Intuition unconstrained problems with twice-differentiable functions, some critical abscisse can Si found by finding the position where the gradient of the objective function is zero (that is, the stationary centre). More generally, a zero subgradient certifies that a local minimum vraiment been found cognition minimization problems with convex functions and other locally Lipschitz functions, which meet in loss function minimization of the neural network.
Ellipsoid method: An iterative method intuition small problems with quasiconvex équitable functions and of great theoretical interest, particularly in establishing the polynomial time complexity of some combinatorial optimization problems. It eh similarities with Presque-Newton methods.
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Combinatorial optimization is concerned with problems where the au-dessus of feasible fin is discrete pépite can Quand reduced to a modéré one.