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dc.contributor.authorChor, Bennyen_US
dc.contributor.authorGoldreich, Odeden_US
dc.date.accessioned2023-03-29T14:26:37Z
dc.date.available2023-03-29T14:26:37Z
dc.date.issued1986-09
dc.identifier.urihttps://hdl.handle.net/1721.1/149092
dc.description.abstractA 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.ispartofseriesMIT-LCS-TM-283
dc.titleUnbiased Bits from Sources of Weak Randomness and Probabilistic Communication Complexityen_US


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