Unbiased Bits from Sources of Weak Randomness and Probabilistic Communication Complexity
dc.contributor.author | Chor, Benny | en_US |
dc.contributor.author | Goldreich, Oded | en_US |
dc.date.accessioned | 2023-03-29T14:26:37Z | |
dc.date.available | 2023-03-29T14:26:37Z | |
dc.date.issued | 1986-09 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/149092 | |
dc.description.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 [26]). 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 as: 1) 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. 2) Probabilistic Communication Complexity: it is shown that most functions have linear communication complexity in a very strong probabilistic sense. 3) Robustness of BPP with respect to sources of weak randomness (generalizing a result of Vazirani and Vazirani [29]). | en_US |
dc.relation.ispartofseries | MIT-LCS-TM-283 | |
dc.title | Unbiased Bits from Sources of Weak Randomness and Probabilistic Communication Complexity | en_US |