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- Universal_approximation_theorem abstract "In the mathematical theory of artificial neural networks, the universal approximation theorem states that a feed-forward network with a single hidden layer containing a finite number of neurons (i.e., a multilayer perceptron), can approximate continuous functions on compact subsets of Rn, under mild assumptions on the activation function. The theorem thus states that simple neural networks can represent a wide variety of interesting functions when given appropriate parameters; however, it does not touch upon the algorithmic learnability of those parameters.One of the first versions of the theorem was proved by George Cybenko in 1989 for sigmoid activation functions.Kurt Hornik showed in 1991 that it is not the specific choice of the activation function, but rather the multilayer feedforward architecture itself which gives neural networks the potential of being universal approximators. The output units are always assumed to be linear. For notational convenience, only the single output case will be shown. The general case can easily be deduced from the single output case.".
- Universal_approximation_theorem wikiPageExternalLink chap4.html.
- Universal_approximation_theorem wikiPageID "18543448".
- Universal_approximation_theorem wikiPageLength "3773".
- Universal_approximation_theorem wikiPageOutDegree "25".
- Universal_approximation_theorem wikiPageRevisionID "699980753".
- Universal_approximation_theorem wikiPageWikiLink Artificial_neural_network.
- Universal_approximation_theorem wikiPageWikiLink Bounded_function.
- Universal_approximation_theorem wikiPageWikiLink Category:Artificial_neural_networks.
- Universal_approximation_theorem wikiPageWikiLink Category:Information,_knowledge,_and_uncertainty.
- Universal_approximation_theorem wikiPageWikiLink Category:Network_architecture.
- Universal_approximation_theorem wikiPageWikiLink Category:Networks.
- Universal_approximation_theorem wikiPageWikiLink Category:Neural_networks.
- Universal_approximation_theorem wikiPageWikiLink Category:Theorems_in_discrete_mathematics.
- Universal_approximation_theorem wikiPageWikiLink Compact_space.
- Universal_approximation_theorem wikiPageWikiLink Computational_learning_theory.
- Universal_approximation_theorem wikiPageWikiLink Continuous_function.
- Universal_approximation_theorem wikiPageWikiLink Dense_set.
- Universal_approximation_theorem wikiPageWikiLink Euclidean_space.
- Universal_approximation_theorem wikiPageWikiLink Feedforward_neural_network.
- Universal_approximation_theorem wikiPageWikiLink George_Cybenko.
- Universal_approximation_theorem wikiPageWikiLink Mathematics.
- Universal_approximation_theorem wikiPageWikiLink Monotonic_function.
- Universal_approximation_theorem wikiPageWikiLink Multilayer_perceptron.
- Universal_approximation_theorem wikiPageWikiLink Neuron.
- Universal_approximation_theorem wikiPageWikiLink No_free_lunch_theorem.
- Universal_approximation_theorem wikiPageWikiLink Representation_theorem.
- Universal_approximation_theorem wikiPageWikiLink Sigmoid_function.
- Universal_approximation_theorem wikiPageWikiLink Theorem.
- Universal_approximation_theorem wikiPageWikiLink Unit_cube.
- Universal_approximation_theorem wikiPageWikiLinkText "Universal approximation theorem".
- Universal_approximation_theorem wikiPageWikiLinkText "approximate".
- Universal_approximation_theorem wikiPageWikiLinkText "universal approximation theorem".
- Universal_approximation_theorem wikiPageWikiLinkText "universal approximation".
- Universal_approximation_theorem wikiPageUsesTemplate Template:Applied-math-stub.
- Universal_approximation_theorem wikiPageUsesTemplate Template:Reflist.
- Universal_approximation_theorem subject Category:Artificial_neural_networks.
- Universal_approximation_theorem subject Category:Information,_knowledge,_and_uncertainty.
- Universal_approximation_theorem subject Category:Network_architecture.
- Universal_approximation_theorem subject Category:Networks.
- Universal_approximation_theorem subject Category:Neural_networks.
- Universal_approximation_theorem subject Category:Theorems_in_discrete_mathematics.
- Universal_approximation_theorem type Network.
- Universal_approximation_theorem type Redirect.
- Universal_approximation_theorem type Theorem.
- Universal_approximation_theorem comment "In the mathematical theory of artificial neural networks, the universal approximation theorem states that a feed-forward network with a single hidden layer containing a finite number of neurons (i.e., a multilayer perceptron), can approximate continuous functions on compact subsets of Rn, under mild assumptions on the activation function.".
- Universal_approximation_theorem label "Universal approximation theorem".
- Universal_approximation_theorem sameAs Q7894110.
- Universal_approximation_theorem sameAs مبرهنة_التقريب_العام.
- Universal_approximation_theorem sameAs 시벤코_정리.
- Universal_approximation_theorem sameAs m.04f_wtc.
- Universal_approximation_theorem sameAs Теорема_Цыбенко.
- Universal_approximation_theorem sameAs Теорема_Цибенко.
- Universal_approximation_theorem sameAs Q7894110.
- Universal_approximation_theorem wasDerivedFrom Universal_approximation_theorem?oldid=699980753.
- Universal_approximation_theorem isPrimaryTopicOf Universal_approximation_theorem.