Streaming Algorithms for Constrained Submodular Maximization-Reference-Cited by-同舟云学术

Streaming Algorithms for Constrained Submodular Maximization

Published:2023-06-19 Issue: Volume: Page:
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Container-title:Abstract Proceedings of the 2023 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems
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Author:

Cui Shuang¹^ORCID,Han Kai²^ORCID,Tang Jing³^ORCID,Huang He²^ORCID,Li Xueying⁴^ORCID,Li Zhiyu⁴^ORCID

Affiliation:

1. University of Science and Technology of China, Hefei, China

2. Soochow University, Suzhou, China

3. The Hong Kong University of Science and Technology, Kowloon, China

4. Alibaba Group, Hangzhou, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3578338.3593573

Reference13 articles.

1. Streaming submodular maximization

2. Fast algorithms for maximizing submodular functions

3. Constrained Submodular Maximization via a Nonsymmetric Technique

4. Shuang Cui , Kai Han , Tianshuai Zhu , Jing Tang , Benwei Wu , and He Huang . 2021 . Randomized Algorithms for Submodular Function Maximization with a k-System Constraint . In International Conference on Machine Learning (ICML). 2222--2232 . Shuang Cui, Kai Han, Tianshuai Zhu, Jing Tang, Benwei Wu, and He Huang. 2021. Randomized Algorithms for Submodular Function Maximization with a k-System Constraint. In International Conference on Machine Learning (ICML). 2222--2232.

5. Ryan Gomes and Andreas Krause . 2010 . Budgeted nonparametric learning from data streams . In International Conference on Machine Learning (ICML). 391--398 . Ryan Gomes and Andreas Krause. 2010. Budgeted nonparametric learning from data streams. In International Conference on Machine Learning (ICML). 391--398.