Pages that link to "Item:Q2419539"

The following pages link to Convergence and evaluation-complexity analysis of a regularized tensor-Newton method for solving nonlinear least-squares problems (Q2419539):

Displaying 8 items.

• New approach to global minimization of normal multivariate polynomial based on tensor (Q1008796) (← links)
• An adaptive high order method for finding third-order critical points of nonconvex optimization (Q2079692) (← links)
• On the evaluation complexity of cubic regularization methods for potentially rank-deficient nonlinear least-squares problems and its relevance to constrained nonlinear optimization (Q2866197) (← links)
• Universal Regularization Methods: Varying the Power, the Smoothness and the Accuracy (Q4629334) (← links)
• A Stochastic Levenberg--Marquardt Method Using Random Models with Complexity Results (Q5075237) (← links)
• Efficiency of higher-order algorithms for minimizing composite functions (Q6155068) (← links)
• The evaluation complexity of finding high-order minimizers of nonconvex optimization (Q6200212) (← links)
• Complexity analysis of regularization methods for implicitly constrained least squares (Q6635781) (← links)