Optimum Intrinsic Randomness Rate with Respect to f -Divergences Using the Smooth Min Entropy

Ryo Nomura, Hideki Yagi

研究成果: Conference contribution

抄録

The intrinsic randomness (IR) problem is considered for general setting. In the literature, the optimum IR rate with respect to the variational distance has been characterized in two ways. One is based on the information spectrum quantity and the other is based on the smooth Rényi entropy. Recently, Nomura has revealed the optimum IR rate with respect to f-divergences, which includes the variational distance, the Kullback-Leibler (KL) divergence and so on, by using the informational spectrum quantity. In this paper, we try to characterize the optimum IR rate with respect to a subclass of f-divergences by using the smooth Min entropy. The subclass of f-divergences considered in this paper includes typical distance measures such as the total variational distance, the KL divergence, the Hellinger distance and so on.

本文言語English
ホスト出版物のタイトル2021 IEEE International Symposium on Information Theory, ISIT 2021 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ページ1784-1789
ページ数6
ISBN(電子版)9781538682098
DOI
出版ステータスPublished - 2021 7 12
イベント2021 IEEE International Symposium on Information Theory, ISIT 2021 - Virtual, Melbourne, Australia
継続期間: 2021 7 122021 7 20

出版物シリーズ

名前IEEE International Symposium on Information Theory - Proceedings
2021-July
ISSN(印刷版)2157-8095

Conference

Conference2021 IEEE International Symposium on Information Theory, ISIT 2021
国/地域Australia
CityVirtual, Melbourne
Period21/7/1221/7/20

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • 情報システム
  • モデリングとシミュレーション
  • 応用数学

フィンガープリント

「Optimum Intrinsic Randomness Rate with Respect to f -Divergences Using the Smooth Min Entropy」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル