The DOI matches its Crossref record.
Computing with Noisy Information
Abstract
This paper studies the depth of noisy decision trees in which each node gives the wrong answer with some constant probability. In the noisy Boolean decision tree model, tight bounds are given on the number of queries to input variables required to compute threshold functions, the parity function and symmetric functions. In the noisy comparison tree model, tight bounds are given on the number of noisy comparisons for searching, sorting, selection and merging. The paper also studies parallel selection and sorting with noisy comparisons, giving tight bounds for several problems.
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Citations
Cited by
Crowdsourced Data Management: A Survey
Li, G., Wang, J., Zheng, Y., & Franklin, M. J. (2016) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2016.2535242 · Cited by 283
Quantum proofs for classical theorems
(2011) · Theory of Computing · doi:10.4086/toc.gs.2011.002 · Cited by 41
Algorithmic monoculture and social welfare
(2023) · The Societal Impacts of Algorithmic Decision-Making · doi:10.1145/3603195.3603202
Metadata
- Authors
- Feige, U., Raghavan, P., Peleg, D., & Upfal, E.
- Venue
- SIAM Journal on Computing
- Published
- 1994-10
- Volume
- 23
- Issue
- 5
- Pages
- 1001-1018
- ISSN
- 0097-5397 (ISSN-L)
- 1095-7111
- OpenAlex
- W2038435918
- Cited by
- 304
- References
- 0
- FWCI
- 2.42
- Type
- journal article
- Language
- en
- Open access
- closed
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: Computing with Noisy Information. https://app.cochat.ai/papers/10.1137/s0097539791195877
- The paper
- Feige, U., Raghavan, P., Peleg, D., & Upfal, E. (1994). Computing with Noisy Information. SIAM Journal on Computing. https://doi.org/10.1137/s0097539791195877
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
