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The Maximum Binary Tree Problem

Authors Karthekeyan Chandrasekaran, Elena Grigorescu, Gabriel Istrate, Shubhang Kulkarni, Young-San Lin, Minshen Zhu

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Karthekeyan Chandrasekaran
  • Dept. of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA
Elena Grigorescu
  • Purdue University, West Lafayette, IN, USA
Gabriel Istrate
  • West University of Timişoara, Romania
  • e-Austria Research Institute, Timişoara, Romania
Shubhang Kulkarni
  • Purdue University, West Lafayette, IN, USA
Young-San Lin
  • Purdue University, West Lafayette, IN, USA
Minshen Zhu
  • Purdue University, West Lafayette, IN, USA

Funding

  • Chandrasekaran, Karthekeyan: Supported by NSF CCF-1814613 and NSF CCF-1907937.
  • Grigorescu, Elena: Supported by NSF CCF-1910659 and NSF CCF-1910411.
  • Istrate, Gabriel: Supported by a grant of Ministry of Research and Innovation, CNCS - UEFISCDI project number PN-III-P4-ID-PCE-2016-0842, within PNCDI III.
  • Lin, Young-San: Supported by NSF CCF-1910659 and NSF CCF-1910411.
  • Zhu, Minshen: Supported by NSF CCF-1910659 and NSF CCF-1910411.

Cite As Get BibTex

Karthekeyan Chandrasekaran, Elena Grigorescu, Gabriel Istrate, Shubhang Kulkarni, Young-San Lin, and Minshen Zhu. The Maximum Binary Tree Problem. In 28th Annual European Symposium on Algorithms (ESA 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 173, pp. 30:1-30:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020) https://doi.org/10.4230/LIPIcs.ESA.2020.30

Abstract

We introduce and investigate the approximability of the maximum binary tree problem (MBT) in directed and undirected graphs. The goal in MBT is to find a maximum-sized binary tree in a given graph. MBT is a natural variant of the well-studied longest path problem, since both can be viewed as finding a maximum-sized tree of bounded degree in a given graph. 
The connection to longest path motivates the study of MBT in directed acyclic graphs (DAGs), since the longest path problem is solvable efficiently in DAGs. In contrast, we show that MBT in DAGs is in fact hard: it has no efficient exp(-O(log n/ log log n))-approximation algorithm under the exponential time hypothesis, where n is the number of vertices in the input graph. In undirected graphs, we show that MBT has no efficient exp(-O(log^0.63 n))-approximation under the exponential time hypothesis. Our inapproximability results rely on self-improving reductions and structural properties of binary trees. We also show constant-factor inapproximability assuming P ≠ NP.
In addition to inapproximability results, we present algorithmic results along two different flavors: (1) We design a randomized algorithm to verify if a given directed graph on n vertices contains a binary tree of size k in 2^k poly(n) time. (2) Motivated by the longest heapable subsequence problem, introduced by Byers, Heeringa, Mitzenmacher, and Zervas, ANALCO 2011, which is equivalent to MBT in permutation DAGs, we design efficient algorithms for MBT in bipartite permutation graphs.

Subject Classification

ACM Subject Classification
  • Theory of computation → Approximation algorithms analysis
Keywords
  • maximum binary tree
  • heapability
  • inapproximability
  • fixed-parameter tractability

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