### Abstract

A population learning model is introduced. In this model a population learner is provided with an oracle that on each call produces a function that is consistent with an independent random sample of the unknown target function. Thus, each call to the hypothesis oracle causes a new sample of m random examples to be drawn, and for a function consistent with these m examples to be returned to the population learner.

Original language | English (US) |
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Title of host publication | Proc 6 Annu ACM Conf Comput Learn Theory |

Publisher | Publ by ACM |

Pages | 101-110 |

Number of pages | 10 |

ISBN (Print) | 0897916115, 9780897916110 |

DOIs | |

State | Published - 1993 |

Externally published | Yes |

Event | Proceedings of the 6th Annual ACM Conference on Computational Learning Theory - Santa Cruz, CA, USA Duration: Jul 26 1993 → Jul 28 1993 |

### Publication series

Name | Proc 6 Annu ACM Conf Comput Learn Theory |
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### Other

Other | Proceedings of the 6th Annual ACM Conference on Computational Learning Theory |
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City | Santa Cruz, CA, USA |

Period | 7/26/93 → 7/28/93 |

### All Science Journal Classification (ASJC) codes

- Engineering(all)

## Cite this

Kearns, M., & Seung, H. S. (1993). Learning from a population of hypotheses. In

*Proc 6 Annu ACM Conf Comput Learn Theory*(pp. 101-110). (Proc 6 Annu ACM Conf Comput Learn Theory). Publ by ACM. https://doi.org/10.1145/168304.168317