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Lecture
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.
This lecture covers the local convergence of Newton's method with a focus on the Lipschitz continuous Hessian. The instructor explains the conditions for the convergence of Newton's method and provides a theorem regarding the behavior of the method. The lecture also delves into the quadratic convergence of Newton's method and the proof behind it. Additionally, the lecture introduces the CG algorithm for solving linear equations, specifically focusing on the Conjugate Gradients method and its termination conditions based on the eigenvalues of the linear map.