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The space complexity of approximating the frequency moments
Abstract
The frequency moments of a sequence containing m i elements of type i, for 1 i n, are the numbers Fk = P n i=1 m k i . We consider the space complexity of randomized algorithms that approximate the numbers Fk , when the elements of the sequence are given one by one and cannot be stored. Surprisingly, it turns out that the numbers F0
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Cited by
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Datar, M., Gionis, A., Indyk, P., & Motwani, R. (2002) · SIAM Journal on Computing · doi:10.1137/s0097539701398363 · Cited by 835
Geometric median and robust estimation in Banach spaces
Minsker, S. (2015) · Bernoulli · doi:10.3150/14-bej645 · Cited by 261
Algorithmic applications of low-distortion geometric embeddings
Indyk, P. (2001) · Proceedings 42nd IEEE Symposium on Foundations of Computer Science · doi:10.1109/sfcs.2001.959878 · Cited by 253
Temporal abstraction in intelligent clinical data analysis: A survey
Stacey, M., & McGregor, C. (2007) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2006.08.002 · Cited by 146
Synthesis of divide and conquer parallelism for loops
Farzan, A., & Nicolet, V. (2017) · Proceedings of the 38th ACM SIGPLAN Conference on Programming Language Design and Implementation · doi:10.1145/3062341.3062355 · Cited by 25
Metadata
- Authors
- Alon, N., Matias, Y., & Szegedy, M.
- Venue
- Proceedings of the twenty-eighth annual ACM symposium on Theory of computing - STOC '96
- Publisher
- ACM Press
- Published
- 1996
- Pages
- 20-29
- OpenAlex
- W2064379477
- Cited by
- 822
- References
- 0
- FWCI
- 2.90
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: The space complexity of approximating the frequency moments. https://app.cochat.ai/papers/10.1145/237814.237823
- The paper
- Alon, N., Matias, Y., & Szegedy, M. (1996). The space complexity of approximating the frequency moments. Proceedings of the twenty-eighth annual ACM symposium on Theory of computing - STOC '96. https://doi.org/10.1145/237814.237823
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
