A New Information Complexity Measure for Multi-pass Streaming with Applications-Reference-Cited by-同舟云学术

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A New Information Complexity Measure for Multi-pass Streaming with Applications

Published:2024-06-10 Issue: Volume:22 Page:1781-1792
ISSN:
Container-title:Proceedings of the 56th Annual ACM Symposium on Theory of Computing
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Author:

Braverman Mark¹^ORCID,Garg Sumegha²^ORCID,Li Qian³^ORCID,Wang Shuo⁴^ORCID,Woodruff David P.⁵^ORCID,Zhang Jiapeng⁶^ORCID

Affiliation:

1. Princeton University, Princeton, NJ, USA

2. Rutgers University, Piscataway, NJ, USA

3. Shenzhen Research Institute of Big Data, Shenzhen, China

4. Shanghai Jiao Tong University, Shanghai, China

5. Carnegie Mellon University, Pittsburgh, USA

6. University of Southern California, Los Angeles, USA

Funder

Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone Project

National Science Foundation

David and Lucile Packard Foundation

Simons Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3618260.3649672

Reference52 articles.

1. Ishaq Aden-Ali, Yanjun Han, Jelani Nelson, and Huacheng Yu. 2022. On the amortized complexity of approximate counting. CoRR, abs/2211.03917 (2022).

2. Yuqing Ai, Wei Hu, Yi Li, and David P. Woodruff. 2016. New Characterizations in Turnstile Streams with Applications. In 31st Conference on Computational Complexity, CCC 2016, May 29 to June 1, 2016, Tokyo, Japan, Ran Raz (Ed.) (LIPIcs, Vol. 50). Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 20:1–20:22.

3. The White-Box Adversarial Data Stream Model

4. The Space Complexity of Approximating the Frequency Moments

5. Streaming Algorithms via Precision Sampling

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