Machine Learning, Gradient Descent, Hessian Matrix, Optimization, Artificial Intelligence.
with a matrix. When a matrix acts on its eigenvector, the result is simply the eigenvector multiplied by a scalar. This means the vector’s direction doesn’t change, only its magnitude. Eigenvalues: These are scaling factors, telling us if the curvature along an eigenvector direction is uphill