Beygelzimer, Alina, Langford, John, Lifshits, Yuri, Sorkin, Gregory B. ORCID: 0000-0003-4935-7820 and Strehl, Alex
(2009)
*Conditional probability tree estimation analysis and algorithms.*
In: Uncertainty in artificial intelligence, 2009-06-18 - 2009-06-21, QC, Canada.

## Abstract

We consider the problem of estimating the conditional probability of a label in time $O(\log n)$, where $n$ is the number of possible labels. We analyze a natural reduction of this problem to a set of binary regression problems organized in a tree structure, proving a regret bound that scales with the depth of the tree. Motivated by this analysis, we propose the first online algorithm which provably constructs a logarithmic depth tree on the set of labels to solve this problem. We test the algorithm empirically, showing that it works succesfully on a dataset with roughly $10^6$ labels.

Item Type: | Conference or Workshop Item (Paper) |
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Official URL: | http://uai.sis.pitt.edu/displayArticles.jsp?mmnu=1... |

Additional Information: | © 2009 the Authors |

Divisions: | Management |

Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |

Date Deposited: | 13 May 2011 10:37 |

Last Modified: | 20 Feb 2024 04:12 |

URI: | http://eprints.lse.ac.uk/id/eprint/35637 |

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