Correcting errors without leaking partial information

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On the Difficulties of Disclosure Prevention in Statistical Databases or The Case for Differential Privacy (2010, methodology): “Unlike most applications of fuzzy extractors (see, in particular, [13, 14]), in this proof we are not interested in hiding partial information about the source, in our case the approximate utility vectors w′ revealed by the San mechanism, so we don’t care how much min-entropy is used up in generatin”
Fuzzy Extractors: How to Generate Strong Keys from Biometrics and Other Noisy Data (2004, unknown): “appeared (e.g., [Boy04, BDK + 05, DS05 , DORS06, Smi07, CL06, LSM06, CFL06]).”
Leftover Hashing Against Quantum Side Information (2010, background): “For example, XORing a classical source about which an adversary holds quantum information with a -biased mask (as in [20]) results in a uniformly distributed string even when conditioned on quantum side information [21]9.”
On the (im)possibility of obfuscating programs (2001, background): “[1978], Feigenbaum and Merritt [1991], Dolev et al. [2000], Boneh and Lipton [1996], and Sander et al.”
Differential Privacy (2006, unknown): “We remark that, unlike in the case of most applications of fuzzy extractors (see, in particular, [10, 11]), in this proof we are not interested in hiding partial information about the source, in our case the approximate utility vectors W , so we don’t care how much min-entropy is used up in…”