💡 Words with a Similar Meaning to "Subgradient method"
Found via reverse dictionary — words that share a conceptual meaning.
| Word | Definition |
|---|---|
| gradient method | In optimization, a gradient method is an algorithm to solve problems of the form |
| ellipsoid method | In mathematical optimization, the ellipsoid method is an iterative method for minimizing convex functions over convex sets. |
| sequential quadratic programming | an iterative method for constrained nonlinear optimization which may be considered a quasi-Newton method. |
| proximal gradient method | Proximal gradient methods are a generalized form of projection used to solve non-differentiable convex optimization problems. |
| mm algorithm | an iterative optimization method which exploits the convexity of a function in order to find its maxima or minima. |
| linear multistep method | Linear multistep methods are used for the numerical solution of ordinary differential equations. |
| mirror descent | In mathematics, mirror descent is an 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 |
| newton's method in optimization | In calculus, Newton's method (also called Newton–Raphson) is an iterative method for finding the roots of a differentiable function , which are solutions to the equation . |
| gradient descentnoun | (mathematics) A first-order iterative optimization algorithm for finding a local minimum of a differentiable function. |
| 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 iteration | In numerical analysis, inverse iteration (also known as the inverse power method) is an iterative eigenvalue algorithm. |
| 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. |
| kaczmarz method | The Kaczmarz method or Kaczmarz's algorithm is an iterative algorithm for solving linear equation systems . |
| quadratic programming | the process of solving certain mathematical optimization problems involving quadratic functions. |
| interior-point method | Interior-point methods (also referred to as barrier methods or IPMs) are algorithms for solving linear and non-linear convex optimization problems. |
| numerical continuation | a method of computing approximate solutions of a system of parameterized nonlinear equations, |
| convex optimization | a subfield of mathematical optimization that studies the problem of minimizing convex functions over convex sets (or, equivalently, maximizing concave functions over convex sets). |
| relaxationnoun | The act of relaxing or the state of being relaxed; the opposite of stress or tension; the aim of recreation and leisure activities. |
| stochastic gradient descent | (often abbreviated SGD) an iterative method for optimizing an objective function with suitable smoothness properties (e.g. differentiable or subdifferentiable). |
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