Who Cited It

What Size Net Gives Valid Generalization?

1989 · Neural Computation · 1,559 citations · 16 from inside this corpus

Eric B. Baum, David Haussler

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

What Size Net Gives Valid Generalization? (1989)What Size Net Gives Valid Gen…Learnability and the Vapnik-Chervonenkis dimension (1989)Learnability and the Vapnik-C…Parallel Networks that Learn to Pronounce English Text (1987)Parallel Networks that Learn …Connectionist learning procedures (1989)Connectionist learning proced…Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm (1988)Learning Quickly When Irrelev…Deep learning in neural networks: An overview (2014)Deep learning in neural netwo…Approximation by superpositions of a sigmoidal function (1989)Approximation by superpositio…A training algorithm for optimal margin classifiers (1992)A training algorithm for opti…Neural Networks and the Bias/Variance Dilemma (1992)Neural Networks and the Bias/…Artificial neural networks: fundamentals, computing, design, and application (2000)Artificial neural networks: f…A Short Introduction to Boosting (1999)A Short Introduction to Boost…Optimal Brain Damage (1989)Optimal Brain DamageImproved boosting algorithms using confidence-rated predictions (1998)Improved boosting algorithms …Boosting the margin: a new explanation for the effectiveness of voting methods (1998)Boosting the margin: a new ex…30 years of adaptive neural networks: perceptron, Madaline, and backpropagation (1990)30 years of adaptive neural n…The Boosting Approach to Machine Learning: An Overview (2003)The Boosting Approach to Mach…Improved Boosting Algorithms Using Confidence-rated Predictions (1999)Improved Boosting Algorithms …Fundamentals of Artificial Neural Networks (1996)Fundamentals of Artificial Ne…Learnability and the Vapnik-Chervonenkis dimension (1989)Learnability and the Vapnik-C…Pruning algorithms-a survey (1993)Pruning algorithms-a surveyNeural networks for classification: a survey (2000)Neural networks for classific…
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What this paper cites, inside the corpus

PaperYearCited
Learnability and the Vapnik-Chervonenkis dimension19891,855
Parallel Networks that Learn to Pronounce English Text19871,557
Connectionist learning procedures19891,466
Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm19881,382

What cites it, inside the corpus

PaperYearCited
Deep learning in neural networks: An overview201418,236
Approximation by superpositions of a sigmoidal function198913,884
A training algorithm for optimal margin classifiers199211,664
Neural Networks and the Bias/Variance Dilemma19923,612
Artificial neural networks: fundamentals, computing, design, and application20003,250
A Short Introduction to Boosting19992,952
Optimal Brain Damage19892,606
Improved boosting algorithms using confidence-rated predictions19982,573
Boosting the margin: a new explanation for the effectiveness of voting methods19982,344
30 years of adaptive neural networks: perceptron, Madaline, and backpropagation19902,244
The Boosting Approach to Machine Learning: An Overview20032,023
Improved Boosting Algorithms Using Confidence-rated Predictions19991,966
Fundamentals of Artificial Neural Networks19961,902
Learnability and the Vapnik-Chervonenkis dimension19891,855
Pruning algorithms-a survey19931,717
Neural networks for classification: a survey20001,672

Links

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Topics

Machine Learning and AlgorithmsComputer Science
Machine Learning and Data ClassificationComputer Science
Domain Adaptation and Few-Shot LearningComputer Science

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complete

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  • supports2 author record(s) attached.
  • supports32 reference(s) recorded.
  • supportsThe DOI's year agrees with the publication year.
  • supportsA title is present.

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