### Abstract

We consider the problem of minimizing regret with respect to a given set S of pairs of time selection functions and modifications rules. We give an online algorithm that has O(√ T log |S|) regret with respect to S when the algorithm is run for T time steps and there are N actions allowed. This improves the upper bound of O(√ TNlog(|I||F|)) given by Blum and Mansour [BM07a] for the case when S = I × for a set I of time selection functions and a set F of modification rules. We do so by giving a simple reduction that uses an online algorithm for external regret as a black box.

Original language | English (US) |
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Title of host publication | 21st Annual Conference on Learning Theory, COLT 2008 |

Pages | 81-86 |

Number of pages | 6 |

State | Published - 2008 |

Event | 21st Annual Conference on Learning Theory, COLT 2008 - Helsinki, Finland Duration: Jul 9 2008 → Jul 12 2008 |

### Other

Other | 21st Annual Conference on Learning Theory, COLT 2008 |
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Country | Finland |

City | Helsinki |

Period | 7/9/08 → 7/12/08 |

### Fingerprint

### ASJC Scopus subject areas

- Education

### Cite this

*21st Annual Conference on Learning Theory, COLT 2008*(pp. 81-86)

**Minimizing wide range regret with time selection functions.** / Khot, Subhash; Ponnuswami, Ashok Kumar.

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

*21st Annual Conference on Learning Theory, COLT 2008.*pp. 81-86, 21st Annual Conference on Learning Theory, COLT 2008, Helsinki, Finland, 7/9/08.

}

TY - GEN

T1 - Minimizing wide range regret with time selection functions

AU - Khot, Subhash

AU - Ponnuswami, Ashok Kumar

PY - 2008

Y1 - 2008

N2 - We consider the problem of minimizing regret with respect to a given set S of pairs of time selection functions and modifications rules. We give an online algorithm that has O(√ T log |S|) regret with respect to S when the algorithm is run for T time steps and there are N actions allowed. This improves the upper bound of O(√ TNlog(|I||F|)) given by Blum and Mansour [BM07a] for the case when S = I × for a set I of time selection functions and a set F of modification rules. We do so by giving a simple reduction that uses an online algorithm for external regret as a black box.

AB - We consider the problem of minimizing regret with respect to a given set S of pairs of time selection functions and modifications rules. We give an online algorithm that has O(√ T log |S|) regret with respect to S when the algorithm is run for T time steps and there are N actions allowed. This improves the upper bound of O(√ TNlog(|I||F|)) given by Blum and Mansour [BM07a] for the case when S = I × for a set I of time selection functions and a set F of modification rules. We do so by giving a simple reduction that uses an online algorithm for external regret as a black box.

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UR - http://www.scopus.com/inward/citedby.url?scp=80053150692&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:80053150692

SP - 81

EP - 86

BT - 21st Annual Conference on Learning Theory, COLT 2008

ER -