LIPIcs.MFCS.2021.6.pdf
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An Approximation Algorithm for the Matrix Tree Multiplication Problem
Authors
Mahmoud Abo-Khamis 
,
Ryan Curtin ,
Kirk Pruhs ,
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Volume:
46th International Symposium on Mathematical Foundations of Computer Science (MFCS 2021)
Series: Leibniz International Proceedings in Informatics (LIPIcs)
Conference: Mathematical Foundations of Computer Science (MFCS) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2021-08-18
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Acknowledgements
We want to thank David Fernandez-Baca for discussions and pointers related to Markovian phelogeny trees.
Cite As Get BibTex
Mahmoud Abo-Khamis, Ryan Curtin, Sungjin Im, Benjamin Moseley, Hung Ngo, Kirk Pruhs, and Alireza Samadian. An Approximation Algorithm for the Matrix Tree Multiplication Problem. In 46th International Symposium on Mathematical Foundations of Computer Science (MFCS 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 202, pp. 6:1-6:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/LIPIcs.MFCS.2021.6
Abstract
We consider the Matrix Tree Multiplication problem. This problem is a generalization of the classic Matrix Chain Multiplication problem covered in the dynamic programming chapter of many introductory algorithms textbooks. An instance of the Matrix Tree Multiplication problem consists of a rooted tree with a matrix associated with each edge. The output is, for each leaf in the tree, the product of the matrices on the chain/path from the root to that leaf. Matrix multiplications that are shared between various chains need only be computed once, potentially being shared between different root to leaf chains. Algorithms are evaluated by the number of scalar multiplications performed. Our main result is a linear time algorithm for which the number of scalar multiplications performed is at most 15 times the optimal number of scalar multiplications.
Subject Classification
ACM Subject Classification
- Theory of computation → Approximation algorithms analysis
Keywords
- Matrix Multiplication
- Approximation Algorithm
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References
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