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  2. Multigrid method - Wikipedia

    en.wikipedia.org/wiki/Multigrid_method

    Multigrid preconditioning is used in practice even for linear systems, typically with one cycle per iteration, e.g., in Hypre. Its main advantage versus a purely multigrid solver is particularly clear for nonlinear problems, e.g., eigenvalue problems.

  3. Interior-point method - Wikipedia

    en.wikipedia.org/wiki/Interior-point_method

    An interior point method was discovered by Soviet mathematician I. I. Dikin in 1967. [1] The method was reinvented in the U.S. in the mid-1980s. In 1984, Narendra Karmarkar developed a method for linear programming called Karmarkar's algorithm, [2] which runs in provably polynomial time (() operations on L-bit numbers, where n is the number of variables and constants), and is also very ...

  4. Constrained least squares - Wikipedia

    en.wikipedia.org/wiki/Constrained_least_squares

    In constrained least squares one solves a linear least squares problem with an additional constraint on the solution. [ 1 ] [ 2 ] This means, the unconstrained equation X β = y {\displaystyle \mathbf {X} {\boldsymbol {\beta }}=\mathbf {y} } must be fit as closely as possible (in the least squares sense) while ensuring that some other property ...

  5. Line length - Wikipedia

    en.wikipedia.org/wiki/Line_length

    In typography, line length is the width of a block of typeset text, usually measured in units of length like inches or points or in characters per line (in which case it is a measure). A block of text or paragraph has a maximum line length that fits a determined design. If the lines are too short then the text becomes disjointed; if they are ...

  6. Levenberg–Marquardt algorithm - Wikipedia

    en.wikipedia.org/wiki/Levenberg–Marquardt...

    In mathematics and computing, the Levenberg–Marquardt algorithm (LMA or just LM), also known as the damped least-squares (DLS) method, is used to solve non-linear least squares problems. These minimization problems arise especially in least squares curve fitting.

  7. Wolfe conditions - Wikipedia

    en.wikipedia.org/wiki/Wolfe_conditions

    Each step often involves approximately solving the subproblem (+) where is the current best guess, is a search direction, and is the step length. The inexact line searches provide an efficient way of computing an acceptable step length α {\displaystyle \alpha } that reduces the objective function 'sufficiently', rather than minimizing the ...

  8. What to do when your CD matures: Taking advantage of your ...

    www.aol.com/finance/what-to-do-when-cd-matures...

    Acting quickly within your grace period can help you avoid missed opportunities. Here's happens when a CD matures — and your 3 main options.

  9. Linear congruential generator - Wikipedia

    en.wikipedia.org/wiki/Linear_congruential_generator

    The second row is the same generator with a seed of 3, which produces a cycle of length 2. Using a = 4 and c = 1 (bottom row) gives a cycle length of 9 with any seed in [0, 8]. A linear congruential generator (LCG) is an algorithm that yields a sequence of pseudo-randomized numbers calculated with a discontinuous piecewise linear equation.