💡 Words with a Similar Meaning to "Sequential minimal optimization"
Found via reverse dictionary — words that share a conceptual meaning.
| Word | Definition |
|---|---|
| sequential quadratic programming | an iterative method for constrained nonlinear optimization which may be considered a quasi-Newton method. |
| quadratic programming | the process of solving certain mathematical optimization problems involving quadratic functions. |
| sum-of-squares optimization | A sum-of-squares optimization program is an optimization problem with a linear cost function and a particular type of constraint on the decision variables. |
| mm algorithm | an iterative optimization method which exploits the convexity of a function in order to find its maxima or minima. |
| matrix chain multiplication | (or the matrix chain ordering problem) an optimization problem concerning the most efficient way to multiply a given sequence of matrices. |
| semidefinite programming | a subfield of mathematical programming concerned with the optimization of a linear objective function (a user-specified function that the user wants to minimize or maximize) |
| quantum optimization algorithms | quantum algorithms that are used to solve optimization problems. |
| ellipsoid method | In mathematical optimization, the ellipsoid method is an iterative method for minimizing convex functions over convex sets. |
| adjoint state method | The adjoint state method is a numerical method for efficiently computing the gradient of a function or operator in a numerical optimization problem. |
| inverse quadratic interpolation | In numerical analysis, inverse quadratic interpolation is a root-finding algorithm, meaning that it is an algorithm for solving equations of the form f(x) = 0. |
| recursive least squares filter | Recursive least squares is an adaptive filter algorithm that recursively finds the coefficients that minimize a weighted linear least squares cost function relating to the input signals. |
| particle swarm optimization | In computational science, particle swarm optimization is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. |
| gradient descentnoun | (mathematics) A first-order iterative optimization algorithm for finding a local minimum of a differentiable function. |
| biconjugate gradient method | In mathematics, more specifically in numerical linear algebra, the biconjugate gradient method is an algorithm to solve systems of linear equations |
| relevance vector machine | In mathematics, a Relevance Vector Machine is a machine learning technique that uses Bayesian inference to obtain parsimonious solutions for regression and probabilistic classification. |
| qr algorithm | In numerical linear algebra, the QR algorithm or QR iteration is an eigenvalue algorithm: that is, a procedure to calculate the eigenvalues and eigenvectors of a matrix. |
| conjugate gradient method | In mathematics, the conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations, namely those whose matrix is positive-semidefinite. |
| coordinate descent | an optimization algorithm that successively minimizes along coordinate directions to find the minimum of a function. |
| nonlinear programming | In mathematics, nonlinear programming is the process of solving an optimization problem where some of the constraints are not linear equalities or the objective function is not a linear function. |
| subgradient method | Subgradient methods are convex optimization methods which use subderivatives. |
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