### Abstract

We design efficient on-line algorithms that predict nearly as well as the best pruning of a planar decision graph. We assume that the graph has no cycles. As in the previous work on decision trees, we implicitly maintain one weight for each of the prunings (exponentially many). The method works for a large class of algorithms that update its weights multiplicatively. It can also be used to design algorithms that predict nearly as well as the best convex combination of prunings.

Original language | English |
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Title of host publication | Algorithmic Learning Theory - 10th International Conference, ALT 1999, Proceedings |

Editors | Osamu Watanabe, Takashi Yokomori |

Publisher | Springer Verlag |

Pages | 335-346 |

Number of pages | 12 |

ISBN (Print) | 3540667482, 9783540667483 |

Publication status | Published - Jan 1 1999 |

Externally published | Yes |

Event | 10th International Conference on Algorithmic Learning Theory, ALT 1999 - Tokyo, Japan Duration: Dec 6 1999 → Dec 8 1999 |

### Publication series

Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 1720 |

ISSN (Print) | 0302-9743 |

ISSN (Electronic) | 1611-3349 |

### Other

Other | 10th International Conference on Algorithmic Learning Theory, ALT 1999 |
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Country | Japan |

City | Tokyo |

Period | 12/6/99 → 12/8/99 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Theoretical Computer Science
- Computer Science(all)

### Cite this

*Algorithmic Learning Theory - 10th International Conference, ALT 1999, Proceedings*(pp. 335-346). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1720). Springer Verlag.

**Predicting nearly as well as the best pruning of a planar decision graph.** / Takimoto, Eiji; Warmuth, Manfred K.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Algorithmic Learning Theory - 10th International Conference, ALT 1999, Proceedings.*Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1720, Springer Verlag, pp. 335-346, 10th International Conference on Algorithmic Learning Theory, ALT 1999, Tokyo, Japan, 12/6/99.

}

TY - GEN

T1 - Predicting nearly as well as the best pruning of a planar decision graph

AU - Takimoto, Eiji

AU - Warmuth, Manfred K.

PY - 1999/1/1

Y1 - 1999/1/1

N2 - We design efficient on-line algorithms that predict nearly as well as the best pruning of a planar decision graph. We assume that the graph has no cycles. As in the previous work on decision trees, we implicitly maintain one weight for each of the prunings (exponentially many). The method works for a large class of algorithms that update its weights multiplicatively. It can also be used to design algorithms that predict nearly as well as the best convex combination of prunings.

AB - We design efficient on-line algorithms that predict nearly as well as the best pruning of a planar decision graph. We assume that the graph has no cycles. As in the previous work on decision trees, we implicitly maintain one weight for each of the prunings (exponentially many). The method works for a large class of algorithms that update its weights multiplicatively. It can also be used to design algorithms that predict nearly as well as the best convex combination of prunings.

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UR - http://www.scopus.com/inward/citedby.url?scp=84937394882&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84937394882

SN - 3540667482

SN - 9783540667483

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 335

EP - 346

BT - Algorithmic Learning Theory - 10th International Conference, ALT 1999, Proceedings

A2 - Watanabe, Osamu

A2 - Yokomori, Takashi

PB - Springer Verlag

ER -