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Robust learning aided by context
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Source Annual Workshop on Computational Learning Theory archive
Proceedings of the eleventh annual conference on Computational learning theory table of contents
Madison, Wisconsin, United States
Pages: 44 - 55  
Year of Publication: 1998
ISBN:1-58113-057-0
Authors
John Case  Department of CIS, University of Delaware, Newark, DE
Sanjay Jain  Department of Information Systems and Computer Science, National University of Singapore, Singapore 119260, Republic of Singapore
Matthias Ott  Institut für Logik, Komplexität und Deduktionssysteme Universität Karlsruhe, 76128 Karlsruhe, Germany
Arun Sharma  School of Computer Science and Engineering, University of New South Wales, Sydney 2052, Australia
Frank Stephan  Mathematisches Institut, Universität Heidelberg, 69120 Heidelberg, Germany
Sponsors
University of Wisconsin : University of Wisconsin
UC @ Santa Cruz : UC @ Santa Cruz
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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R. A. Caruana. Multitask connectionist learning. In Proceedings of the 1993 Connectioni.st Models Summer School, pages 372 379, 1993.
 
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R. A. Caruana. Algorithms and applications for multitask learning. In Proceedings 13th International Conference on Machine Learning, pages 87- 95. Morgan Kaufmann, 1996.
 
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L. Fortnow, W. Gasarch, S. Jain, E. Kinber, M. Kmnmer, S. Kurtz, M. Pleszkoeh, T. Slaman, R. Solovay, and F. Stephan. Extremes in the degrees of inferability. Annals of Pure and Applied Logic, 66:21-276, 1994.
 
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Collaborative Colleagues:
John Case: colleagues
Sanjay Jain: colleagues
Matthias Ott: colleagues
Arun Sharma: colleagues
Frank Stephan: colleagues

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