Iterative methods for minimizing smooth functions, such as the BFGS algorithm, the Frank-Wolfe algorithm and sequential quadratic programming. An algorithm belongs here when its cited article describes an iterative method for unconstrained or constrained numerical optimization. It excludes linear programming and metaheuristic methods. A member is placed here by what its own cited article states about it, not by the name of the algorithm or by the uses it is put to today, so each entry sits in the group its source describes it as belonging to.
All Gradient and Quasi-Newton Optimization Methods
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Newton's method in optimization (Wikipedia)
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is an iterative method for finding the roots of a differentiable function
View the Source Line search (Wikipedia)
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The descent direction can be computed by various methods, such as gradient descent or quasi-Newton method.
View the Source Broyden-Fletcher-Goldfarb-Shanno algorithm (Wikipedia)
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iterative method for solving unconstrained nonlinear optimization
View the Source Frank-Wolfe algorithm (Wikipedia)
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iterative first-order optimization algorithm for constrained convex optimization
View the Source Sequential quadratic programming (Wikipedia)
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is an iterative method for constrained nonlinear optimization
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