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  2. Newton's method in optimization - Wikipedia

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

    Newton's method uses curvature information (i.e. the second derivative) to take a more direct route. In calculus , Newton's method (also called Newton–Raphson ) is an iterative method for finding the roots of a differentiable function f {\displaystyle f} , which are solutions to the equation f ( x ) = 0 {\displaystyle f(x)=0} .

  3. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    An illustration of Newton's method. In numerical analysis, the Newton–Raphson method, also known simply as Newton's method, named after Isaac Newton and Joseph Raphson, is a root-finding algorithm which produces successively better approximations to the roots (or zeroes) of a real-valued function.

  4. Gauss–Newton algorithm - Wikipedia

    en.wikipedia.org/wiki/Gauss–Newton_algorithm

    In a quasi-Newton method, such as that due to Davidon, Fletcher and Powell or Broyden–Fletcher–Goldfarb–Shanno (BFGS method) an estimate of the full Hessian is built up numerically using first derivatives only so that after n refinement cycles the method closely approximates to Newton's method in performance. Note that quasi-Newton ...

  5. Mathematical optimization - Wikipedia

    en.wikipedia.org/wiki/Mathematical_optimization

    Newton's method requires the 2nd-order derivatives, so for each iteration, the number of function calls is in the order of N², but for a simpler pure gradient optimizer it is only N. However, gradient optimizers need usually more iterations than Newton's algorithm.

  6. De analysi per aequationes numero terminorum infinitas

    en.wikipedia.org/wiki/De_analysi_per_aequationes...

    Composed in 1669, [4] during the mid-part of that year probably, [5] from ideas Newton had acquired during the period 1665–1666. [4] Newton wrote And whatever the common Analysis performs by Means of Equations of a finite number of Terms (provided that can be done) this new method can always perform the same by means of infinite Equations.

  7. Truncated Newton method - Wikipedia

    en.wikipedia.org/wiki/Truncated_Newton_method

    The truncated Newton method, originated in a paper by Ron Dembo and Trond Steihaug, [1] also known as Hessian-free optimization, [2] are a family of optimization algorithms designed for optimizing non-linear functions with large numbers of independent variables.

  8. Verlet integration - Wikipedia

    en.wikipedia.org/wiki/Verlet_integration

    Verlet integration (French pronunciation:) is a numerical method used to integrate Newton's equations of motion. [1] It is frequently used to calculate trajectories of particles in molecular dynamics simulations and computer graphics.

  9. Newton fractal - Wikipedia

    en.wikipedia.org/wiki/Newton_fractal

    The Newton fractal is a boundary set in the complex plane which is characterized by Newton's method applied to a fixed polynomial p(z) ∈ [z] or transcendental function. It is the Julia set of the meromorphic function z ↦ z − ⁠ p(z) / p′(z) ⁠ which is given by Newton's method.