Machine Learning, Gradient Descent, Hessian Matrix, Optimization, Artificial Intelligence.
again. The curvature at any point bends upwards in all directions. The Hessian will have positive eigenvalues, reflecting this upward curvature. Example Equation: f(x, y) = x^2 + 2y^2 This function has a Hessian of H(f) = [[2, 0], [0, 4]] with eigenvalues 2 and 4. The positive eigenvalue 2