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Article
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https://doi.org/10.1007/113621...
Part of book or chapter of book . 2005 . Peer-reviewed
Data sources: Crossref
https://doi.org/10.1109/icnnb....
Article . 2006 . Peer-reviewed
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The Mathematics of Learning: Dealing with Data *

The mathematics of learning: dealing with data.
descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Article 27 Sep 2005Publisher:Springer Berlin HeidelbergJournal:2005 International Conference on Neural Networks and Brain, volume 1, pages PL-5
Authors: Poggio, Tomaso; Smale, Steve;

doi: 10.1007/11362197_1 , 10.1109/icnnb.2005.1614546

The Mathematics of Learning: Dealing with Data *

Abstract

Summary: A key to extracting useful information from large quantities of data is to program machines to learn from examples. The authors outline the mathematical foundations of learning theory and describe one important algorithm.

Related Organizations
Keywords

Classification and discrimination; cluster analysis (statistical aspects), Learning and adaptive systems in artificial intelligence, Computational learning theory

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 12
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    		 Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    		 Average
Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Top 10%
Average