## Probabilistic inductive inference: a survey

*Ambainis, Andris*;

- Publisher: Elsevier BV
- Journal: Theoretical Computer Science,volume 264,issue 1,pages155-167 (issn: 0304-3975)
Related identifiers: doi: 10.1016/s0304-3975(00)00218-8 - Subject: Theoretical Computer Science | Mathematics - Logic | Computer Science(all) | Computer Science - Computational Complexity | F.1.1., F.4.1., I.2.3., I.2.6 | Computer Science - Logic in Computer Science | Computer Science - Learningacm: TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES

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[3] A. Ambainis, K. Aps¯ıtis, R. Freivalds, W. Gasarch, and C. H. Smith. Team learning as a game. In Ming Li and Akira Maruoka, editors, Proceedings of the 8th International Workshop on Algorithmic Learning Theory (ALT-97), volume 1316 of LNAI, pages 2-17, Berlin, October 6-8 1997. Springer.

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[7] K. Aps¯ıtis, R. Freivalds, and C. H. Smith Asymmetric team learning. In Proceedings of the Tenth Annual Conference on Computational Learning Theory, pages 90-95. ACM Press, 1997.

[8] R. Daley and B. Kalyanasundaram. Use of reduction arguments in determining Popperian FIN-type learning capabilities. In K. Jantke, S. Kobayashi, E. Tomita, and T. Yokomori, editors, Algorithmic Learning Theory: Fourth International Workshop (ALT '93), volume 744 of Lecture Notes in Artificial Intelligence, pages 173-186. Springer-Verlag, 1993.

[9] R. Daley and B. Kalyanasundaram. Towards reduction arguments for FINite learning. In K. Jantke and S. Lange, editors, Algorithmic Learning for Knowledge-Based Systems, volume 961 of Lecture Notes in Artificial Intelligence, pages 63-74. Springer-Verlag, 1995.

[10] R. Daley, B. Kalyanasundaram, and M. Velauthapillai. The power of probabilism in Popperian finite learning. In Analogical and Inductive Inference, Proceedings of the Third International Workshop, volume 642 of Lecture Notes in Artificial Intelligence, pages 151-169. Springer-Verlag, 1992.

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