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Faster Semi-Streaming Matchings via Alternating Trees

Authors Slobodan Mitrović , Anish Mukherjee , Piotr Sankowski , Wen-Horng Sheu

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ACM Subject Classification
  • Theory of computation → Graph algorithms analysis
  • Theory of computation → Approximation algorithms analysis
  • Theory of computation → Streaming, sublinear and near linear time algorithms
Keywords
  • streaming algorithms
  • approximation algorithms
  • maximum matching

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Abstract

We design a deterministic algorithm for the (1+ε)-approximate maximum matching problem. Our primary result demonstrates that this problem can be solved in O(ε^{-6}) semi-streaming passes, improving upon the O(ε^{-19}) pass-complexity algorithm by [Fischer, Mitrović, and Uitto, STOC'22]. This contributes substantially toward resolving Open question 2 from [Assadi, SOSA'24]. Leveraging the framework introduced in [FMU'22], our algorithm achieves an analogous round complexity speed-up for computing a (1+ε)-approximate maximum matching in both the Massively Parallel Computation (MPC) and CONGEST models.
The data structures maintained by our algorithm are formulated using blossom notation and represented through alternating trees. This approach enables a simplified correctness analysis by treating specific components as if operating on bipartite graphs, effectively circumventing certain technical intricacies present in prior work.

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Slobodan Mitrović, Anish Mukherjee, Piotr Sankowski, and Wen-Horng Sheu. Faster Semi-Streaming Matchings via Alternating Trees. In 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 334, pp. 119:1-119:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.ICALP.2025.119

Author Details

Slobodan Mitrović
  • Department of Computer Science, UC Davis, CA, USA
  • Department of Mathematics and Informatics, University of Novi Sad, Serbia
Anish Mukherjee
  • Department of Computer Science, University of Liverpool, UK
Piotr Sankowski
  • Institute of Informatics, University of Warsaw, Poland
Wen-Horng Sheu
  • Department of Computer Science, UC Davis, CA, USA

Funding

  • Mitrović, Slobodan: Supported by the Google Research Scholar and NSF Faculty Early Career Development Program No. 2340048.
  • Sankowski, Piotr: Supported by National Science Center grant no. 2020/37/B/ST6/04179.
  • Sheu, Wen-Horng: Supported by NSF Faculty Early Career Development Program No. 2340048.

References

  1. Mohamad Ahmadi, Fabian Kuhn, and Rotem Oshman. Distributed approximate maximum matching in the congest model. In 32nd International Symposium on Distributed Computing (DISC 2018). Schloss-Dagstuhl-Leibniz Zentrum für Informatik, 2018. Google Scholar
  2. Kook Jin Ahn and Sudipto Guha. Laminar families and metric embeddings: Non-bipartite maximum matching problem in the semi-streaming model. arXiv preprint arXiv:1104.4058, 2011. URL: https://arxiv.org/abs/1104.4058.
  3. Kook Jin Ahn and Sudipto Guha. Linear programming in the semi-streaming model with application to the maximum matching problem. Information and Computation, 222:59-79, 2013. URL: https://doi.org/10.1016/J.IC.2012.10.006.
  4. Kook Jin Ahn and Sudipto Guha. Access to data and number of iterations: Dual primal algorithms for maximum matching under resource constraints. ACM Transactions on Parallel Computing (TOPC), 4(4):1-40, 2018. URL: https://doi.org/10.1145/3154855.
  5. Sepehr Assadi. A two-pass (conditional) lower bound for semi-streaming maximum matching. In Proceedings of the 2022 ACM-SIAM Symposium on Discrete Algorithms, SODA, pages 708-742. SIAM, 2022. URL: https://doi.org/10.1137/1.9781611977073.32.
  6. Sepehr Assadi. A simple (1 - ε)-approximation semi-streaming algorithm for maximum (weighted) matching. In Symposium on Simplicity in Algorithms (SOSA), pages 337-354. SIAM, 2024. URL: https://doi.org/10.1137/1.9781611977936.31.
  7. Sepehr Assadi, MohammadHossein Bateni, Aaron Bernstein, Vahab Mirrokni, and Cliff Stein. Coresets meet edcs: algorithms for matching and vertex cover on massive graphs. In Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 1616-1635. SIAM, 2019. URL: https://doi.org/10.1137/1.9781611975482.98.
  8. Sepehr Assadi and Soheil Behnezhad. Beating two-thirds for random-order streaming matching. In 48th International Colloquium on Automata, Languages, and Programming, ICALP, volume 198 of LIPIcs, pages 19:1-19:13. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021. URL: https://doi.org/10.4230/LIPICS.ICALP.2021.19.
  9. Sepehr Assadi, Soheil Behnezhad, Sanjeev Khanna, and Huan Li. On regularity lemma and barriers in streaming and dynamic matching. In Proceedings of the 55th Annual ACM Symposium on Theory of Computing, STOC, pages 131-144. ACM, 2023. URL: https://doi.org/10.1145/3564246.3585110.
  10. Sepehr Assadi, Aaron Bernstein, and Aditi Dudeja. Decremental matching in general graphs. In 49th International Colloquium on Automata, Languages, and Programming, ICALP, volume 229 of LIPIcs, pages 11:1-11:19. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. URL: https://doi.org/10.4230/LIPIcs.ICALP.2022.11.
  11. Sepehr Assadi, Arun Jambulapati, Yujia Jin, Aaron Sidford, and Kevin Tian. Semi-streaming bipartite matching in fewer passes and optimal space. In Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 627-669. SIAM, 2022. URL: https://doi.org/10.1137/1.9781611977073.29.
  12. Sepehr Assadi, Sanjeev Khanna, and Peter Kiss. Improved bounds for fully dynamic matching via ordered Ruzsa-Szemerédi graphs. In Proceedings of the 2025 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 2971-2990. SIAM, 2025. URL: https://doi.org/10.1137/1.9781611978322.96.
  13. Sepehr Assadi, Sanjeev Khanna, and Yang Li. On estimating maximum matching size in graph streams. In Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA, pages 1723-1742. SIAM, 2017. URL: https://doi.org/10.1137/1.9781611974782.113.
  14. Sepehr Assadi, Sanjeev Khanna, Yang Li, and Grigory Yaroslavtsev. Maximum matchings in dynamic graph streams and the simultaneous communication model. In Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, SODA, pages 1345-1364. SIAM, 2016. URL: https://doi.org/10.1137/1.9781611974331.CH93.
  15. Sepehr Assadi, Gillat Kol, Raghuvansh R. Saxena, and Huacheng Yu. Multi-pass graph streaming lower bounds for cycle counting, max-cut, matching size, and other problems. In 61st IEEE Annual Symposium on Foundations of Computer Science, FOCS, pages 354-364. IEEE, 2020. URL: https://doi.org/10.1109/FOCS46700.2020.00041.
  16. Sepehr Assadi, S Cliff Liu, and Robert E Tarjan. An auction algorithm for bipartite matching in streaming and massively parallel computation models. In Symposium on Simplicity in Algorithms (SOSA), pages 165-171. SIAM, 2021. URL: https://doi.org/10.1137/1.9781611976496.18.
  17. Sepehr Assadi and Ran Raz. Near-quadratic lower bounds for two-pass graph streaming algorithms. In 61st IEEE Annual Symposium on Foundations of Computer Science, FOCS, pages 342-353. IEEE, 2020. URL: https://doi.org/10.1109/FOCS46700.2020.00040.
  18. Sepehr Assadi and Janani Sundaresan. Hidden permutations to the rescue: Multi-pass streaming lower bounds for approximate matchings. In 64th IEEE Annual Symposium on Foundations of Computer Science, FOCS, pages 909-932. IEEE, 2023. URL: https://doi.org/10.1109/FOCS57990.2023.00058.
  19. Reuven Bar-Yehuda, Keren Censor-Hillel, Mohsen Ghaffari, and Gregory Schwartzman. Distributed approximation of maximum independent set and maximum matching. In Proceedings of the ACM Symposium on Principles of Distributed Computing, pages 165-174, 2017. URL: https://doi.org/10.1145/3087801.3087806.
  20. Soheil Behnezhad. Time-optimal sublinear algorithms for matching and vertex cover. In 62nd IEEE Annual Symposium on Foundations of Computer Science, FOCS, pages 873-884. IEEE, 2021. URL: https://doi.org/10.1109/FOCS52979.2021.00089.
  21. Soheil Behnezhad and Alma Ghafari. Fully Dynamic Matching and Ordered Ruzsa-Szemerédi Graphs . In 2024 IEEE 65th Annual Symposium on Foundations of Computer Science (FOCS), pages 314-327, Los Alamitos, CA, USA, October 2024. IEEE Computer Society. URL: https://doi.org/10.1109/FOCS61266.2024.00027.
  22. Soheil Behnezhad, Mohammad Roghani, and Aviad Rubinstein. Sublinear time algorithms and complexity of approximate maximum matching. In Proceedings of the 55th Annual ACM Symposium on Theory of Computing, STOC, pages 267-280. ACM, 2023. URL: https://doi.org/10.1145/3564246.3585231.
  23. Soheil Behnezhad, Mohammad Roghani, Aviad Rubinstein, and Amin Saberi. Beating greedy matching in sublinear time. In Proceedings of the 2023 ACM-SIAM Symposium on Discrete Algorithms, SODA, pages 3900-3945. SIAM, 2023. URL: https://doi.org/10.1137/1.9781611977554.CH151.
  24. Claude Berge. Two theorems in graph theory. Proceedings of the National Academy of Sciences, 43(9):842-844, 1957. Google Scholar
  25. Aaron Bernstein. Improved bounds for matching in random-order streams. In 47th International Colloquium on Automata, Languages, and Programming, ICALP 2020, volume 168 of LIPIcs, pages 12:1-12:13. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. URL: https://doi.org/10.4230/LIPICS.ICALP.2020.12.
  26. Aaron Bernstein, Jiale Chen, Aditi Dudeja, Zachary Langley, Aaron Sidford, and Ta-Wei Tu. Matching composition and efficient weight reduction in dynamic matching. In Proceedings of the 2025 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 2991-3028, 2025. URL: https://doi.org/10.1137/1.9781611978322.97.
  27. Aaron Bernstein, Aditi Dudeja, and Zachary Langley. A framework for dynamic matching in weighted graphs. In Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing, STOC 2021, pages 668-681, New York, NY, USA, 2021. Association for Computing Machinery. URL: https://doi.org/10.1145/3406325.3451113.
  28. Aaron Bernstein, Maximilian Probst Gutenberg, and Thatchaphol Saranurak. Deterministic decremental reachability, scc, and shortest paths via directed expanders and congestion balancing. In 61st IEEE Annual Symposium on Foundations of Computer Science, FOCS, pages 1123-1134. IEEE, 2020. URL: https://doi.org/10.1109/FOCS46700.2020.00108.
  29. Sayan Bhattacharya, Peter Kiss, and Thatchaphol Saranurak. Dynamic (1 + ε)-approximate matching size in truly sublinear update time. In 64th IEEE Annual Symposium on Foundations of Computer Science, FOCS, pages 1563-1588. IEEE, 2023. URL: https://doi.org/10.1109/FOCS57990.2023.00095.
  30. Joakim Blikstad and Peter Kiss. Incremental (1-ε)-approximate dynamic matching in o(poly(1/ε)) update time. In 31st Annual European Symposium on Algorithms, ESA, volume 274 of LIPIcs, pages 22:1-22:19. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023. URL: https://doi.org/10.4230/LIPICS.ESA.2023.22.
  31. Niv Buchbinder, Danny Segev, and Yevgeny Tkach. Online algorithms for maximum cardinality matching with edge arrivals. Algorithmica, 81(5):1781-1799, 2019. URL: https://doi.org/10.1007/S00453-018-0505-7.
  32. Marc Bury and Chris Schwiegelshohn. Sublinear estimation of weighted matchings in dynamic data streams. In Algorithms - ESA 2015 - 23rd Annual European Symposium, Proceedings, volume 9294 of Lecture Notes in Computer Science, pages 263-274. Springer, 2015. URL: https://doi.org/10.1007/978-3-662-48350-3_23.
  33. Lijie Chen, Gillat Kol, Dmitry Paramonov, Raghuvansh R. Saxena, Zhao Song, and Huacheng Yu. Almost optimal super-constant-pass streaming lower bounds for reachability. In STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, pages 570-583. ACM, 2021. URL: https://doi.org/10.1145/3406325.3451038.
  34. Ashish Chiplunkar, Sumedh Tirodkar, and Sundar Vishwanathan. On randomized algorithms for matching in the online preemptive model. In Algorithms - ESA 2015 - 23rd Annual European Symposium, Proceedings, volume 9294 of Lecture Notes in Computer Science, pages 325-336. Springer, 2015. URL: https://doi.org/10.1007/978-3-662-48350-3_28.
  35. Rajesh Chitnis, Graham Cormode, Hossein Esfandiari, MohammadTaghi Hajiaghayi, Andrew McGregor, Morteza Monemizadeh, and Sofya Vorotnikova. Kernelization via sampling with applications to finding matchings and related problems in dynamic graph streams. In Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, SODA, pages 1326-1344. SIAM, 2016. URL: https://doi.org/10.1137/1.9781611974331.CH92.
  36. Artur Czumaj, Jakub Łącki, Aleksander Mądry, Slobodan Mitrović, Krzysztof Onak, and Piotr Sankowski. Round compression for parallel matching algorithms. In Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, pages 471-484, 2018. Google Scholar
  37. Doratha E. Drake and Stefan Hougardy. Improved linear time approximation algorithms for weighted matchings. In Approximation, Randomization, and Combinatorial Optimization: Algorithms and Techniques, 6th International Workshop APPROX and 7th International Workshop RANDOM Proceedings, volume 2764 of Lecture Notes in Computer Science, pages 14-23. Springer, 2003. URL: https://doi.org/10.1007/978-3-540-45198-3_2.
  38. Ran Duan and Seth Pettie. Linear-time approximation for maximum weight matching. J. ACM, 61(1), January 2014. URL: https://doi.org/10.1145/2529989.
  39. Jack Edmonds. Paths, trees, and flowers. Canadian Journal of mathematics, 17:449-467, 1965. Google Scholar
  40. Sebastian Eggert, Lasse Kliemann, Peter Munstermann, and Anand Srivastav. Bipartite matching in the semi-streaming model. Algorithmica, 63(1):490-508, 2012. URL: https://doi.org/10.1007/S00453-011-9556-8.
  41. Sebastian Eggert, Lasse Kliemann, and Anand Srivastav. Bipartite graph matchings in the semi-streaming model. In European Symposium on Algorithms, pages 492-503. Springer, 2009. URL: https://doi.org/10.1007/978-3-642-04128-0_44.
  42. Leah Epstein, Asaf Levin, Danny Segev, and Oren Weimann. Improved bounds for online preemptive matching. In 30th International Symposium on Theoretical Aspects of Computer Science, STACS, volume 20 of LIPIcs, pages 389-399. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2013. URL: https://doi.org/10.4230/LIPICS.STACS.2013.389.
  43. Hossein Esfandiari, MohammadTaghi Hajiaghayi, Vahid Liaghat, Morteza Monemizadeh, and Krzysztof Onak. Streaming algorithms for estimating the matching size in planar graphs and beyond. ACM Trans. Algorithms, 14(4):48:1-48:23, 2018. URL: https://doi.org/10.1145/3230819.
  44. Salwa Faour, Marc Fuchs, and Fabian Kuhn. Distributed congest approximation of weighted vertex covers and matchings. arXiv preprint arXiv:2111.10577, 2021. URL: https://arxiv.org/abs/2111.10577.
  45. Alireza Farhadi, Mohammad Taghi Hajiaghayi, Tung Mai, Anup Rao, and Ryan A. Rossi. Approximate maximum matching in random streams. In Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, SODA, pages 1773-1785. SIAM, 2020. URL: https://doi.org/10.1137/1.9781611975994.108.
  46. Joan Feigenbaum, Sampath Kannan, Andrew McGregor, Siddharth Suri, and Jian Zhang. On graph problems in a semi-streaming model. Theor. Comput. Sci., 348(2-3):207-216, 2005. URL: https://doi.org/10.1016/J.TCS.2005.09.013.
  47. Manuela Fischer, Mohsen Ghaffari, and Fabian Kuhn. Deterministic distributed edge-coloring via hypergraph maximal matching. In 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS), pages 180-191. IEEE, 2017. URL: https://doi.org/10.1109/FOCS.2017.25.
  48. Manuela Fischer, Slobodan Mitrović, and Jara Uitto. Deterministic (1+ε)-approximate maximum matching with poly(1/ε) passes in the semi-streaming model and beyond. In Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2022, pages 248-260. Association for Computing Machinery, 2022. URL: https://doi.org/10.1145/3519935.3520039.
  49. Buddhima Gamlath, Sagar Kale, Slobodan Mitrovic, and Ola Svensson. Weighted matchings via unweighted augmentations. In Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing, pages 491-500, 2019. URL: https://doi.org/10.1145/3293611.3331603.
  50. Buddhima Gamlath, Michael Kapralov, Andreas Maggiori, Ola Svensson, and David Wajc. Online matching with general arrivals. In 60th IEEE Annual Symposium on Foundations of Computer Science, FOCS, pages 26-37. IEEE Computer Society, 2019. URL: https://doi.org/10.1109/FOCS.2019.00011.
  51. Mohsen Ghaffari, Themis Gouleakis, Christian Konrad, Slobodan Mitrović, and Ronitt Rubinfeld. Improved massively parallel computation algorithms for mis, matching, and vertex cover. In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing, pages 129-138, 2018. URL: https://doi.org/10.1145/3212734.3212743.
  52. Mohsen Ghaffari, Christoph Grunau, and Slobodan Mitrović. Massively parallel algorithms for b-matching. In Proceedings of the 34th ACM Symposium on Parallelism in Algorithms and Architectures, pages 35-44, 2022. URL: https://doi.org/10.1145/3490148.3538589.
  53. Mohsen Ghaffari, David G Harris, and Fabian Kuhn. On derandomizing local distributed algorithms. In 2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS), pages 662-673. IEEE, 2018. URL: https://doi.org/10.1109/FOCS.2018.00069.
  54. Mohsen Ghaffari, Fabian Kuhn, Yannic Maus, and Jara Uitto. Deterministic distributed edge-coloring with fewer colors. In Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, pages 418-430, 2018. URL: https://doi.org/10.1145/3188745.3188906.
  55. Ashish Goel, Michael Kapralov, and Sanjeev Khanna. On the communication and streaming complexity of maximum bipartite matching. In Proceedings of the Twenty-Third Annual ACM-SIAM Symposium on Discrete Algorithms, SODA, pages 468-485. SIAM, 2012. URL: https://doi.org/10.1137/1.9781611973099.41.
  56. Fabrizio Grandoni, Stefano Leonardi, Piotr Sankowski, Chris Schwiegelshohn, and Shay Solomon. (1 + ε)-approximate incremental matching in constant deterministic amortized time. In Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA, pages 1886-1898. SIAM, 2019. URL: https://doi.org/10.1137/1.9781611975482.114.
  57. Venkatesan Guruswami and Krzysztof Onak. Superlinear lower bounds for multipass graph processing. Algorithmica, 76(3):654-683, 2016. URL: https://doi.org/10.1007/S00453-016-0138-7.
  58. David G Harris. Distributed local approximation algorithms for maximum matching in graphs and hypergraphs. In 2019 IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS), pages 700-724. IEEE, 2019. URL: https://doi.org/10.1109/FOCS.2019.00048.
  59. Monika R. Henzinger, Prabhakar Raghavan, and Sridhar Rajagopalan. Computing on data streams, pages 107-118. American Mathematical Society, USA, 1999. Google Scholar
  60. John E Hopcroft and Richard M Karp. A n^5/2 algorithm for maximum matchings in bipartite graphs. In 12th Annual Symposium on Switching and Automata Theory (swat 1971), pages 122-125. IEEE, 1971. URL: https://doi.org/10.1109/SWAT.1971.1.
  61. Shang-En Huang and Hsin-Hao Su. (1-ε)-approximate maximum weighted matching in poly (1/ε, log n) time in the distributed and parallel settings. In Proceedings of the 2023 ACM Symposium on Principles of Distributed Computing, pages 44-54, 2023. Google Scholar
  62. Michael Kapralov. Better bounds for matchings in the streaming model. In Proceedings of the twenty-fourth annual ACM-SIAM symposium on Discrete algorithms, pages 1679-1697. SIAM, 2013. URL: https://doi.org/10.1137/1.9781611973105.121.
  63. Michael Kapralov. Space lower bounds for approximating maximum matching in the edge arrival model. In Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms, SODA, pages 1874-1893. SIAM, 2021. URL: https://doi.org/10.1137/1.9781611976465.112.
  64. Michael Kapralov, Sanjeev Khanna, and Madhu Sudan. Approximating matching size from random streams. In Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA, pages 734-751. SIAM, 2014. URL: https://doi.org/10.1137/1.9781611973402.55.
  65. Michael Kapralov, Slobodan Mitrovic, Ashkan Norouzi-Fard, and Jakab Tardos. Space efficient approximation to maximum matching size from uniform edge samples. In Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, SODA, pages 1753-1772. SIAM, 2020. URL: https://doi.org/10.1137/1.9781611975994.107.
  66. Richard M. Karp, Umesh V. Vazirani, and Vijay V. Vazirani. An optimal algorithm for on-line bipartite matching. In Proceedings of the 22nd Annual ACM Symposium on Theory of Computing, pages 352-358. ACM, 1990. URL: https://doi.org/10.1145/100216.100262.
  67. Christian Konrad. Maximum matching in turnstile streams. In Algorithms - ESA 2015 - 23rd Annual European Symposium, Proceedings, volume 9294 of Lecture Notes in Computer Science, pages 840-852. Springer, 2015. URL: https://doi.org/10.1007/978-3-662-48350-3_70.
  68. Christian Konrad, Frédéric Magniez, and Claire Mathieu. Maximum matching in semi-streaming with few passes. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques - 15th International Workshop, APPROX, and 16th International Workshop, RANDOM Proceedings, volume 7408 of Lecture Notes in Computer Science, pages 231-242. Springer, 2012. URL: https://doi.org/10.1007/978-3-642-32512-0_20.
  69. Zvi Lotker, Boaz Patt-Shamir, and Seth Pettie. Improved distributed approximate matching. Journal of the ACM (JACM), 62(5):1-17, 2015. URL: https://doi.org/10.1145/2786753.
  70. Mohammad Mahdian and Qiqi Yan. Online bipartite matching with random arrivals: an approach based on strongly factor-revealing LPs. In Proceedings of the 43rd ACM Symposium on Theory of Computing, STOC, pages 597-606. ACM, 2011. URL: https://doi.org/10.1145/1993636.1993716.
  71. Andrew McGregor. Finding graph matchings in data streams. In International Workshop on Approximation Algorithms for Combinatorial Optimization, pages 170-181. Springer, 2005. URL: https://doi.org/10.1007/11538462_15.
  72. Slobodan Mitrović, Anish Mukherjee, Piotr Sankowski, and Wen-Horng Sheu. Faster semi-streaming matchings via alternating trees. arXiv preprint arXiv:2412.19057, 2025. Google Scholar
  73. Sumedh Tirodkar. Deterministic algorithms for maximum matching on general graphs in the semi-streaming model. In 38th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2018). Schloss-Dagstuhl-Leibniz Zentrum für Informatik, 2018. Google Scholar
  74. Da Wei Zheng and Monika Henzinger. Multiplicative auction algorithm for approximate maximum weight bipartite matching. In Integer Programming and Combinatorial Optimization - 24th International Conference, IPCO Proceedings, volume 13904 of Lecture Notes in Computer Science, pages 453-465. Springer, 2023. URL: https://doi.org/10.1007/978-3-031-32726-1_32.
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