• CVX

  • Referenced in 652 articles [sw04594]
  • also solve much more complex convex optimization problems, including many involving nondifferentiable functions, such ... solve constrained norm minimization, entropy maximization, determinant maximization, and many other convex programs...
  • fminsearch

  • Referenced in 239 articles [sw07467]
  • popular direct search method for multidimensional unconstrained minimization. Despite its widespread use, essentially no theoretical ... strictly convex functions in dimensions 1 and 2. We prove convergence to a minimizer ... McKinnon gives a family of strictly convex functions in two dimensions ... converge to a minimizer for a more specialized class of convex functions in two dimensions...
  • NESTA

  • Referenced in 115 articles [sw06576]
  • fewer alternatives, such as total-variation minimization and convex programs seeking to minimize...
  • alphaBB

  • Referenced in 49 articles [sw06249]
  • solution of a series of nonlinear convex minimization problems. The global optimization method, ffBB...
  • SNLSDP

  • Referenced in 37 articles [sw05127]
  • relaxation (with regularization) of the non-convex minimization problem (1), and use the SDP computed...
  • NESUN

  • Referenced in 29 articles [sw28733]
  • present new methods for black-box convex minimization. They do not need to know...
  • isotone

  • Referenced in 28 articles [sw20811]
  • adjacent-violators algorithm (PAVA) to minimize a separable convex function with simple chain constraints. Besides...
  • bmrm

  • Referenced in 18 articles [sw11016]
  • Risk Minimization Package. Bundle methods for minimization of convex and non-convex risk under...
  • HANSO

  • Referenced in 11 articles [sw05271]
  • gradient sampling methods. For general unconstrained minimization: convex or nonconvex, smooth or nonsmooth, including BFGS...
  • SQOPT

  • Referenced in 17 articles [sw07860]
  • SQOPT is a software package for minimizing a convex quadratic function subject to both equality...
  • QPOPT

  • Referenced in 17 articles [sw07859]
  • convex quadratic programming. QPOPT is a set of Fortran 77 subroutines for minimizing a general ... inequalities. If the quadratic function is convex (i.e., the Hessian is positive definite or positive ... will be a global minimizer. If the quadratic is non-convex (i.e., the Hessian...
  • OrthoMADS

  • Referenced in 43 articles [sw07713]
  • which yields convex cones of missed directions at each iteration that are minimal...
  • TILOS

  • Referenced in 8 articles [sw11680]
  • three programs is shown to be convex: 1) Minimize A subject ... subject to A < K. 3) Minimize AT K . The convex equations describing...
  • iPiano

  • Referenced in 42 articles [sw09623]
  • solving a minimization problem composed of a differentiable (possibly nonconvex) and a convex (possibly nondifferentiable...
  • LS-SVMlab

  • Referenced in 24 articles [sw07367]
  • theory and structural risk minimization. In the methods one solves convex optimization problems, typically quadratic...
  • NAPHEAP

  • Referenced in 8 articles [sw23701]
  • This article considers the problem of minimizing a convex, separable quadratic function subject...
  • SPGL1

  • Referenced in 153 articles [sw08365]
  • solution. We prove that this curve is convex and continuously differentiable over all points ... iteration, a spectral gradient-projection method approximately minimizes a least-squares problem with an explicit...
  • ConicBundle

  • Referenced in 12 articles [sw05118]
  • implements a bundle method for minimizing the sum of convex functions that are given...
  • 2EBD-HPE

  • Referenced in 11 articles [sw31879]
  • method which is proposed to minimize the sum of convex differentiable functions and convex...
  • cdd

  • Referenced in 109 articles [sw00114]
  • given as the Minkowski sum of the convex hull of a finite set of points ... linear programming (LP) problem to maximize (or minimize) a linear function over polyhedron...