Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
Lecture
Conjugate Gradient Optimization
Description
This lecture covers the Conjugate Gradient optimization method, focusing on the quadratic case and nonlinear constrained optimization. It explains the Wolfe conditions, the use of BFGS and CG algorithms, and the importance of preconditioning. The instructor discusses the convergence speed, the application of the conjugate gradient method, and the significance of symmetric matrices in optimization.
Official source
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.