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Sindhwani et al., 2006 - Google Patents

Large scale semi-supervised linear SVMs

Sindhwani et al., 2006

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Document ID
7053656856724540025
Author
Sindhwani V
Keerthi S
Publication year
Publication venue
Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval

External Links

Snippet

Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In many information retrieval and data mining applications, linear classifiers are strongly preferred …
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Classifications

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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G06K9/627—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches based on distances between the pattern to be recognised and training or reference patterns
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