Equivalences between triangle and range query problems
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1908.11819.pdf
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Author(s)
Duraj, L
Kleiner, K
Polak, A
Williams, VV
Date Issued
January 2020
Journal
Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms
Citation
Duraj, L, Kleiner, K, Polak, A and Williams, VV. 2020. "Equivalences between triangle and range query problems." Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms, 2020-January.
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Author's final manuscript
Abstract
Copyright © 2020 by SIAM We define a natural class of range query problems, and prove that all problems within this class have the same time complexity (up to polylogarithmic factors). The equivalence is very general, and even applies to online algorithms. This allows us to obtain new improved algorithms for all of the problems in the class. We then focus on the special case of the problems when the queries are offline and the number of queries is linear. We show that our range query problems are runtime-equivalent (up to polylogarithmic factors) to counting for each edge e in an m-edge graph the number of triangles through e. This natural triangle problem can be solved using the best known triangle counting algorithm, running in O(m2ω/(ω+1)) ≤ O(m1.41)time. Moreover, if ω = 2, the O(m2ω/(ω+1)) running time is known to be tight (within mo(1) factors) under the 3SUM Hypothesis. In this case, our equivalence settles the complexity of the range query problems. Our problems constitute the first equivalence class with this peculiar running time bound. To better understand the complexity of these problems, we also provide a deeper insight into the family of triangle problems, in particular showing black-box reductions between triangle listing and per-edge triangle detection and counting. As a byproduct of our reductions, we obtain a simple triangle listing algorithm matching the state-of-the-art for all regimes of the number of triangles. We also give some not necessarily tight, but still surprising reductions from variants of matrix products, such as the (min, max)-product.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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