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  2. Augmented Lagrangian method - Wikipedia

    en.wikipedia.org/wiki/Augmented_Lagrangian_method

    Augmented Lagrangian methods are a certain class of algorithms for solving constrained optimization problems. They have similarities to penalty methods in that they replace a constrained optimization problem by a series of unconstrained problems and add a penalty term to the objective, but the augmented Lagrangian method adds yet another term designed to mimic a Lagrange multiplier.

  3. Lagrange multiplier - Wikipedia

    en.wikipedia.org/wiki/Lagrange_multiplier

    The Lagrange multiplier theorem states that at any local maximum (or minimum) of the function evaluated under the equality constraints, if constraint qualification applies (explained below), then the gradient of the function (at that point) can be expressed as a linear combination of the gradients of the constraints (at that point), with the ...

  4. Karush–Kuhn–Tucker conditions - Wikipedia

    en.wikipedia.org/wiki/Karush–Kuhn–Tucker...

    Consider the following nonlinear optimization problem in standard form: . minimize () subject to (),() =where is the optimization variable chosen from a convex subset of , is the objective or utility function, (=, …,) are the inequality constraint functions and (=, …,) are the equality constraint functions.

  5. Conjugate gradient method - Wikipedia

    en.wikipedia.org/wiki/Conjugate_gradient_method

    A practical way to enforce this is by requiring that the next search direction be built out of the current residual and all previous search directions. The conjugation constraint is an orthonormal-type constraint and hence the algorithm can be viewed as an example of Gram-Schmidt orthonormalization. This gives the following expression:

  6. Levenberg–Marquardt algorithm - Wikipedia

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

    The primary application of the Levenberg–Marquardt algorithm is in the least-squares curve fitting problem: given a set of empirical pairs (,) of independent and dependent variables, find the parameters ⁠ ⁠ of the model curve (,) so that the sum of the squares of the deviations () is minimized:

  7. New Kindle? Here are 10 accessories you need - AOL

    www.aol.com/lifestyle/new-kindle-here-are-10...

    This page turner works on any capacitive screen (i.e. screens that operate using the body's electrical currents), and includes a clip that goes onto the screen and remote you use can across a ...

  8. California mom shot and killed by her 2-year-old; boyfriend ...

    www.aol.com/california-mom-shot-killed-her...

    A California woman was fatally shot by her 2-year-old toddler, leading to the arrest of her boyfriend who is accused of failing to properly store the weapon, Fresno police said this week.

  9. Meghan Markle's Body Language Speaks Volumes in New Footage ...

    www.aol.com/lifestyle/meghan-markles-body...

    Meghan Markle is back and better than ever. Not only did the Suits actress make her triumphant return to IG in a sweet video celebrating the new year, but she also announced her brand new Netflix ...