2 Search Results for "Sakaue, Shinsaku"


Document
CompDP: A Framework for Simultaneous Subgraph Counting Under Connectivity Constraints

Authors: Kengo Nakamura, Masaaki Nishino, Norihito Yasuda, and Shin-ichi Minato

Published in: LIPIcs, Volume 265, 21st International Symposium on Experimental Algorithms (SEA 2023)


Abstract
The subgraph counting problem computes the number of subgraphs of a given graph that satisfy some constraints. Among various constraints imposed on a graph, those regarding the connectivity of vertices, such as "these two vertices must be connected," have great importance since they are indispensable for determining various graph substructures, e.g., paths, Steiner trees, and rooted spanning forests. In this view, the subgraph counting problem under connectivity constraints is also important because counting such substructures often corresponds to measuring the importance of a vertex in network infrastructures. However, we must solve the subgraph counting problems multiple times to compute such an importance measure for every vertex. Conventionally, they are solved separately by constructing decision diagrams such as BDD and ZDD for each problem. However, even solving a single subgraph counting is a computationally hard task, preventing us from solving it multiple times in a reasonable time. In this paper, we propose a dynamic programming framework that simultaneously counts subgraphs for every vertex by focusing on similar connectivity constraints. Experimental results show that the proposed method solved multiple subgraph counting problems about 10-20 times faster than the existing approach for many problem settings.

Cite as

Kengo Nakamura, Masaaki Nishino, Norihito Yasuda, and Shin-ichi Minato. CompDP: A Framework for Simultaneous Subgraph Counting Under Connectivity Constraints. In 21st International Symposium on Experimental Algorithms (SEA 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 265, pp. 11:1-11:20, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)


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@InProceedings{nakamura_et_al:LIPIcs.SEA.2023.11,
  author =	{Nakamura, Kengo and Nishino, Masaaki and Yasuda, Norihito and Minato, Shin-ichi},
  title =	{{CompDP: A Framework for Simultaneous Subgraph Counting Under Connectivity Constraints}},
  booktitle =	{21st International Symposium on Experimental Algorithms (SEA 2023)},
  pages =	{11:1--11:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-279-2},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{265},
  editor =	{Georgiadis, Loukas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2023.11},
  URN =		{urn:nbn:de:0030-drops-183613},
  doi =		{10.4230/LIPIcs.SEA.2023.11},
  annote =	{Keywords: Subgraph counting, Connectivity, Zero-suppressed Binary Decision Diagram}
}
Document
Track A: Algorithms, Complexity and Games
Nearly Tight Spectral Sparsification of Directed Hypergraphs

Authors: Kazusato Oko, Shinsaku Sakaue, and Shin-ichi Tanigawa

Published in: LIPIcs, Volume 261, 50th International Colloquium on Automata, Languages, and Programming (ICALP 2023)


Abstract
Spectral hypergraph sparsification, an attempt to extend well-known spectral graph sparsification to hypergraphs, has been extensively studied over the past few years. For undirected hypergraphs, Kapralov, Krauthgamer, Tardos, and Yoshida (2022) have proved an ε-spectral sparsifier of the optimal O^*(n) size, where n is the number of vertices and O^* suppresses the ε^{-1} and log n factors. For directed hypergraphs, however, the optimal sparsifier size has not been known. Our main contribution is the first algorithm that constructs an O^*(n²)-size ε-spectral sparsifier for a weighted directed hypergraph. Our result is optimal up to the ε^{-1} and log n factors since there is a lower bound of Ω(n²) even for directed graphs. We also show the first non-trivial lower bound of Ω(n²/ε) for general directed hypergraphs. The basic idea of our algorithm is borrowed from the spanner-based sparsification for ordinary graphs by Koutis and Xu (2016). Their iterative sampling approach is indeed useful for designing sparsification algorithms in various circumstances. To demonstrate this, we also present a similar iterative sampling algorithm for undirected hypergraphs that attains one of the best size bounds, enjoys parallel implementation, and can be transformed to be fault-tolerant.

Cite as

Kazusato Oko, Shinsaku Sakaue, and Shin-ichi Tanigawa. Nearly Tight Spectral Sparsification of Directed Hypergraphs. In 50th International Colloquium on Automata, Languages, and Programming (ICALP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 261, pp. 94:1-94:19, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)


Copy BibTex To Clipboard

@InProceedings{oko_et_al:LIPIcs.ICALP.2023.94,
  author =	{Oko, Kazusato and Sakaue, Shinsaku and Tanigawa, Shin-ichi},
  title =	{{Nearly Tight Spectral Sparsification of Directed Hypergraphs}},
  booktitle =	{50th International Colloquium on Automata, Languages, and Programming (ICALP 2023)},
  pages =	{94:1--94:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-278-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{261},
  editor =	{Etessami, Kousha and Feige, Uriel and Puppis, Gabriele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2023.94},
  URN =		{urn:nbn:de:0030-drops-181469},
  doi =		{10.4230/LIPIcs.ICALP.2023.94},
  annote =	{Keywords: Spectral sparsification, (Directed) hypergraphs, Iterative sampling}
}
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