMRPACK: A package of QMR algorithms. The quasi-minimal residual (QMR) algorithm is a Krylov...
  • Algorithm 500

  • Referenced in 69 articles [sw05275]
  • Algorithm 500: Minimization of Unconstrained Multivariate Functions...
  • spcov

  • Referenced in 37 articles [sw12271]
  • positive definite. Implements the majorize-minimize algorithm described in Bien, J., and Tibshirani...
  • MIPLIB

  • Referenced in 319 articles [sw04067]
  • which a linear objective function is minimized subject to linear constraints over real- and integervalued ... benchmarking and testing of mip solution algorithms...
  • Scikit

  • Referenced in 496 articles [sw08058]
  • state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This ... performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified...
  • ROOT

  • Referenced in 55 articles [sw06817]
  • analysis (multi-dimensional histogramming, fitting, minimization, cluster finding algorithms) and visualization tools. The user interacts...
  • SDBOX

  • Referenced in 30 articles [sw05137]
  • globally convergent derivative-free algorithm for the minimization of a continuously differentiable function ... variables are bounded. This algorithm investigates the local behaviour of the objective function ... limit accuracy of the algorithm in the minimization of noisy functions. Finally, we report...
  • iPiano

  • Referenced in 53 articles [sw09623]
  • this paper we study an algorithm for solving a minimization problem composed of a differentiable ... convex (possibly nondifferentiable) function. The algorithm iPiano combines forward-backward splitting with an inertial force...
  • FPC_AS

  • Referenced in 66 articles [sw12218]
  • propose a fast algorithm for solving the ℓ 1 -regularized minimization problem ... system of linear equations Ax=b. The algorithm is divided into two stages that ... resulting subspace problem, which involves the minimization of a smaller and smooth quadratic function ... embeds this basic two-stage algorithm in a continuation (homotopy) approach by assigning a decreasing...
  • Optimization Toolbox

  • Referenced in 293 articles [sw10828]
  • Toolbox™ provides functions for finding parameters that minimize or maximize objectives while satisfying constraints ... tradeoff analyses, and incorporate optimization methods into algorithms and applications...
  • simannf90

  • Referenced in 119 articles [sw05059]
  • Minimizing multimodal functions of continuous variables with the “simulated annealing” algorithm From authors’ summary...
  • UOBYQA

  • Referenced in 65 articles [sw07576]
  • algorithm generates a new vector of variables either by minimizing the quadratic model subject ... adjustment of trust region radii. par The algorithm works with the Lagrange functions ... quadratic approximation of the function being minimized. It is pointed out that results are very...
  • DFBOX_IMPR

  • Referenced in 21 articles [sw36996]
  • globally convergent derivative-free algorithm for the minimization of a continuously differentiable function ... variables are bounded. This algorithm investigates the local behaviour of the objective function ... limit accuracy of the algorithm in the minimization of noisy functions. Finally, we report...