Generating quasi-random sequences from semi-random sources
Journal of Computer and System Sciences
On using deterministic functions to reduce randomness in probabilistic algorithms
Information and Computation
Combinatorica - Theory of Computing
Unbiased bits from sources of weak randomness and probabilistic communication complexity
SIAM Journal on Computing - Special issue on cryptography
Expanders, randomness, or time versus space
Journal of Computer and System Sciences - Structure in Complexity Theory Conference, June 2-5, 1986
Pseudo-random generation from one-way functions
STOC '89 Proceedings of the twenty-first annual ACM symposium on Theory of computing
Simulating BPP using a general weak random source
SFCS '91 Proceedings of the 32nd annual symposium on Foundations of computer science
SIAM Journal on Computing
Expanders that beat the eigenvalue bound: explicit construction and applications
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Graph augmentation and related problems: theory and practice
Graph augmentation and related problems: theory and practice
Journal of Computer and System Sciences
On extracting randomness from weak random sources (extended abstract)
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Randomness-optimal sampling, extractors, and constructive leader election
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
P = BPP if E requires exponential circuits: derandomizing the XOR lemma
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
A new general derandomization method
Journal of the ACM (JACM)
Worst-Case Hardness Suffices for Derandomization: A New Method for Hardness-Randomness Trade-Offs
ICALP '97 Proceedings of the 24th International Colloquium on Automata, Languages and Programming
Extracting Randomness: How and Why - A survey
CCC '96 Proceedings of the 11th Annual IEEE Conference on Computational Complexity
Weak random sources, hitting sets, and BPP simulations
FOCS '97 Proceedings of the 38th Annual Symposium on Foundations of Computer Science
Random Polynomial Time is Equal to Semi-Random Polynomial Time
Random Polynomial Time is Equal to Semi-Random Polynomial Time
Randomness, adversaries and computation (random polynomial time)
Randomness, adversaries and computation (random polynomial time)
Computing with very weak random sources
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
A new general derandomization method
Journal of the ACM (JACM)
Construction of extractors using pseudo-random generators (extended abstract)
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Extracting all the randomness and reducing the error in Trevisan's extractors
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Loss-less condensers, unbalanced expanders, and extractors
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Extractors and pseudorandom generators
Journal of the ACM (JACM)
Extracting all the randomness and reducing the error in Trevisan's extractors
Journal of Computer and System Sciences - STOC 1999
Derandomizing Arthur-Merlin Games under Uniform Assumptions
ISAAC '00 Proceedings of the 11th International Conference on Algorithms and Computation
Derandomizing Arthur-Merlin Games Using Hitting Sets
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
Uniform hardness versus randomness tradeoffs for Arthur-Merlin games
Computational Complexity
Derandomizing Arthur-Merlin games using hitting sets
Computational Complexity
An introduction to randomness extractors
ICALP'11 Proceedings of the 38th international conference on Automata, languages and programming - Volume Part II
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An (N, M, T)-OR-disperser is a bipartite multigraph G=(V, W, E) with |V| = N, and |W| = M, having the following expansion property: any subset of V having at least T vertices has a neighbor set of size at least M/2. For any pair of constants &xgr;, &lgr;, 1 ≥ &xgr; &lgr; ≥ 0, any sufficiently large N, and for any T ≥ 2(logN) M ≤ 2(log N)&lgr;, we give an explicit elementary construction of an (N, M, T)-OR-disperser such that the out-degree of any vertex in V is at most polylogarithmic in N. Using this with known applications of OR-dispersers yields several results. First, our construction implies that the complexity class Strong-RP defined by Sipser, equals RP. Second, for any fixed &eegr; 0, we give the first polynomial-time simulation of RP algorithms using the output of any “&eegr;-minimally random” source. For any integral R 0, such a source accepts a single request for an R-bit string and generates the string according to a distribution that assigns probability at most 2−R&eegr; to any string. It is minimally random in the sense that any weaker source is insufficient to do a black-box polynomial-time simulation of RP algorithms.