Quasi Newton Methods, Optimization Lecture 22

Quasi-Newton methods are based on the Secant method in numerical analysis and is explained considering one-dimensional and multi-dimensional functions. The secant condition is used to motivate the secant condition which leads to the Hessian matrix approximations. the BFGS and DFP are quasi Newton methods which are popular for unconstrained multivariate function minimization. Optimization Tutorial #optimizationtechniques #optimization Optimization playlist:    • Optimization Techniques Lectures