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Faster Combinatorial k-Clique Algorithms (2401.13502v2)

Published 24 Jan 2024 in cs.DS

Abstract: Detecting if a graph contains a $k$-Clique is one of the most fundamental problems in computer science. The asymptotically fastest algorithm runs in time $O(n{\omega k/3})$, where $\omega$ is the exponent of Boolean matrix multiplication. To date, this is the only technique capable of beating the trivial $O(nk)$ bound by a polynomial factor. Due to this technique's various limitations, much effort has gone into designing "combinatorial" algorithms that improve over exhaustive search via other techniques. The first contribution of this work is a faster combinatorial algorithm for $k$-Clique, improving Vassilevska's bound of $O(n{k}/\log{k-1}{n})$ by two log factors. Technically, our main result is a new reduction from $k$-Clique to Triangle detection that exploits the same divide-and-conquer at the core of recent combinatorial algorithms by Chan (SODA'15) and Yu (ICALP'15). Our second contribution is exploiting combinatorial techniques to improve the state-of-the-art (even of non-combinatorial algorithms) for generalizations of the $k$-Clique problem. In particular, we give the first $o(nk)$ algorithm for $k$-clique in hypergraphs and an $O(n3/\log{2.25}{n} + t)$ algorithm for listing $t$ triangles in a graph.

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References (56)
  1. Fine-grained complexity of analyzing compressed data: Quantifying improvements over decompress-and-solve. In 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS), pages 192–203. IEEE, 2017.
  2. If the current clique algorithms are optimal, so is valiant’s parser. SIAM Journal on Computing, 47(6):2527–2555, 2018.
  3. More consequences of falsifying seth and the orthogonal vectors conjecture. In Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, pages 253–266, 2018.
  4. New graph decompositions and combinatorial boolean matrix multiplication algorithms. CoRR, abs/2311.09095, 2023. URL: https://doi.org/10.48550/arXiv.2311.09095, arXiv:2311.09095, doi:10.48550/ARXIV.2311.09095.
  5. Faster algorithms for all-pairs bounded min-cuts. In Christel Baier, Ioannis Chatzigiannakis, Paola Flocchini, and Stefano Leonardi, editors, 46th International Colloquium on Automata, Languages, and Programming, ICALP 2019, July 9-12, 2019, Patras, Greece, volume 132 of LIPIcs, pages 7:1–7:15. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2019. doi:10.4230/LIPIcs.ICALP.2019.7.
  6. Breaking the cubic barrier for all-pairs max-flow: Gomory-hu tree in nearly quadratic time. In 63rd IEEE Annual Symposium on Foundations of Computer Science, FOCS 2022, Denver, CO, USA, October 31 - November 3, 2022, pages 884–895. IEEE, 2022. doi:10.1109/FOCS54457.2022.00088.
  7. Subcubic algorithms for gomory-hu tree in unweighted graphs. In Samir Khuller and Virginia Vassilevska Williams, editors, STOC ’21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, Virtual Event, Italy, June 21-25, 2021, pages 1725–1737. ACM, 2021. doi:10.1145/3406325.3451073.
  8. Popular conjectures imply strong lower bounds for dynamic problems. In 55th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2014), pages 434–443. IEEE Computer Society, 2014. doi:10.1109/FOCS.2014.53.
  9. Consequences of faster alignment of sequences. In Automata, Languages, and Programming: 41st International Colloquium, ICALP 2014, Copenhagen, Denmark, July 8-11, 2014, Proceedings, Part I 41, pages 39–51. Springer, 2014.
  10. Fast estimation of diameter and shortest paths (without matrix multiplication). In Éva Tardos, editor, Proceedings of the Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, 28-30 January 1996, Atlanta, Georgia, USA, pages 547–553. ACM/SIAM, 1996. URL: http://dl.acm.org/citation.cfm?id=313852.314117.
  11. Dana Angluin. The four russians’ algorithm for boolean matrix multiplication is optimal in its class. ACM SIGACT News, 8(1):29–33, 1976.
  12. On economical construction of the transitive closure of an oriented graph. Doklady Akademii Nauk, 194(3):487–488, 1970.
  13. Tight hardness results for maximum weight rectangles. In Ioannis Chatzigiannakis, Michael Mitzenmacher, Yuval Rabani, and Davide Sangiorgi, editors, 43rd International Colloquium on Automata, Languages, and Programming, ICALP 2016, July 11-15, 2016, Rome, Italy, volume 55 of LIPIcs, pages 81:1–81:13. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2016. doi:10.4230/LIPIcs.ICALP.2016.81.
  14. Improving viterbi is hard: Better runtimes imply faster clique algorithms. In Doina Precup and Yee Whye Teh, editors, Proceedings of the 34th International Conference on Machine Learning, ICML 2017, Sydney, NSW, Australia, 6-11 August 2017, volume 70 of Proceedings of Machine Learning Research, pages 311–321. PMLR, 2017. URL: http://proceedings.mlr.press/v70/backurs17a.html.
  15. Regularity lemmas and combinatorial algorithms. Theory Comput., 8(1):69–94, 2012. doi:10.4086/toc.2012.v008a004.
  16. Subquadratic algorithms for 3SUM. Algorithmica, 50(4):584–596, 2008. doi:10.1007/s00453-007-9036-3.
  17. New techniques and fine-grained hardness for dynamic near-additive spanners. In Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 1836–1855. SIAM, 2021.
  18. Even faster elastic-degenerate string matching via fast matrix multiplication. LEIBNIZ INTERNATIONAL PROCEEDINGS IN INFORMATICS, 132:1–15, 2019.
  19. Listing triangles. In Javier Esparza, Pierre Fraigniaud, Thore Husfeldt, and Elias Koutsoupias, editors, Automata, Languages, and Programming - 41st International Colloquium, ICALP 2014, Copenhagen, Denmark, July 8-11, 2014, Proceedings, Part I, volume 8572 of Lecture Notes in Computer Science, pages 223–234. Springer, 2014. doi:10.1007/978-3-662-43948-7_19.
  20. A fine-grained analogue of schaefer’s theorem in p: Dichotomy of exists^ k-forall-quantified first-order graph properties. In 34th Computational Complexity Conference (CCC 2019). Schloss Dagstuhl-Leibniz-Zentrum für Informatik, 2019.
  21. Tree edit distance cannot be computed in strongly subcubic time (unless apsp can). ACM Transactions on Algorithms (TALG), 16(4):1–22, 2020.
  22. Truly subcubic algorithms for language edit distance and rna folding via fast bounded-difference min-plus product. SIAM Journal on Computing, 48(2):481–512, 2019.
  23. A dichotomy for regular expression membership testing. In 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS), pages 307–318. IEEE, 2017.
  24. Clique-based lower bounds for parsing tree-adjoining grammars. arXiv preprint arXiv:1803.00804, 2018.
  25. On the enumeration complexity of unions of conjunctive queries. In Dan Suciu, Sebastian Skritek, and Christoph Koch, editors, Proceedings of the 38th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, PODS 2019, Amsterdam, The Netherlands, June 30 - July 5, 2019, pages 134–148. ACM, 2019. doi:10.1145/3294052.3319700.
  26. Fine-grained complexity of regular path queries. arXiv preprint arXiv:2101.01945, 2021.
  27. Timothy M Chan. A (slightly) faster algorithm for klee’s measure problem. In Proceedings of the twenty-fourth annual symposium on Computational geometry, pages 94–100, 2008.
  28. Timothy M. Chan. Speeding up the four russians algorithm by about one more logarithmic factor. In Piotr Indyk, editor, Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2015, San Diego, CA, USA, January 4-6, 2015, pages 212–217. SIAM, 2015. doi:10.1137/1.9781611973730.16.
  29. Range closest-pair search in higher dimensions. Computational Geometry, 91:101669, 2020.
  30. Yi-Jun Chang. Hardness of RNA folding problem with four symbols. In Roberto Grossi and Moshe Lewenstein, editors, 27th Annual Symposium on Combinatorial Pattern Matching, CPM 2016, June 27-29, 2016, Tel Aviv, Israel, volume 54 of LIPIcs, pages 13:1–13:12. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2016. doi:10.4230/LIPIcs.CPM.2016.13.
  31. Upper and lower bounds for dynamic data structures on strings. arXiv preprint arXiv:1802.06545, 2018.
  32. Listing cliques from smaller cliques. CoRR, abs/2307.15871, 2023. arXiv:2307.15871, doi:10.48550/arXiv.2307.15871.
  33. Graph pattern detection: Hardness for all induced patterns and faster non-induced cycles. In Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, pages 1167–1178, 2019.
  34. Lower bounds for combinatorial algorithms for boolean matrix multiplication. In Rolf Niedermeier and Brigitte Vallée, editors, 35th Symposium on Theoretical Aspects of Computer Science, STACS 2018, February 28 to March 3, 2018, Caen, France, volume 96 of LIPIcs, pages 23:1–23:14. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2018. doi:10.4230/LIPIcs.STACS.2018.23.
  35. Faster matrix multiplication via asymmetric hashing. In 64th IEEE Annual Symposium on Foundations of Computer Science (FOCS 2023). IEEE Computer Society, 2023. To appear. URL: https://doi.org/10.48550/arXiv.2210.10173.
  36. 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.
  37. Jacob Fox. A new proof of the graph removal lemma. CoRR, abs/1006.1300, 2010. URL: http://arxiv.org/abs/1006.1300, arXiv:1006.1300.
  38. Quick approximation to matrices and applications. Comb., 19(2):175–220, 1999. doi:10.1007/s004930050052.
  39. Unifying and strengthening hardness for dynamic problems via the online matrix-vector multiplication conjecture. In Rocco A. Servedio and Ronitt Rubinfeld, editors, Proceedings of the Forty-Seventh Annual ACM on Symposium on Theory of Computing, STOC 2015, Portland, OR, USA, June 14-17, 2015, pages 21–30. ACM, 2015. doi:10.1145/2746539.2746609.
  40. Ce Jin and Yinzhan Xu. Tight dynamic problem lower bounds from generalized bmm and omv. In Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing, pages 1515–1528, 2022.
  41. Higher lower bounds from the 3SUM conjecture. In Robert Krauthgamer, editor, 27th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2016), pages 1272–1287. SIAM, 2016. doi:10.1137/1.9781611974331.ch89.
  42. A simple algorithm for approximating the text-to-pattern hamming distance. In Raimund Seidel, editor, 1st Symposium on Simplicity in Algorithms (SOSA 2018), volume 61 of OASIcs, pages 10:1–10:5. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2018. doi:10.4230/OASIcs.SOSA.2018.10.
  43. Faster online matrix-vector multiplication. In Philip N. Klein, editor, Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2017, Barcelona, Spain, Hotel Porta Fira, January 16-19, pages 2182–2189. SIAM, 2017. doi:10.1137/1.9781611974782.142.
  44. Lillian Lee. Fast context-free grammar parsing requires fast boolean matrix multiplication. Journal of the ACM (JACM), 49(1):1–15, 2002.
  45. Jason Li. Faster minimum k-cut of a simple graph. In 2019 IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS), pages 1056–1077. IEEE, 2019.
  46. Tight hardness for shortest cycles and paths in sparse graphs. In Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 1236–1252. SIAM, 2018.
  47. Szemerédi’s lemma for the analyst. GAFA Geometric And Functional Analysis, 17:252–270, 2007. URL: https://api.semanticscholar.org/CorpusID:15201345.
  48. On the complexity of the subgraph problem. Commentationes Mathematicae Universitatis Carolinae, 26(2):415–419, 1985.
  49. Mihai Pătraşcu. Towards polynomial lower bounds for dynamic problems. In Leonard J. Schulman, editor, 42nd Annual ACM Symposium on Theory of Computing (STOC 2010), pages 603–610. ACM, 2010. doi:10.1145/1806689.1806772.
  50. On dynamic shortest paths problems. In Susanne Albers and Tomasz Radzik, editors, Algorithms - ESA 2004, 12th Annual European Symposium, Bergen, Norway, September 14-17, 2004, Proceedings, volume 3221 of Lecture Notes in Computer Science, pages 580–591. Springer, 2004. doi:10.1007/978-3-540-30140-0_52.
  51. Volker Strassen. Gaussian elimination is not optimal. Numerische Mathematik, 13:354–356, 1969.
  52. Virginia Vassilevska. Efficient algorithms for clique problems. Inf. Process. Lett., 109(4):254–257, 2009. doi:10.1016/j.ipl.2008.10.014.
  53. Virginia Vassilevska Williams. On some fine-grained questions in algorithms and complexity. In Proceedings of the International Congress of Mathematicians (ICM 2018), pages 3447–3487, 2018. doi:10.1142/9789813272880_0188.
  54. Subcubic equivalences between path, matrix, and triangle problems. J. ACM, 65(5):27:1–27:38, 2018. doi:10.1145/3186893.
  55. Monochromatic triangles, triangle listing and APSP. In Sandy Irani, editor, 61st Annual IEEE Symposium on Foundations of Computer Science (FOCS 2020), pages 786–797. IEEE, 2020. doi:10.1109/FOCS46700.2020.00078.
  56. Huacheng Yu. An improved combinatorial algorithm for boolean matrix multiplication. Inf. Comput., 261:240–247, 2018. doi:10.1016/j.ic.2018.02.006.
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