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Showing 1 to 6 of 6 for “"Randomness extractors"”.

  1. The method of multiplicities

    … correcting codes, pseudorandom generators and randomness extractors. Somewhat strikingly, polynomials have also been found to be a powerful tool in the analysis of combinatorial parameters of objects that have some algebraic structure. This method of analysis has found applications in works on …

    mit Repository record for The method of multiplicities (opens in a new tab)

  2. Maintaining secrecy when information leakage is unavoidable

    … tools from complexity theory known as randomness extractors.

    mit Repository record for Maintaining secrecy when information leakage is unavoidable (opens in a new tab)

  3. Kakeya sets and the method of multiplicities

    … results, of interest in combinatorics and randomness extraction. 1. We show that every Kakeya set (a set of points that contains a line in every direction) in F' must be of size at least qn/2n. This bound is tight to within a 2 + o(1) factor for every n as q -- oc, compared to previous …

    mit Repository record for Kakeya sets and the method of multiplicities (opens in a new tab)

  4. Algebraic methods in randomness and pseudorandomness

    Algebra and randomness come together rather nicely in computation. A central example of this relationship in action is the Schwartz-Zippel lemma and its application to the fast randomized checking of polynomial identities. In this thesis, we further this relationship in two ways: (1) by compiling …

    mit Repository record for Algebraic methods in randomness and pseudorandomness (opens in a new tab)

  5. Seedless Extractors

    Randomness is a powerful tool, exploited almost everywhere in computer science – from cryptography, to distributed computing, to algorithm design and more. Unfortunately, most of these applications require access to perfectly uniform bits, while randomness harvested from nature (e.g., atmospheric …

    cornell Repository record for Seedless Extractors (opens in a new tab)

  6. Sparse graph codes for compression, sensing, and secrecy

    … because they provide a method for constructing randomness extractors. Finally, we use several well-known isoperimetric inequalities (Harper's inequality, Azuma's inequality, and the Gaussian Isoperimetric inequality) in our analysis of the duality between lossy source coding and channel coding.

    mit Repository record for Sparse graph codes for compression, sensing, and secrecy (opens in a new tab)