Add to ORKGA regression problem is separable if the model can be represented as a linear combination of functions which have a nonlinear parametric dependence. The Gauss-Newton algorithm is a method for minimizing the residual sum of squares in such problems. It i
This paper has two main purposes: To discuss general principles for a reliable and efficient numeric...
In this work, we combine the special structure of the separable nonlinear least squares problem with...
Abstract — In numerical linear algebra, the variable projec-tion (VP) algorithm has been a standard ...
Dedicated to Gene Golub on the occasion of his 75th birthday Abstract. A regression problem is separ...
Consider the separable nonlinear least squares problem of finding ~a in R^n and ~alpha in R^k which,...
Abstract. Modeling the mean of a random variable as a function of unknown parameters leads to a nonl...
We consider a class of non-linear least squares problems that are widely used in fitting experimenta...
Abstract. We consider a class of non-linear least squares problems that are widely used in fitting e...
Parameter estimation problems of mathematical models can often be formulated as nonlinear least squa...
For separable nonlinear least squares models, a variable projection algorithm based on matrix factor...
In this paper, we suggest a generalized Gauss-Seidel approach to sparse linear and nonlinear least-s...
Parameter estimation problems of mathematical models can often be formulated as nonlinear least squa...
The Gauss-Newton algorithm for solving nonlinear least squares problems proves particularly efficien...
Variable Projection (VarPro) is a framework to solve optimization problems efficiently by optimally ...
Variable Projection (VarPro) is a framework to solve op- timization problems efficiently by optimall...
This paper has two main purposes: To discuss general principles for a reliable and efficient numeric...
In this work, we combine the special structure of the separable nonlinear least squares problem with...
Abstract — In numerical linear algebra, the variable projec-tion (VP) algorithm has been a standard ...
Dedicated to Gene Golub on the occasion of his 75th birthday Abstract. A regression problem is separ...
Consider the separable nonlinear least squares problem of finding ~a in R^n and ~alpha in R^k which,...
Abstract. Modeling the mean of a random variable as a function of unknown parameters leads to a nonl...
We consider a class of non-linear least squares problems that are widely used in fitting experimenta...
Abstract. We consider a class of non-linear least squares problems that are widely used in fitting e...
Parameter estimation problems of mathematical models can often be formulated as nonlinear least squa...
For separable nonlinear least squares models, a variable projection algorithm based on matrix factor...
In this paper, we suggest a generalized Gauss-Seidel approach to sparse linear and nonlinear least-s...
Parameter estimation problems of mathematical models can often be formulated as nonlinear least squa...
The Gauss-Newton algorithm for solving nonlinear least squares problems proves particularly efficien...
Variable Projection (VarPro) is a framework to solve optimization problems efficiently by optimally ...
Variable Projection (VarPro) is a framework to solve op- timization problems efficiently by optimall...
This paper has two main purposes: To discuss general principles for a reliable and efficient numeric...
In this work, we combine the special structure of the separable nonlinear least squares problem with...
Abstract — In numerical linear algebra, the variable projec-tion (VP) algorithm has been a standard ...