Lectures related to Quasi-Newton Methods

Covers convex optimization problems and gradient-based algorithms to find the global minimum.

Covers Newton's Method for optimization and discusses the caveats of indefiniteness in optimization problems.

Covers root-finding methods, focusing on the bisection and secant techniques, their implementations, and comparisons of their convergence rates.

Covers the convergence of Newton's method and its applications in numerical analysis.

Covers the trust-region method and introduces the truncated conjugate gradients method.

Explains Newton's method of order 2 for finding function zeros.