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  1. 02 情報科学
  2. 01 学術雑誌論文

A Recursive Framework for Evaluating Moments Using Zero-Suppressed Binary Decision Diagrams

http://hdl.handle.net/10061/0002000778
http://hdl.handle.net/10061/0002000778
68a7e15f-1496-48e3-9831-12cebc871b3f
アイテムタイプ 学術雑誌論文 / Journal Article(1)
公開日 2025-02-17
タイトル
タイトル A Recursive Framework for Evaluating Moments Using Zero-Suppressed Binary Decision Diagrams
言語
言語 eng
キーワード
主題Scheme Other
主題 Discrete optimization
キーワード
主題Scheme Other
主題 family operation
キーワード
主題Scheme Other
主題 method of moments
キーワード
主題Scheme Other
主題 zero-suppressed binary decision diagram
資源タイプ
資源タイプ journal article
アクセス権
アクセス権 open access
著者 Lim, Brian Godwin

× Lim, Brian Godwin

en Lim, Brian Godwin

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Tan, Renzo Roel

× Tan, Renzo Roel

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en Tan, Renzo Roel

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Kawahara, Jun

× Kawahara, Jun

en Kawahara, Jun

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Minato, Shin-Ichi

× Minato, Shin-Ichi

en Minato, Shin-Ichi

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池田, 和司

× 池田, 和司

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e-Rad_Researcher 10262552

ja 池田, 和司

ja-Kana イケダ, カズシ

en Ikeda, Kazushi

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抄録
内容記述タイプ Abstract
内容記述 The zero-suppressed binary decision diagram (ZDD) is a compact data structure widely used for the efficient representation of families of sparse subsets. Its inherent recursive structure also facilitates easy diagram manipulation and family operations. Practical applications generally fall under discrete optimization, such as combinatorial problems and graph theory. Given its utility, summarizing the subsets represented in the diagram using key metrics is of great value as this provides valuable insights into the characteristics of the family. The paper proposes a recursive algorithm to extract information on moments from families represented as a ZDD. Given a value for every element in the universe, the value of a subset is first formulated as the sum of the values of its elements. The moments of a family are then calculated as the mean of the exponentiated subset values, akin to the method of moments. Leveraging the structure of the ZDD, the proposed algorithm recursively traverses a given diagram for efficient moments evaluation via multinomial expansion. Its utility is then demonstrated with three classical problems$2014power sets, the knapsack problem, and paths in graphs$2014offering orders of magnitude increase in computational efficiency relative to conventional method. Overall, the proposed algorithm enhances the functionality of the ZDD by introducing an efficient family operation to uncover the distribution of subset values in a represented family.
書誌情報 en : IEEE Access

巻 12, p. 91886-91895, 発行日 2024-07-01
出版者
出版者 IEEE
ISSN
収録物識別子タイプ EISSN
収録物識別子 2169-3536
出版者版DOI
関連タイプ isReplacedBy
識別子タイプ DOI
関連識別子 https://doi.org/10.1109/ACCESS.2024.3421676
出版者版URI
関連タイプ isReplacedBy
識別子タイプ URI
関連識別子 https://ieeexplore.ieee.org/document/10579738
権利
権利情報Resource https://creativecommons.org/licenses/by-nc-nd/4.0/
権利情報 c 2024 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/
著者版フラグ
出版タイプ NA
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