A unifying convergence analysis of second-order methods for secular equations

A unifying convergence analysis of second-order methods for secular equations

Existing numerical methods of second-order are considered for a so-called secular equation. We give a brief description of the most important of these methods and show that all of them can be interpreted as improvements of Newton’s method for an equivalent problem for which Newton’s method exhibits convergence from any point in a given interval. This interpretation unifies the convergence analy...

Analysis of third-order methods for secular equations

Third-order numerical methods are analyzed for secular equations. These equations arise in several matrix problems and numerical linear algebra applications. A closer look at an existing method shows that it can be considered as a classical method for an equivalent problem. This not only leads to other third-order methods, it also provides the means for a unifying convergence analysis of these ...

Convergence Analysis of the Legendre Spectral Collocation Methods for Second Order Volterra Integro-Differential Equations

A class of numerical methods is developed for second order Volterra integrodifferential equations by using a Legendre spectral approach. We provide a rigorous error analysis for the proposed methods, which shows that the numerical errors decay exponentially in the L∞-norm and L-norm. Numerical examples illustrate the convergence and effectiveness of the numerical methods. AMS subject classifica...

New family of Two-Parameters Iterative Methods for Non-Linear Equations with Fourth-Order Convergence

A Unifying Framework for Convergence Analysis of Approximate Newton Methods

Many machine learning models are reformulated as optimization problems. Thus, it is important to solve a large-scale optimization problem in big data applications. Recently, subsampled Newton methods have emerged to attract much attention for optimization due to their efficiency at each iteration, rectified a weakness in the ordinary Newton method of suffering a high cost in each iteration whil...