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  2. Saddle point - Wikipedia

    en.wikipedia.org/wiki/Saddle_point

    A saddle point (in red) on the graph of z = x 2 − y 2 (hyperbolic paraboloid). In mathematics, a saddle point or minimax point [1] is a point on the surface of the graph of a function where the slopes (derivatives) in orthogonal directions are all zero (a critical point), but which is not a local extremum of the function. [2]

  3. Newton's method in optimization - Wikipedia

    en.wikipedia.org/wiki/Newton's_method_in...

    The geometric interpretation of Newton's method is that at each iteration, it amounts to the fitting of a parabola to the graph of () at the trial value , having the same slope and curvature as the graph at that point, and then proceeding to the maximum or minimum of that parabola (in higher dimensions, this may also be a saddle point), see below.

  4. Second partial derivative test - Wikipedia

    en.wikipedia.org/wiki/Second_partial_derivative_test

    At the remaining critical point (0, 0) the second derivative test is insufficient, and one must use higher order tests or other tools to determine the behavior of the function at this point. (In fact, one can show that f takes both positive and negative values in small neighborhoods around (0, 0) and so this point is a saddle point of f.)

  5. Method of steepest descent - Wikipedia

    en.wikipedia.org/wiki/Method_of_steepest_descent

    In mathematics, the method of steepest descent or saddle-point method is an extension of Laplace's method for approximating an integral, where one deforms a contour integral in the complex plane to pass near a stationary point (saddle point), in roughly the direction of steepest descent or stationary phase. The saddle-point approximation is ...

  6. Derivative test - Wikipedia

    en.wikipedia.org/wiki/Derivative_test

    In calculus, a derivative test uses the derivatives of a function to locate the critical points of a function and determine whether each point is a local maximum, a local minimum, or a saddle point. Derivative tests can also give information about the concavity of a function.

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  8. Mathematical optimization - Wikipedia

    en.wikipedia.org/wiki/Mathematical_optimization

    Further, critical points can be classified using the definiteness of the Hessian matrix: If the Hessian is positive definite at a critical point, then the point is a local minimum; if the Hessian matrix is negative definite, then the point is a local maximum; finally, if indefinite, then the point is some kind of saddle point.

  9. Go Small or Go Home With These 15 Teacup Dog Breeds - AOL

    www.aol.com/small-home-15-teacup-dog-180100277.html

    Should you be set on adding a teacup dog to your family, be sure you patronize an ethical breeder, and do your research, beginning with checking out our rundown of 15 teacup dog breeds that you'll ...