On succinct representation of directed graphs

研究成果: Conference contribution

22 被引用数 (Scopus)

抄録

Directed graphs encode meaningful dependencies among objects ubiquitously. This paper introduces new and simple representations for labeled directed graphs with the properties of being succinct (space is information-theoretically optimal); in which we avoid exploiting a-priori knowledge on digraph regularity such as triangularity, separability, planarity, symmetry and sparsity. Our results have direct implications to model directed graphs by using single integer numbers effectively, which is significant to enable canonical (generation of graph instances is unique) and efficient (coding and decoding take polynomial time) encodings for learning and optimization algorithms. To the best of our knowledge, the proposed representations are the first known in the literature.

本文言語English
ホスト出版物のタイトル2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ199-205
ページ数7
ISBN(電子版)9781509030156
DOI
出版ステータスPublished - 2017 3月 17
イベント2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017 - Jeju Island, Korea, Republic of
継続期間: 2017 2月 132017 2月 16

出版物シリーズ

名前2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017

Other

Other2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017
国/地域Korea, Republic of
CityJeju Island
Period17/2/1317/2/16

ASJC Scopus subject areas

  • 情報システム
  • 人工知能
  • コンピュータ サイエンスの応用
  • コンピュータ ビジョンおよびパターン認識

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