Improved Streaming Algorithms for Maximum Directed Cut via Smoothed Snapshots

Author:

Saxena Raghuvansh R.1,Singer Noah G.2,Sudan Madhu3,Velusamy Santhoshini4

Affiliation:

1. Tata Institute of Fundamental Research,Mumbai,Maharashtra,India

2. Carnegie Mellon University,Department of Computer Science,Pittsburgh,PA,USA

3. Harvard University,School of Engineering and Applied Sciences,Cambridge,MA,USA

4. Toyota Technological Institute at Chicago,Chicago,IL,USA

Funder

Google

Publisher

IEEE

Reference20 articles.

1. Sketching Cuts in Graphs and Hypergraphs

2. Approximating matching size from random streams

3. Streaming Complexity of Approximating Max 2CSP and Max Acyclic Subgraph;Guruswami;Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX 2017, Berkeley, CA, USA, August 16-18, 2017), ser. LIPIcs,2017

4. (1 + Ω(1))-Αpproximation to MAX-CUT Requires Linear Space

5. Streaming Hardness of Unique Games;Guruswami;Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX 2019, Cambridge, MA, USA, September 20-22, 2019), ser. LIPIcs,2019

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Exponential Quantum Space Advantage for Approximating Maximum Directed Cut in the Streaming Model;Proceedings of the 56th Annual ACM Symposium on Theory of Computing;2024-06-10

2. Streaming approximation resistance of every ordering CSP;computational complexity;2024-05-29

3. Sketching Approximability of All Finite CSPs;Journal of the ACM;2024-04-12

4. Improved Streaming Algorithms for Maximum Directed Cut via Smoothed Snapshots;2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS);2023-11-06

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