### Abstract

A new upper bound on the relative entropy is derived as a function of the total variation distance for probability measures defined on a common finite alphabet. The bound improves a previously reported bound by Csiszár and Talata. It is further extended to an upper bound on the Rényi divergence of an arbitrary non-negative order (including ∞) as a function of the total variation distance.

Original language | English (US) |
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Title of host publication | ITW 2015 - 2015 IEEE Information Theory Workshop |

Publisher | Institute of Electrical and Electronics Engineers Inc. |

Pages | 214-218 |

Number of pages | 5 |

ISBN (Electronic) | 9781467378529 |

DOIs | |

State | Published - Dec 17 2015 |

Event | IEEE Information Theory Workshop, ITW 2015 - Jeju Island, Korea, Republic of Duration: Oct 11 2015 → Oct 15 2015 |

### Publication series

Name | ITW 2015 - 2015 IEEE Information Theory Workshop |
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### Other

Other | IEEE Information Theory Workshop, ITW 2015 |
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Country | Korea, Republic of |

City | Jeju Island |

Period | 10/11/15 → 10/15/15 |

### All Science Journal Classification (ASJC) codes

- Information Systems

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## Cite this

Sason, I., & Verdu, S. (2015). Upper bounds on the relative entropy and Rényi divergence as a function of total variation distance for finite alphabets. In

*ITW 2015 - 2015 IEEE Information Theory Workshop*(pp. 214-218). [7360766] (ITW 2015 - 2015 IEEE Information Theory Workshop). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITWF.2015.7360766