Machine Learning, Gradient Descent, Hessian Matrix, Optimization, Artificial Intelligence.
direction to the biggest eigenvector (shown in red). Image generated in Python 2. Second-Order Optimizers: Methods like Newton’s Method directly use the Hessian (and hence its eigenvalues and eigenvectors) to calculate updates. They factor in the curvature, not just the direction, of the loss