Near-Optimal Algorithms for Point-Line Covering Problems
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Abstract
- We study fundamental point-line covering problems in computational geometry, in which the input is a set S of points in the plane. The first is the Rich Lines problem, which asks for the set of all lines that each covers at least λ points from S, for a given integer parameter λ ≥ 2; this problem subsumes the 3-Points-on-Line problem and the Exact Fitting problem, which – the latter – asks for a line containing the maximum number of points. The second is the NP-hard problem Line Cover, which asks for a set of k lines that cover the points of S, for a given parameter k ∈ N. Both problems have been extensively studied. In particular, the Rich Lines problem is a fundamental problem whose solution serves as a building block for several algorithms in computational geometry.
For Rich Lines and Exact Fitting, we present a randomized Monte Carlo algorithm that achieves a lower running time than that of Guibas et al.’s algorithm [Computational Geometry 1996], for a wide range of the parameter λ. We derive lower-bound results showing that, for λ = Ω(√ n log n), the upper bound on the running time of this randomized algorithm matches the lower bound that
we derive on the time complexity of Rich Lines in the algebraic computation trees model.
For Line Cover, we present two kernelization algorithms: a randomized Monte Carlo algorithm and a deterministic algorithm. Both algorithms improve the running time of existing kernelization algorithms for Line Cover. We derive lower-bound results showing that the running time of the randomized algorithm we present comes close to the lower bound we derive on the time complexity
of kernelization algorithms for Line Cover in the algebraic computation trees model.
Title | Near-Optimal Algorithms for Point-Line Covering Problems |
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Creator | Kanj, I. |
Chen, J. | |
Xia, Ge | |
Huang, Q. | |
Publisher | 39th International Symposium on Theoretical Aspects of Computer Science (STACS 2022) |
Academic Department | Computer Science |
Division | Natural Sciences |
Organization | Lafayette College |
Date Issued | 2022 |
Date Available | 2023-03-23 |
Type | Article |
Language | English |
Keyword | rich lines |
kernelization | |
exact ftting | |
complexity lower bounds | |
algebraic computation trees | |
randomized algorithms | |
line cover | |
Bibliographic Citation | Chen, J., et al. (2022) "Near-Optimal Algorithms for Point-Line Covering Problems." In Petra Berenbrink and Benjamin Monmege (eds.), 39th International Symposium on Theoretical Aspects of Computer Science (STACS 2022) (Article 21). Dagstuhl Publishing. |
Standard Identifier | Handle 10385/s7526f233 |
DOI 10.4230/LIPIcs.STACS.2022.21 | |
Permalink | http://hdl.handle.net/10385/s7526f233 |
Rights Statement |
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Rights Holders | Kanj, I. |
Chen, J. | |
Xia, Ge | |
Huang, Q. |
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File | Xia-39thInternationalSymposiumonTheoreticalAspectsofComputerScience-2022.pdf | Uploaded 2023-03-23 | Public |
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