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The Effect of Sparsity on $k$-Dominating Set and Related First-Order Graph Properties (2312.14593v1)

Published 22 Dec 2023 in cs.DS

Abstract: We revisit $k$-Dominating Set, one of the first problems for which a tight $nk-o(1)$ conditional lower bound (for $k\ge 3$), based on SETH, was shown (P\u{a}tra\c{s}cu and Williams, SODA 2007). However, the underlying reduction creates dense graphs, raising the question: how much does the sparsity of the graph affect its fine-grained complexity? We first settle the fine-grained complexity of $k$-Dominating Set in terms of both the number of nodes $n$ and number of edges $m$. Specifically, we show an $mn{k-2-o(1)}$ lower bound based on SETH, for any dependence of $m$ on $n$. This is complemented by an $mn{k-2+o(1)}$-time algorithm for all $k\ge 3$. For the $k=2$ case, we give a randomized algorithm that employs a Bloom-filter inspired hashing to improve the state of the art of $n{\omega+o(1)}$ to $m{\omega/2+o(1)}$. If $\omega=2$, this yields a conditionally tight bound for all $k\ge 2$. To study if $k$-Dominating Set is special in its sensitivity to sparsity, we consider a class of very related problems. The $k$-Dominating Set problem belongs to a type of first-order definable graph properties that we call monochromatic basic problems. These problems are the natural monochromatic variants of the basic problems that were proven complete for the class FOP of first-order definable properties (Gao, Impagliazzo, Kolokolova, and Williams, TALG 2019). We show that among these problems, $k$-Dominating Set is the only one whose fine-grained complexity decreases in sparse graphs. Only for the special case of reflexive properties, is there an additional basic problem that can be solved faster than $n{k\pm o(1)}$ on sparse graphs. For the natural variant of distance-$r$ $k$-dominating set, we obtain a hardness of $n{k-o(1)}$ under SETH for every $r\ge 2$ already on sparse graphs, which is tight for sufficiently large $k$.

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References (37)
  1. Fine-grained complexity for sparse graphs. In Ilias Diakonikolas, David Kempe, and Monika Henzinger, editors, Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2018, Los Angeles, CA, USA, June 25-29, 2018, pages 239–252. ACM, 2018. doi:10.1145/3188745.3188888.
  2. A refined laser method and faster matrix multiplication. In Dániel Marx, editor, Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms, SODA 2021, Virtual Conference, January 10 - 13, 2021, pages 522–539. SIAM, 2021. doi:10.1137/1.9781611976465.32.
  3. Finding and counting given length cycles. Algorithmica, 17(3):209–223, 1997. doi:10.1007/BF02523189.
  4. Faster join-projects and sparse matrix multiplications. In Ronald Fagin, editor, Database Theory - ICDT 2009, 12th International Conference, St. Petersburg, Russia, March 23-25, 2009, Proceedings, volume 361 of ACM International Conference Proceeding Series, pages 121–126. ACM, 2009. doi:10.1145/1514894.1514909.
  5. The fine-grained complexity of multi-dimensional ordering properties. Algorithmica, 84(11):3156–3191, 2022. doi:10.1007/s00453-022-01014-x.
  6. Fine-grained completeness for optimization in P. In Mary Wootters and Laura Sanità, editors, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, APPROX/RANDOM 2021, August 16-18, 2021, University of Washington, Seattle, Washington, USA (Virtual Conference), volume 207 of LIPIcs, pages 9:1–9:22. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021. doi:10.4230/LIPIcs.APPROX/RANDOM.2021.9.
  7. A structural investigation of the approximability of polynomial-time problems. In Mikolaj Bojanczyk, Emanuela Merelli, and David P. Woodruff, editors, 49th International Colloquium on Automata, Languages, and Programming, ICALP 2022, July 4-8, 2022, Paris, France, volume 229 of LIPIcs, pages 30:1–30:20. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. doi:10.4230/LIPIcs.ICALP.2022.30.
  8. A fine-grained analogue of schaefer’s theorem in P: dichotomy of exists^k-forall-quantified first-order graph properties. In Amir Shpilka, editor, 34th Computational Complexity Conference, CCC 2019, July 18-20, 2019, New Brunswick, NJ, USA, volume 137 of LIPIcs, pages 31:1–31:27. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2019. doi:10.4230/LIPIcs.CCC.2019.31.
  9. Quadratic conditional lower bounds for string problems and dynamic time warping. In 2015 IEEE 56th Annual Symposium on Foundations of Computer Science, pages 79–97, 2015. doi:10.1109/FOCS.2015.15.
  10. From gap-exponential time hypothesis to fixed parameter tractable inapproximability: Clique, dominating set, and more. SIAM J. Comput., 49(4):772–810, 2020. doi:10.1137/18M1166869.
  11. New algorithms for subset query, partial match, orthogonal range searching, and related problems. In Peter Widmayer, Francisco Triguero Ruiz, Rafael Morales Bueno, Matthew Hennessy, Stephan J. Eidenbenz, and Ricardo Conejo, editors, Automata, Languages and Programming, 29th International Colloquium, ICALP 2002, Malaga, Spain, July 8-13, 2002, Proceedings, volume 2380 of Lecture Notes in Computer Science, pages 451–462. Springer, 2002. doi:10.1007/3-540-45465-9_39.
  12. Parameterized Algorithms. Springer, 2015. doi:10.1007/978-3-319-21275-3.
  13. Finding even cycles faster via capped k-walks. In Hamed Hatami, Pierre McKenzie, and Valerie King, editors, Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2017, Montreal, QC, Canada, June 19-23, 2017, pages 112–120. ACM, 2017. doi:10.1145/3055399.3055459.
  14. A framework for exponential-time-hypothesis-tight algorithms and lower bounds in geometric intersection graphs. SIAM J. Comput., 49(6):1291–1331, 2020. doi:10.1137/20M1320870.
  15. Fixed-parameter tractability and completeness I: basic results. SIAM J. Comput., 24(4):873–921, 1995. doi:10.1137/S0097539792228228.
  16. Fundamentals of Parameterized Complexity. Texts in Computer Science. Springer, 2013. doi:10.1007/978-1-4471-5559-1.
  17. All non-trivial variants of 3-ldt are equivalent. In Konstantin Makarychev, Yury Makarychev, Madhur Tulsiani, Gautam Kamath, and Julia Chuzhoy, editors, Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, STOC 2020, Chicago, IL, USA, June 22-26, 2020, pages 974–981. ACM, 2020. doi:10.1145/3357713.3384275.
  18. Neighborhood complexity and kernelization for nowhere dense classes of graphs. In Ioannis Chatzigiannakis, Piotr Indyk, Fabian Kuhn, and Anca Muscholl, editors, 44th International Colloquium on Automata, Languages, and Programming, ICALP 2017, July 10-14, 2017, Warsaw, Poland, volume 80 of LIPIcs, pages 63:1–63:14. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2017. doi:10.4230/LIPIcs.ICALP.2017.63.
  19. On the complexity of fixed parameter clique and dominating set. Theor. Comput. Sci., 326(1-3):57–67, 2004. doi:10.1016/j.tcs.2004.05.009.
  20. Improved rectangular matrix multiplication using powers of the coppersmith-winograd tensor. In Artur Czumaj, editor, Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2018, New Orleans, LA, USA, January 7-10, 2018, pages 1029–1046. SIAM, 2018. doi:10.1137/1.9781611975031.67.
  21. Completeness for first-order properties on sparse structures with algorithmic applications. ACM Trans. Algorithms, 15(2):23:1–23:35, 2019. doi:10.1145/3196275.
  22. Fundamentals of domination in graphs, volume 208 of Pure and applied mathematics. Dekker, 1998.
  23. Which problems have strongly exponential complexity? J. Comput. Syst. Sci., 63(4):512–530, 2001. doi:10.1006/jcss.2001.1774.
  24. David R. Karger. Minimum cuts in near-linear time. J. ACM, 47(1):46–76, 2000. doi:10.1145/331605.331608.
  25. A new approach to the minimum cut problem. J. ACM, 43(4):601–640, 1996. doi:10.1145/234533.234534.
  26. On the parameterized complexity of approximating dominating set. J. ACM, 66(5):33:1–33:38, 2019. doi:10.1145/3325116.
  27. Karthik C. S. and Pasin Manurangsi. On closest pair in euclidean metric: Monochromatic is as hard as bichromatic. Comb., 40(4):539–573, 2020. doi:10.1007/s00493-019-4113-1.
  28. Structural properties and constant factor-approximation of strong distance-r dominating sets in sparse directed graphs. In Heribert Vollmer and Brigitte Vallée, editors, 34th Symposium on Theoretical Aspects of Computer Science, STACS 2017, March 8-11, 2017, Hannover, Germany, volume 66 of LIPIcs, pages 48:1–48:15. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2017. doi:10.4230/LIPIcs.STACS.2017.48.
  29. Algorithms and lower bounds for cycles and walks: Small space and sparse graphs. In Thomas Vidick, editor, 11th Innovations in Theoretical Computer Science Conference, ITCS 2020, January 12-14, 2020, Seattle, Washington, USA, volume 151 of LIPIcs, pages 11:1–11:17. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. doi:10.4230/LIPIcs.ITCS.2020.11.
  30. Tight hardness for shortest cycles and paths in sparse graphs. In Artur Czumaj, editor, Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2018, New Orleans, LA, USA, January 7-10, 2018, pages 1236–1252. SIAM, 2018. doi:10.1137/1.9781611975031.80.
  31. Mihai Pătraşcu. Towards polynomial lower bounds for dynamic problems. In Leonard J. Schulman, editor, Proceedings of the 42nd ACM Symposium on Theory of Computing, STOC 2010, Cambridge, Massachusetts, USA, 5-8 June 2010, pages 603–610. ACM, 2010. doi:10.1145/1806689.1806772.
  32. On the possibility of faster SAT algorithms. In Moses Charikar, editor, Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2010, Austin, Texas, USA, January 17-19, 2010, pages 1065–1075. SIAM, 2010. doi:10.1137/1.9781611973075.86.
  33. Virginia Vassilevska Williams. On some fine-grained questions in algorithms and complexity. In Proceedings of the International Congress of Mathematicians, ICM ’18, pages 3447–3487, 2018.
  34. Monochromatic triangles, triangle listing and APSP. In Sandy Irani, editor, 61st IEEE Annual Symposium on Foundations of Computer Science, FOCS 2020, Durham, NC, USA, November 16-19, 2020, pages 786–797. IEEE, 2020. doi:10.1109/FOCS46700.2020.00078.
  35. Ryan Williams. Faster decision of first-order graph properties. In Thomas A. Henzinger and Dale Miller, editors, Joint Meeting of the Twenty-Third EACSL Annual Conference on Computer Science Logic (CSL) and the Twenty-Ninth Annual ACM/IEEE Symposium on Logic in Computer Science (LICS), CSL-LICS ’14, Vienna, Austria, July 14 - 18, 2014, pages 80:1–80:6. ACM, 2014. doi:10.1145/2603088.2603121.
  36. Finding even cycles even faster. In Serge Abiteboul and Eli Shamir, editors, Automata, Languages and Programming, 21st International Colloquium, ICALP94, Jerusalem, Israel, July 11-14, 1994, Proceedings, volume 820 of Lecture Notes in Computer Science, pages 532–543. Springer, 1994. doi:10.1007/3-540-58201-0_96.
  37. Fast sparse matrix multiplication. ACM Trans. Algorithms, 1(1):2–13, 2005. doi:10.1145/1077464.1077466.
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