Method and apparatus for providing fast kernel learning on...

Data processing: artificial intelligence – Machine learning

Reexamination Certificate

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C706S048000

Reexamination Certificate

active

07664713

ABSTRACT:
A method and apparatus based on transposition to speed up learning computations on sparse data are disclosed. For example, the method receives an support vector comprising at least one feature represented by one non-zero entry. The method then identifies at least one column within a matrix with non-zero entries, wherein the at least one column is identified in accordance with the at least one feature of the support vector. The method then performs kernel computations using successive list merging on the at least one identified column of the matrix and the support vector to derive a result vector, wherein the result vector is used in a data learning function.

REFERENCES:
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Kudo,T. et al. “Fast Methods for Kernel-based Text Analysis” Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics, Jul. 2003.
Goharian,N. et al. “Comparative Analysis of Sparse Matrix Algorithms for Information Retrieval” Journal of Systemics, Cybernetics and Informatics, vol. 1, No. 1. 2003.
Haffner,P. “Fast Transpose Methods for Kernel Learning on Sparse Data” Proceedings of the 23rd International Conference on Machine Learning. Jun. 25-29, 2006.
Toledo,S. “Improving teh memory-system performance of sparse-matrix vector multiplication” IBM Journal of Research and Development. 1997.

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