Weighted Matchings via Unweighted Augmentations-Reference-Cited by-同舟云学术

Weighted Matchings via Unweighted Augmentations

Published:2019-07-16 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing
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Author:

Gamlath Buddhima¹,Kale Sagar¹,Mitrovic Slobodan²,Svensson Ola¹

Affiliation:

1. EPFL, Lausanne, Switzerland

2. Massachusetts Institute of Technology, Cambridge, MA, USA

Funder

European Research Council

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3293611.3331603

Reference45 articles.

1. Kook Jin Ahn and Sudipto Guha. 2013. Linear Programming in the Semi-streaming Model with Application to the Maximum Matching Problem. Inf. Comput. 222(Jan. 2013) 59--79. 10.1016/j.ic.2012.10.006 Kook Jin Ahn and Sudipto Guha. 2013. Linear Programming in the Semi-streaming Model with Application to the Maximum Matching Problem. Inf. Comput. 222(Jan. 2013) 59--79. 10.1016/j.ic.2012.10.006

2. Kook Jin Ahn and Sudipto Guha. 2018. Access to data and number of iterations: Dual primal algorithms for maximum matching under resource constraints. ACM Transactions on Parallel Computing (TOPC)4 4 (2018) 17. 10.1145/3154855 Kook Jin Ahn and Sudipto Guha. 2018. Access to data and number of iterations: Dual primal algorithms for maximum matching under resource constraints. ACM Transactions on Parallel Computing (TOPC)4 4 (2018) 17. 10.1145/3154855

3. A fast and simple randomized parallel algorithm for the maximal independent set problem

4. Parallel algorithms for geometric graph problems

5. Parallel Graph Connectivity in Log Diameter Rounds

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