A general regression technique for learning transductions

Corinna Cortes, Mehryar Mohri, Jason Weston

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The problem of learning a transduction, that is a string-to-string mapping, is a common problem arising in natural language processing and computational biology. Previous methods proposed for learning such mappings are based on classification techniques. This paper presents a new and general regression technique for learning transductions and reports the results of experiments showing its effectiveness. Our transduction learning consists of two phases: the estimation of a set of regression coefficients and the computation of the pre-image corresponding to this set of coefficients. A novel and conceptually cleaner formulation of kernel dependency estimation provides a simple framework for estimating the regression coefficients, and an efficient algorithm for computing the pre-image from the regression coefficients extends the applicability of kernel dependency estimation to output sequences. We report the results of a series of experiments illustrating the application of our regression technique for learning transductions.

Original languageEnglish (US)
Title of host publicationICML 2005 - Proceedings of the 22nd International Conference on Machine Learning
EditorsL. Raedt, S. Wrobel
Pages153-160
Number of pages8
DOIs
StatePublished - 2005
EventICML 2005: 22nd International Conference on Machine Learning - Bonn, Germany
Duration: Aug 7 2005Aug 11 2005

Other

OtherICML 2005: 22nd International Conference on Machine Learning
CountryGermany
CityBonn
Period8/7/058/11/05

Fingerprint

Experiments
Processing

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Cortes, C., Mohri, M., & Weston, J. (2005). A general regression technique for learning transductions. In L. Raedt, & S. Wrobel (Eds.), ICML 2005 - Proceedings of the 22nd International Conference on Machine Learning (pp. 153-160) https://doi.org/10.1145/1102351.1102371

A general regression technique for learning transductions. / Cortes, Corinna; Mohri, Mehryar; Weston, Jason.

ICML 2005 - Proceedings of the 22nd International Conference on Machine Learning. ed. / L. Raedt; S. Wrobel. 2005. p. 153-160.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Cortes, C, Mohri, M & Weston, J 2005, A general regression technique for learning transductions. in L Raedt & S Wrobel (eds), ICML 2005 - Proceedings of the 22nd International Conference on Machine Learning. pp. 153-160, ICML 2005: 22nd International Conference on Machine Learning, Bonn, Germany, 8/7/05. https://doi.org/10.1145/1102351.1102371
Cortes C, Mohri M, Weston J. A general regression technique for learning transductions. In Raedt L, Wrobel S, editors, ICML 2005 - Proceedings of the 22nd International Conference on Machine Learning. 2005. p. 153-160 https://doi.org/10.1145/1102351.1102371
Cortes, Corinna ; Mohri, Mehryar ; Weston, Jason. / A general regression technique for learning transductions. ICML 2005 - Proceedings of the 22nd International Conference on Machine Learning. editor / L. Raedt ; S. Wrobel. 2005. pp. 153-160
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