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Unbiased Bits from Sources of Weak Randomness and Probabilistic Communication Complexity
Abstract
A new model for weak random physical sources is presented. The new model strictly generalizes previous models (e.g., the Santha and Vazirani model [27]). The sources considered output strings according to probability distributions in which no single string is too probable. The new model provides a fruitful viewpoint on problems studied previously such as: • Extracting almost-perfect bits from sources of weak randomness. The question of possibility as well as the question of efficiency of such extraction schemes are addressed. • Probabilistic communication complexity. It is shown that most functions have linear communication complexity in a very strong probabilistic sense. • Robustness of BPP with respect to sources of weak randomness (generalizing a result of Vazirani and Vazirani [32], [33]).
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Cited by
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Linear degree extractors and the inapproximability of max clique and chromatic number
Zuckerman, D. (2006) · Proceedings of the thirty-eighth annual ACM symposium on Theory of Computing · doi:10.1145/1132516.1132612 · Cited by 398
Extractors and pseudorandom generators
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Extracting all the randomness and reducing the error in Trevisan's extractors
Raz, R., Reingold, O., & Vadhan, S. (1999) · Proceedings of the thirty-first annual ACM symposium on Theory of Computing · doi:10.1145/301250.301292 · Cited by 171
Metadata
- Authors
- Chor, B., & Goldreich, O.
- Venue
- SIAM Journal on Computing
- Published
- 1988-04
- Volume
- 17
- Issue
- 2
- Pages
- 230-261
- ISSN
- 0097-5397 (ISSN-L)
- 1095-7111
- OpenAlex
- W2151303208
- Cited by
- 544
- References
- 0
- FWCI
- 5.42
- Type
- journal article
- Language
- en
- Open access
- closed
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- Chor, B., & Goldreich, O. (1988). Unbiased Bits from Sources of Weak Randomness and Probabilistic Communication Complexity. SIAM Journal on Computing. https://doi.org/10.1137/0217015
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