Improved streaming algorithms for maximizing monotone submodular functions under a knapsack constraint

Chien Chung Huang, Naonori Kakimura

研究成果: Conference contribution

抄録

In this paper, we consider the problem of maximizing a monotone submodular function subject to a knapsack constraint in the streaming setting. In particular, the elements arrive sequentially and at any point of time, the algorithm has access only to a small fraction of the data stored in primary memory. For this problem, we propose a (0.4 - ε) -approximation algorithm requiring only a single pass through the data. This improves on the currently best (0.363 - ε) -approximation algorithm. The required memory space depends only on the size of the knapsack capacity and ε.

本文言語English
ホスト出版物のタイトルAlgorithms and Data Structures - 16th International Symposium, WADS 2019, Proceedings
編集者Zachary Friggstad, Mohammad R. Salavatipour, Jörg-Rüdiger Sack
出版社Springer Verlag
ページ438-451
ページ数14
ISBN(印刷版)9783030247652
DOI
出版ステータスPublished - 2019 1 1
イベント16th International Symposium on Algorithms and Data Structures, WADS 2019 - Edmonton, Canada
継続期間: 2019 8 52019 8 7

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11646 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference16th International Symposium on Algorithms and Data Structures, WADS 2019
CountryCanada
CityEdmonton
Period19/8/519/8/7

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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