• # ParNes

• Referenced in 12 articles [sw08366]
• squares problem with a 1-norm constraint on the solution. We prove under the assumption ... sparsity condition on the solution, that nesta-lasso is guaranteed to be almost always locally ... bpdn) problem (i.e., approximating the minimum 1-norm solution to an underdetermined least squares problem...
• # PDNET

• Referenced in 39 articles [sw04752]
• implementation of this algorithm for solving the minimum-cost network flow problem. In each iteration ... search direction is computed inexactly, and the norm of the resulting residual vector is used ... iterative solver employed for the solution of the system. In the implementation, a preconditioned conjugate ... tested on a large set of standard minimum-cost network flow test problems. Computational results...
• # GMBACK

• Referenced in 12 articles [sw02139]
• GMBACK: A generalised minimum backward error algorithm for nonsymmetric linear systems A drawback of employing ... residual error norm as a stopping condition in an iterative process is that the error ... present an algorithm which computes an approximate solution to the linear system $Ax = b$ such...
• # SpaRSA

• Referenced in 3 articles [sw20467]
• Reconstruction by Separable Approximation. Finding sparse approximate solutions to large underdetermined linear systems of equations ... sparsity-inducing (usually the 1-norm) regularizer. We present an algorithmic framework for the more ... proposed iterative algorithm to a minimum of the objective function. In addition to solving ... yields efficient solution techniques for other regularizers, such as an 1-norm and group-separable...
• # BEDFix

• Referenced in 8 articles [sw04469]
• constant 1 with respect to the infinity norm; such functions are commonly found in economics ... highly efficient when used to compute residual solutions for bivariate functions, having a bound ... gradient information; also, it handles functions with minimum Lipschitz constants equal to 1, whereas...