(Q56169175)

English

Regularization Theory and Neural Networks Architectures

article by Federico Girosi et al published March 1995 in Neural Computation

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title

Regularization Theory and Neural Networks Architectures (English)

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3

Tomaso Poggio

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author name string

Federico Girosi

series ordinal

1

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Michael Jones

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2

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publication date

March 1995

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published in

Neural Computation

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volume

7

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issue

2

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page(s)

219-269

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cites work

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Neural Networks and the Bias/Variance Dilemma

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A computational theory of visual surface interpolation.

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reference URL

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21 January 2018

Multiquadric equations of topography and other irregular surfaces

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Theory and applications of the multiquadric-biharmonic method 20 years of discovery 1968–1988

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Multilayer feedforward networks are universal approximators

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Synthesizing a color algorithm from examples.

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On Estimating Regression

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A generalized inverse for matrices

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A theory of how the brain might work.

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Regularization algorithms for learning that are equivalent to multilayer networks.

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Computational vision and regularization theory.

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Modeling by shortest data description

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A general regression neural network.

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On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities

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Identifiers

DOI

10.1162/NECO.1995.7.2.219

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DBLP publication ID

journals/neco/GirosiJP95

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DBLP Dataset 2021-01-02

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28 January 2021

ResearchGate publication ID

2246342

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(Q56169175)

Regularization Theory and Neural Networks Architectures

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