The Frank–Wolfe algorithm is an iterative first-order optimization algorithm for constrained convex optimization. Also known as the conditional gradient...
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Route assignment (section Frank-Wolfe algorithm)
"pretty well," but they are not exact. Dafermos (1968) applied the Frank-Wolfe algorithm (1956, Florian 1976), which can be used to deal with the traffic...
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C. season Frank Wolfe (fictional character), see List of American Pickers episodes Frank–Wolfe algorithm, an optimization algorithm Frank Wolf (disambiguation)...
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Albert as her advisor. Together with Philip Wolfe in 1956 at Princeton, she invented the Frank–Wolfe algorithm, an iterative optimization method for general...
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Gradient method (category Optimization algorithms and methods)
Gradient descent Stochastic gradient descent Coordinate descent Frank–Wolfe algorithm Landweber iteration Random coordinate descent Conjugate gradient...
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swarm Frank-Wolfe algorithm: an iterative first-order optimization algorithm for constrained convex optimization Golden-section search: an algorithm for...
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gradient methods for learning Frank–Wolfe algorithm Daubechies, I; Defrise, M; De Mol, C (2004). "An iterative thresholding algorithm for linear inverse problems...
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general non-linear programming, leading to the Frank–Wolfe algorithm in joint work with Marguerite Frank, then a visitor at Princeton. When Maurice Sion...
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the choices of the others. This is very slow computationally. The Frank–Wolfe algorithm improves on this by exploiting dynamic programming properties of...
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optimization, Dantzig's simplex algorithm (or simplex method) is a popular algorithm for linear programming. The name of the algorithm is derived from the concept...
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{\displaystyle \alpha \in \mathbb {R} ^{+}} exactly. A line search algorithm can use Wolfe conditions as a requirement for any guessed α {\displaystyle \alpha...
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In numerical optimization, the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm is an iterative method for solving unconstrained nonlinear optimization...
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List of numerical analysis topics (redirect from List of eigenvalue algorithms)
programming Linear least squares (mathematics) Total least squares Frank–Wolfe algorithm Sequential minimal optimization — breaks up large QP problems into...
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A greedy algorithm is any algorithm that follows the problem-solving heuristic of making the locally optimal choice at each stage. In many problems, a...
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including the Online Newton Step and Online Frank Wolfe algorithm, projection free methods, and adaptive-regret algorithms. In the area of mathematical optimization...
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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...
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Limited-memory BFGS (category Optimization algorithms and methods)
is an optimization algorithm in the family of quasi-Newton methods that approximates the Broyden–Fletcher–Goldfarb–Shanno algorithm (BFGS) using a limited...
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In computer science, the Edmonds–Karp algorithm is an implementation of the Ford–Fulkerson method for computing the maximum flow in a flow network in...
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Metaheuristic (redirect from Meta-algorithm)
designed to find, generate, tune, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem...
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Gradient descent (category Optimization algorithms and methods)
Wolfe conditions Preconditioning Broyden–Fletcher–Goldfarb–Shanno algorithm Davidon–Fletcher–Powell formula Nelder–Mead method Gauss–Newton algorithm...
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computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems...
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Integer programming (redirect from Lenstra's algorithm)
presented an improved algorithm with run-time n O ( n ) ⋅ ( m ⋅ log V ) O ( 1 ) {\displaystyle n^{O(n)}\cdot (m\cdot \log V)^{O(1)}} . Frank and Tardos presented...
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Branch and bound (redirect from Branch-and-bound algorithm)
an algorithm design paradigm for discrete and combinatorial optimization problems, as well as mathematical optimization. A branch-and-bound algorithm consists...
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Scoring algorithm, also known as Fisher's scoring, is a form of Newton's method used in statistics to solve maximum likelihood equations numerically,...
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Column generation (category Optimization algorithms and methods)
programming which uses this kind of approach is the Dantzig–Wolfe decomposition algorithm. Additionally, column generation has been applied to many problems...
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1145/1791212.1791238. Frank Hutter, Holger Hoos, and Kevin Leyton-Brown (2011). Sequential model-based optimization for general algorithm configuration, Learning...
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computer science and operations research, approximation algorithms are efficient algorithms that find approximate solutions to optimization problems...
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Nelder–Mead method (redirect from Nelder-Mead algorithm)
shrink the simplex towards a better point. An intuitive explanation of the algorithm from "Numerical Recipes": The downhill simplex method now takes a series...
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Dinic's algorithm or Dinitz's algorithm is a strongly polynomial algorithm for computing the maximum flow in a flow network, conceived in 1970 by Israeli...
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Combinatorial optimization (redirect from Combinatorial optimization algorithms)
tractable, and so specialized algorithms that quickly rule out large parts of the search space or approximation algorithms must be resorted to instead....
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