About: Frank–Wolfe algorithm

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The Frank–Wolfe algorithm is an iterative first-order optimization algorithm for constrained convex optimization. Also known as the conditional gradient method, reduced gradient algorithm and the convex combination algorithm, the method was originally proposed by Marguerite Frank and Philip Wolfe in 1956. In each iteration, the Frank–Wolfe algorithm considers a linear approximation of the objective function, and moves towards a minimizer of this linear function (taken over the same domain).

Attributes	Values
rdf:type	software
rdfs:label	Frank–Wolfe algorithm (en)
rdfs:comment	The Frank–Wolfe algorithm is an iterative first-order optimization algorithm for constrained convex optimization. Also known as the conditional gradient method, reduced gradient algorithm and the convex combination algorithm, the method was originally proposed by Marguerite Frank and Philip Wolfe in 1956. In each iteration, the Frank–Wolfe algorithm considers a linear approximation of the objective function, and moves towards a minimizer of this linear function (taken over the same domain). (en)
sameAs	Frank–Wolfe algorithm
dbp:wikiPageUsesTemplate	dbt:Cite_book dbt:Cite_journal dbt:Reflist dbt:Optimization_algorithms
Subject	Iterative methods Optimization algorithms and methods First order methods Gradient methods
thumbnail	wiki-commons:Special:FilePath/Frank-Wolfe_Algorithm.png?width=300
foaf:depiction
gold:hypernym	Algorithm
prov:wasDerivedFrom	http://en.wikipedia.org/wiki/Frank–Wolfe_algorithm?oldid=1019730027&ns=0
Wikipage page ID	3152055 (xsd:integer)
page length (characters) of wiki page	8391 (xsd:nonNegativeInteger)
Wikipage revision ID	1019730027 (xsd:integer)
Link from a Wikipage to another Wikipage	Flow network Machine learning Projection (mathematics) Proximal gradient method Algorithm Taylor series Iterative methods Optimization algorithms and methods Differentiable function Duality gap Linear approximation Linear programming Lipschitz continuity Philip Wolfe (mathematician) Springer Science+Business Media Compact space Constrained optimization Convex function Convex optimization Convex set Optimization problem Order of approximation Gradient descent Transport network analysis Vector space Iterative method First order methods Marguerite Frank Mathematical optimization Real-valued function Signal processing Gradient methods
has abstract	The Frank–Wolfe algorithm is an iterative first-order optimization algorithm for constrained convex optimization. Also known as the conditional gradient method, reduced gradient algorithm and the convex combination algorithm, the method was originally proposed by Marguerite Frank and Philip Wolfe in 1956. In each iteration, the Frank–Wolfe algorithm considers a linear approximation of the objective function, and moves towards a minimizer of this linear function (taken over the same domain). (en)
foaf:isPrimaryTopicOf	http://en.wikipedia.org/wiki/Frank–Wolfe_algorithm
is Wikipage redirect of	Frank-Wolfe algorithm Conditional gradient method Frank-Wolfe
is Link from a Wikipage to another Wikipage of	Frank-Wolfe algorithm Frank Wolfe Active-set method List of numerical analysis topics Conditional gradient method John Glen Wardrop List of algorithms Gradient method Frank-Wolfe Marguerite Frank Mathematical optimization
is foaf:primaryTopic of	http://en.wikipedia.org/wiki/Frank–Wolfe_algorithm

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