On the mathematical foundations of learning

Felipe Cucker; Steve Smale

doi:https://doi.org/10.1090/s0273-0979-01-00923-5

On the mathematical foundations of learning

2001 · Bulletin of the American Mathematical Society · 1,593 citations · 2 from inside this corpus

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.

5 of 5 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.

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Citation edge evidence

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Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Ex…→On the mathematical foundations of learningLegacy edge — source detail unavailable
Random Features for Large-Scale Kernel Machines→On the mathematical foundations of learningLegacy edge — source detail unavailable
On the mathematical foundations of learning→Statistical Learning TheoryLegacy edge — source detail unavailable
On the mathematical foundations of learning→Neural networks for pattern recognitionLegacy edge — source detail unavailable
On the mathematical foundations of learning→Neural Networks for Pattern RecognitionLegacy edge — source detail unavailable
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Ex…→Statistical Learning TheoryLegacy edge — source detail unavailable

What this paper cites, inside the corpus

Paper	Year	Cited
Statistical Learning Theory	1999	26,957
Neural networks for pattern recognition	1994	18,720
Neural Networks for Pattern Recognition	1995	12,273

What cites it, inside the corpus

Paper	Year	Cited
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Ex…	2006	3,266
Random Features for Large-Scale Kernel Machines	2007	2,646

Links

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Topics

Machine Learning and Algorithms	Computer Science
Neural Networks and Applications	Computer Science
Computability, Logic, AI Algorithms	Computer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

supports2 author record(s) attached.
supports62 reference(s) recorded.
neutralThe DOI carries no year to check against.
supportsA title is present.

Provenance

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