{"title":"Almost optimal query algorithm for hitting set using a subset query","authors":"Arijit Bishnu , Arijit Ghosh , Sudeshna Kolay , Gopinath Mishra , Saket Saurabh","doi":"10.1016/j.jcss.2023.02.002","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, we focus on <span>Hitting-Set</span><span>, a fundamental problem in combinatorial optimization, through the lens of sublinear time algorithms. Given access to the hypergraph through a subset query oracle in the query model, we give sublinear time algorithms for </span><span>Hitting-Set</span><span> with almost tight parameterized query complexity. In </span><em>parameterized query complexity</em>, we estimate the number of queries to the oracle based on the parameter <em>k</em>, the size of the <span>Hitting-Set</span>. The subset query oracle we use in this paper is called Generalized <em>d</em><span>-partite Independent Set query oracle (GPIS) and it was introduced by Bishnu et al. (ISAAC'18). GPIS is a generalization to hypergraphs of the Bipartite Independent Set query oracle (BIS) introduced by Beame et al. (ITCS'18 and TALG'20) for estimating the number of edges in graphs. Since its introduction GPIS query oracle has been used for estimating the number of hyperedges independently by Dell et al. (SODA'20 and SICOMP'22) and Bhattacharya et al. (STACS'22), and for estimating the number of triangles in a graph by Bhattacharya et al. (ISAAC'19 and TOCS'21). Formally, GPIS is defined as follows: </span><span>GPIS</span> <em>oracle for a d-uniform hypergraph</em> <span><math><mi>H</mi></math></span> <em>takes as input d pairwise disjoint non-empty subsets</em> <span><math><msub><mrow><mi>A</mi></mrow><mrow><mn>1</mn></mrow></msub><mo>,</mo><mo>…</mo><mo>,</mo><msub><mrow><mi>A</mi></mrow><mrow><mi>d</mi></mrow></msub></math></span> <em>of vertices in</em> <span><math><mi>H</mi></math></span> <em>and answers whether there is a hyperedge in</em> <span><math><mi>H</mi></math></span> <em>that intersects each set</em> <span><math><msub><mrow><mi>A</mi></mrow><mrow><mi>i</mi></mrow></msub></math></span><em>, where</em> <span><math><mi>i</mi><mo>∈</mo><mo>{</mo><mn>1</mn><mo>,</mo><mspace></mspace><mn>2</mn><mo>,</mo><mspace></mspace><mo>…</mo><mo>,</mo><mi>d</mi><mo>}</mo></math></span><em>.</em> For <span><math><mi>d</mi><mo>=</mo><mn>2</mn></math></span>, the <span>GPIS</span> oracle is nothing but <span>BIS</span> oracle.</p><p>We show that <em>d</em>-<span>Hitting-Set</span>, the hitting set problem for <em>d</em>-uniform hypergraphs, can be solved using <span><math><msub><mrow><mover><mrow><mi>O</mi></mrow><mrow><mo>˜</mo></mrow></mover></mrow><mrow><mi>d</mi></mrow></msub><mo>(</mo><msup><mrow><mi>k</mi></mrow><mrow><mi>d</mi></mrow></msup><mi>log</mi><mo></mo><mi>n</mi><mo>)</mo></math></span> <span>GPIS</span> queries. Additionally, we also showed that <em>d</em>-<span>Decision-Hitting-Set</span>, the decision version of <em>d</em>-<span>Hitting-Set</span> can be solved with <span><math><msub><mrow><mover><mrow><mi>O</mi></mrow><mrow><mo>˜</mo></mrow></mover></mrow><mrow><mi>d</mi></mrow></msub><mrow><mo>(</mo><mi>min</mi><mo></mo><mrow><mo>{</mo><msup><mrow><mi>k</mi></mrow><mrow><mi>d</mi></mrow></msup><mi>log</mi><mo></mo><mi>n</mi></mrow></mrow></math></span>, <span><math><mrow><msup><mrow><mi>k</mi></mrow><mrow><mn>2</mn><msup><mrow><mi>d</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></msup><mo>}</mo></mrow><mo>)</mo></math></span> <span>GPIS</span> queries. We complement these parameterized upper bounds with an almost matching parameterized lower bound that states that any algorithm that solves <em>d</em>-<span>Decision-Hitting-Set</span> requires <span><math><mi>Ω</mi><mrow><mo>(</mo><mrow><mo>(</mo><mtable><mtr><mtd><mrow><mi>k</mi><mo>+</mo><mi>d</mi></mrow></mtd></mtr><mtr><mtd><mi>d</mi></mtd></mtr></mtable><mo>)</mo></mrow><mo>)</mo></mrow></math></span> <span>GPIS</span> queries.</p></div>","PeriodicalId":50224,"journal":{"name":"Journal of Computer and System Sciences","volume":"137 ","pages":"Pages 50-65"},"PeriodicalIF":1.1000,"publicationDate":"2023-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer and System Sciences","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022000023000156","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we focus on Hitting-Set, a fundamental problem in combinatorial optimization, through the lens of sublinear time algorithms. Given access to the hypergraph through a subset query oracle in the query model, we give sublinear time algorithms for Hitting-Set with almost tight parameterized query complexity. In parameterized query complexity, we estimate the number of queries to the oracle based on the parameter k, the size of the Hitting-Set. The subset query oracle we use in this paper is called Generalized d-partite Independent Set query oracle (GPIS) and it was introduced by Bishnu et al. (ISAAC'18). GPIS is a generalization to hypergraphs of the Bipartite Independent Set query oracle (BIS) introduced by Beame et al. (ITCS'18 and TALG'20) for estimating the number of edges in graphs. Since its introduction GPIS query oracle has been used for estimating the number of hyperedges independently by Dell et al. (SODA'20 and SICOMP'22) and Bhattacharya et al. (STACS'22), and for estimating the number of triangles in a graph by Bhattacharya et al. (ISAAC'19 and TOCS'21). Formally, GPIS is defined as follows: GPISoracle for a d-uniform hypergraphtakes as input d pairwise disjoint non-empty subsetsof vertices inand answers whether there is a hyperedge inthat intersects each set, where. For , the GPIS oracle is nothing but BIS oracle.
We show that d-Hitting-Set, the hitting set problem for d-uniform hypergraphs, can be solved using GPIS queries. Additionally, we also showed that d-Decision-Hitting-Set, the decision version of d-Hitting-Set can be solved with , GPIS queries. We complement these parameterized upper bounds with an almost matching parameterized lower bound that states that any algorithm that solves d-Decision-Hitting-Set requires GPIS queries.
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