Pseudorandomness and Average-Case Complexity via Uniform Reductions

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Pseudorandomness and Average-Case Complexity via Uniform Reductions

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Title: Pseudorandomness and Average-Case Complexity via Uniform Reductions
Author: Trevisan, Luca; Vadhan, Salil

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Citation: Trevisan, Luca and Salil Vadhan. 2007. Pseudorandomness and average-case complexity via uniform reductions. Computational Complexity, 16, no. 4: 331-364.
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Abstract: Impagliazzo and Wigderson (36th FOCS, 1998) gave the first construction of pseudorandom generators from a uniform complexity assumption on EXP (namely EXP [not equal to] BPP). Unlike results in the nonuniform setting, their result does not provide a continuous trade-off between worst-case hardness and pseudorandomness, nor does it explicitly establish an average-case hardness result. In this paper: 1. We obtain an optimal worst-case to average-case connection for EXP: if EXP is not a subset of BPTIME(t(n)), EXP has problems that cannot be solved on a fraction 1/2 +1/t'(n) of the inputs by BPTIME(t'(n)) algorithms, for t'=t^{\Omega(1)}. 2. We exhibit a PSPACE-complete self-correctible and downward self-reducible problem. This slightly simplifies and strengthens the proof of Impaglaizzo and Wigderson, which used a a #P-complete problem with these properties. 3. We argue that the results of Impagliazzo and Wigderson, and the ones in this paper, cannot be proved via "black-box" uniform reductions.
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  • FAS Scholarly Articles [7682]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University

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