Fletcher-Reeves Method Explained, Optimization Lecture 18

Three conjugate gradient methods for numerical function minimization are derived using the conjugate gradient formula for a quadratic function. These methods are the Hestenes-Stiefel method, Polak-Rebiere method and the Fletcher-Reeves method. Approximations made about exact line searches are clearly mentioned. The formulas for these methods are derived. Optimization tutorial #optimizationtechniques #optimization Video to watch next: https://youtu.be/SXmNbqKiNTc Optimization playlist: https://www.youtube.com/playlist?list=PLLbH4oi6GwyQWYMK11UbRyqzbPkvdorjc