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Language learning with some negative information

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STACS 93 (STACS 1993)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 665))

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References

  1. D. Angluin. Inductive inference of formal languages from positive data.-Information and Control, 45:117–135, 1980.

    Google Scholar 

  2. L. Blum and M. Blum. Toward a mathematical theory of inductive inference. Information and Control, 28:125–155, 1975.

    Google Scholar 

  3. G. Baliga, J. Case, and S. Jain. Language learning with some negative information. Technical Report TR.-92-27, University of Delaware, May 1992.

    Google Scholar 

  4. M. Blum. A machine independent theory of the complexity of recursive functions. Journal of the ACM, 14:322–336, 1967.

    Google Scholar 

  5. J. Case. Learning machines. In W. Demopoulos and A. Marras, editors, Language Learning and Concept Acquisition. Ablex Publishing Company, 1986.

    Google Scholar 

  6. J. Case. The power of vacillation. In D. Haussler and L. Pitt, editors, Proceedings of the Workshop on Computational Learning Theory, pages 133–142. Morgan Kaufmann Publishers, Inc., 1988. Expanded in [Cas92].

    Google Scholar 

  7. J. Case. The power of vacillation in language learning. Technical Report 93-08, University of Delaware, 1992. Expands on [Cas88]; journal article under review.

    Google Scholar 

  8. J. Case and C. Lynes. Machine inductive inference and language identification. In M. Nielsen and E. M. Schmidt, editors, Proceedings of the 9th International Colloquium on Automata, Languages and Programming, volume 140, pages 107–115. Springer-Verlag, Berlin, 1982.

    Google Scholar 

  9. J. Case and C. Smith. Comparison of identification criteria for machine inductive inference. Theoretical Computer Science, 25:193–220, 1983.

    Google Scholar 

  10. M. Fulk. A Study of Inductive Inference machines. PhD thesis, SUNY at Buffalo, 1985.

    Google Scholar 

  11. M. Fulk. Prudence and other conditions on formal language learning. Information and Computation, 85:1–11, 1990.

    Google Scholar 

  12. E. M. Gold. Language identification in the limit. Information and Control, 10:447–474, 1967.

    Google Scholar 

  13. J. Hopcroft and J. Ullman. Introduction to Automata Theory Languages and Computation. Addison-Wesley Publishing Company, 1979.

    Google Scholar 

  14. S. Jain and A. Sharma. Learning in the presence of partial explanations. Information and Computation, 95-2:162–191, 1991.

    Google Scholar 

  15. D. Moeser and A. Bregman. The role of reference in the acquisition of a miniature artificial language. Journal of Verbal Learning and Verbal Behavior, 11:759–769, 1972.

    Google Scholar 

  16. D. Moeser and A. Bregman. Imagery and language acquisition. Journal of Verbal Learning and Verbal Behavior, 12:91–98, 1973.

    Google Scholar 

  17. D. McNeill. Developmental psycholinguistics. In F. Smith and G. A. Miller, editors, The Genesis of Language, pages 15–84. MIT Press, 1966.

    Google Scholar 

  18. E. Mendelson. Introduction to Mathematical Logic. Brooks-Cole, San Francisco, 1986. 3rd Edition.

    Google Scholar 

  19. T. Motoki. Inductive inference from all positive and some negative data. Unpublished, 1992.

    Google Scholar 

  20. M. Machtey and P. Young. An Introduction to the General Theory of Algorithms. North Holland, New York, 1978.

    Google Scholar 

  21. D. Osherson, M. Stob, and S. Weinstein. Ideal learning machines. Cognitive Science, 6:277–290, 1982.

    Google Scholar 

  22. D. Osherson, M. Stob, and S. Weinstein. Learning theory and natural language. Cognition, 17:1–28, 1984.

    Google Scholar 

  23. D. Osherson, M. Stob, and S. Weinstein. Systems that Learn, An Introduction to Learning Theory for Cognitive and Computer Scientists. MIT Press, Cambridge, Mass., 1986.

    Google Scholar 

  24. D. Osherson and S. Weinstein. Criteria of language learning. Information and Control, 52:123–138, 1982.

    Google Scholar 

  25. D. Osherson and S. Weinstein. A note on formal learning theory. Cognition, 11:77–88, 1982.

    Google Scholar 

  26. S. Pinker. Formal models of language learning. Cognition, 7:217–283, 1979.

    Google Scholar 

  27. H. Rogers. Gödel numberings of partial recursive functions. Journal of Symbolic Logic, 23:331–341, 1958.

    Google Scholar 

  28. H. Rogers. Theory of Recursive Functions and Effective Computability. Mc-Graw Hill, New York, 1967. Reprinted, MIT Press 1987.

    Google Scholar 

  29. T. Shinohara. Studies on Inductive Inference from Positive Data. PhD thesis, Kyushu University, Kyushu, Japan, 1986.

    Google Scholar 

  30. K. Wexler and P. Culicover. Formal Principles of Language Acquisition. MIT Press, Cambridge, Mass, 1980.

    Google Scholar 

  31. K. Wexler. On extensional learnability. Cognition, 11:89–95, 1982.

    Google Scholar 

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P. Enjalbert A. Finkel K. W. Wagner

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© 1993 Springer-Verlag Berlin Heidelberg

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Baliga, G., Case, J., Jain, S. (1993). Language learning with some negative information. In: Enjalbert, P., Finkel, A., Wagner, K.W. (eds) STACS 93. STACS 1993. Lecture Notes in Computer Science, vol 665. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56503-5_66

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  • DOI: https://doi.org/10.1007/3-540-56503-5_66

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-56503-1

  • Online ISBN: 978-3-540-47574-3

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