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Electronic Colloquium on Computational Complexity

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REPORTS > KEYWORD > SAMPLABLE DISTRIBUTION:
Reports tagged with samplable distribution:
TR11-167 | 6th December 2011
Nikolay Vereshchagin

Improving on Gutfreund, Shaltiel, and Ta-Shma's paper "If NP Languages are Hard on the Worst-Case, Then it is Easy to Find Their Hard Instances''

Revisions: 1

Assume that $NP\ne RP$. Gutfreund, Shaltiel, and Ta-Shma in [Computational Complexity 16(4):412-441 (2007)] have proved that for every randomized polynomial time decision algorithm $D$ for SAT there is a polynomial time samplable distribution such that $D$ errs with probability at least $1/6-\epsilon$ on a random formula chosen with respect to ... more >>>




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