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2012 IEEE 27th Conference on Computational Complexity (1996)
Philadelphia, PA
May 24, 1996 to May 27, 1996
ISBN: 0-8186-7386-9
pp: 59
Joan Feigenbaum , AT & T Research
Lance Fortnow, Sophie Laplante, and Ashish V. Naik We address two questions about self-reducibility--the power of adaptiveness in examiners that take advice and the relationship between random-self-reducibility and self-correctability. We first show that adaptive examiners are more powerful than nonadaptive examiners, even if the nonadaptive ones are nonuniform. Blum et al. [Blum, Luby and Rubinfeld, Journal of Computer and System Sciences, 59:549--595, 1993] showed that every random-self-reducible function is self-correctable. However, whether self-correctability implies random-self-reducibility is unknown. We show that, under a reasonable complexity hypothesis, there exists a self-correctable function that is not random-self-reducible. For P-sampleable distributions, however, we show that constructing a self-correctable function that is not random-self-reducible is as hard as proving that P is not equal to PP.
Computational complexity, coherence, self-correctability, random-self-reducibility, polynomial advice, Kolmogorov complexity, adaptive versus nonadaptive oracle machines
Joan Feigenbaum, "On Coherence, Random-Self-Reducibility, and Self-Correction", 2012 IEEE 27th Conference on Computational Complexity, vol. 00, no. , pp. 59, 1996, doi:10.1109/CCC.1996.507668
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