Lectures related to Newton Method: Convergence and Quadratic Care

Covers the convergence of fixed point methods for nonlinear equations, including global and local convergence theorems and the order of convergence.

Covers Newton's method for finding zeros of functions through fixed point iteration and discusses convergence properties.

Covers implicit schemes in numerical analysis for solving partial differential equations.

Discusses proximal gradient descent and its applications in optimizing machine learning algorithms.

Discusses proximal and subgradient descent methods for optimization in machine learning.

Covers methods for solving nonlinear equations, including bisection and Newton-Raphson methods, with a focus on convergence and error criteria.