- Referenced in 72 articles
- Convergence of a non-interior continuation algorithm for the monotone SCCP It is well known ... algorithm is globally linearly and locally quadratically convergent under suitable assumptions...
- Referenced in 39 articles
- certify that Newton iterations will converge quadratically to solutions to a square polynomial system...
- Referenced in 28 articles
- Meini, 1996), provides a numerically stable, quadratically convergent method for solving the matrix equation...
- Referenced in 59 articles
- algorithm for solving the SSVM converges globally and quadratically. Numerical results and comparisons are given...
- Referenced in 148 articles
- particular it is NP-hard when the quadratic objective is nonconvex. On the other hand ... Newton method, the SQP algorithm converges very rapidly, meaning that it requires few iterations (hence...
- Referenced in 12 articles
- scaling algorithm, global convergence and local quadratic convergence are proved...
- Referenced in 55 articles
- Sequential Quadratic Programming solver with a “filter” to promote global convergence. The solver runs with ... robust QP solver. Keywords: Nonlinear Programming, Sequential Quadratic Programming...
- Referenced in 46 articles
- family of trust-region interior-point sequential quadratic programming (SQP) algorithms for the solution ... methods, including many iterative techniques.par Global convergence of these algorithms to a first-order Karush ... reasonable, but more stringent, conditions on the quadratic model and on the trial steps ... rate of convergence to a nondegenerate strict local minimizer is $q$-quadratic. The results given...
- Referenced in 10 articles
- increases volume conservation. A new efficient (quadratic convergent) and accurate iterative flux correction algorithm...
- Referenced in 9 articles
- prescribed value. Global and local quadratic convergence are proved under nondegeneracy assumptions for both algorithms...
- Referenced in 8 articles
- presented and discussed and a local quadratic convergence of the semismooth Newton method is observed...
- Referenced in 144 articles
- lack of convergence with spatial refinement, or convergence to a solution that is slightly different ... calculated from an optimal fit for a quadratic approximation to the interface over groups...
- Referenced in 3 articles
- through a variant of the (locally quadratically convergent) Newton method. For this method, easily computable...
- Referenced in 67 articles
- regression problems are trained by solving a quadratic optimization problem which needs on the order ... recent paper from C. Lin [On the convergence of the decomposition method for support vector...
- Referenced in 61 articles
- implementation of two algorithms based on Sequential Quadratic Programming (SQP), modified so as to generate ... eventually accepted, a requirement for superlinear convergence. In the second one the same effect...
- Referenced in 20 articles
- Newton’s method and employs a quadratic approximation, but with some modifications that leverage ... show that our method is superlinearly convergent, and present experimental results using synthetic and real...
- Referenced in 6 articles
- sequential quadratic programming (SQP) method for inequality constrained problems and provide local convergence theory ... guarantee fast convergence. For the solution of the occurring large-scale quadratic programming problems ... counter-intuitive toy examples which show that convergence of a one-shot one-step optimization...
- Referenced in 38 articles
- function and a linearization of constraints, a quadratic programming subproblem is formulated and solved ... given number of iterations. All theoretical convergence properties of the SQP algorithm remain satisfied...
- Referenced in 14 articles
- algorithms are performed. Worst-case time complexity, convergence results, and examples are included. The fast ... transforms and then reduce the brute force quadratic worst-case time complexity to linear time...
- Referenced in 7 articles
- second-order dynamical systems is presented: the quadratic dominant pole algorithm (QDPA). The algorithm works ... linearization is needed. To improve global convergence, the QDPA uses subspace acceleration, and deflation...