DOI: 10.1162/08997660260293274. A New Discriminative Kernel from Probabilistic Models

A New Discriminative Kernel from Probabilistic Models

10.1162/08997660260293274

Crossref journal-article

MIT Press - Journals

Neural Computation (281)

Abstract

Recently, Jaakkola and Haussler (1999) proposed a method for constructing kernel functions from probabilistic models. Their so-called Fisher kernel has been combined with discriminative classifiers such as support vector machines and applied successfully in, for example, DNA and protein analysis. Whereas the Fisher kernel is calculated from the marginal log-likelihood, we propose the TOP kernel derived from tangent vectors of posterior log-odds. Furthermore, we develop a theoretical framework on feature extractors from probabilistic models and use it for analyzing the TOP kernel. In experiments, our new discriminative TOP kernel compares favorably to the Fisher kernel.

Bibliography

Tsuda, K., Kawanabe, M., RÃ¤tsch, G., Sonnenburg, S., & MÃ¼ller, K.-R. (2002). A New Discriminative Kernel from Probabilistic Models. Neural Computation, 14(10), 2397â2414.

Authors 5

Koji Tsuda (first)
Motoaki Kawanabe (additional)
Gunnar Rätsch (additional)
Sören Sonnenburg (additional)
Klaus-Robert Müller (additional)

References 6 Referenced 74

Dates

Type	When
Created	22 years, 10 months ago (Oct. 11, 2002, 12:52 a.m.)
Deposited	4 years, 5 months ago (March 12, 2021, 4:49 p.m.)
Indexed	1 month ago (Aug. 3, 2025, 7:03 p.m.)
Issued	22 years, 11 months ago (Oct. 1, 2002)
Published	22 years, 11 months ago (Oct. 1, 2002)
Published Print	22 years, 11 months ago (Oct. 1, 2002)

Funders 0

None

BibTeX

@article{Tsuda_2002, title={A New Discriminative Kernel from Probabilistic Models}, volume={14}, ISSN={1530-888X}, url={http://dx.doi.org/10.1162/08997660260293274}, DOI={10.1162/08997660260293274}, number={10}, journal={Neural Computation}, publisher={MIT Press - Journals}, author={Tsuda, Koji and Kawanabe, Motoaki and Rätsch, Gunnar and Sonnenburg, Sören and Müller, Klaus-Robert}, year={2002}, month=oct, pages={2397–2414} }

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