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Capabilities of fallible FINite learning

Authors:

Robert Daley,

Bala Kalyanasundaram,

Mahendran VelauthapillaiAuthors Info & Claims

COLT '93: Proceedings of the sixth annual conference on Computational learning theory

Pages 199 - 208

https://doi.org/10.1145/168304.168332

Published: 01 August 1993 Publication History

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References

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R. Daley, and B. Kalyanasundaram, Use of reduction arguments in determining Popperian FINite learning capabilities, In preparation.

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R. Daley, B. Kalyanasundaram, and M. Velauthapillai, Breaking the probability ~ barrier in FIN-type learning, In Proceedings of the 1992 Workshop on Computational Learning Theory, 1992, 203-217.

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Cited By

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Fortnow LFreivalds RGasarch WKummer MKurtz SSmith CStephan F(2005)Measure, category and learning theoryAutomata, Languages and Programming10.1007/3-540-60084-1_105(558-569)Online publication date: 7-Jun-2005
https://doi.org/10.1007/3-540-60084-1_105
Apsītis KFreivalds RSmith CLeighton FGoodrich M(1994)Choosing a learning teamProceedings of the twenty-sixth annual ACM symposium on Theory of Computing10.1145/195058.195158(283-289)Online publication date: 23-May-1994
https://dl.acm.org/doi/10.1145/195058.195158

Index Terms

Capabilities of fallible FINite learning
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Logical and relational learning
        Inductive logic learning
2. Theory of computation
  1. Models of computation
    1. Probabilistic computation

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Published In

COLT '93: Proceedings of the sixth annual conference on Computational learning theory

August 1993

463 pages

ISBN:0897916115

DOI:10.1145/168304

Editor:
Lenny Pitt
Univ. of Illinois, Urbana

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 August 1993

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6COLT93

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6COLT93: 6th Annual Conference on Computational Learning Theory

July 26 - 28, 1993

California, Santa Cruz, USA

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Cited By

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Fortnow LFreivalds RGasarch WKummer MKurtz SSmith CStephan F(2005)Measure, category and learning theoryAutomata, Languages and Programming10.1007/3-540-60084-1_105(558-569)Online publication date: 7-Jun-2005
https://doi.org/10.1007/3-540-60084-1_105
Apsītis KFreivalds RSmith CLeighton FGoodrich M(1994)Choosing a learning teamProceedings of the twenty-sixth annual ACM symposium on Theory of Computing10.1145/195058.195158(283-289)Online publication date: 23-May-1994
https://dl.acm.org/doi/10.1145/195058.195158

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