
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 totalvariation 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 nonconvex minimization problem (1), and use the SDP computed...

NESUN
 Referenced in 29 articles
[sw28733]
 present new methods for blackbox convex minimization. They do not need to know...

isotone
 Referenced in 28 articles
[sw20811]
 adjacentviolators 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 nonconvex 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 nonconvex (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...

LSSVMlab
 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 gradientprojection method approximately minimizes a leastsquares problem with an explicit...

ConicBundle
 Referenced in 12 articles
[sw05118]
 implements a bundle method for minimizing the sum of convex functions that are given...

2EBDHPE
 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...