Sampling a population with a semi-random source

Extended abstract
  • Umesh V. Vazirani
  • Vijay V. Vazirani
Session 7 Complexity
Part of the Lecture Notes in Computer Science book series (LNCS, volume 241)


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [CG]
    B. Chor and O. Goldreich, "Unbiased Bits from Weak Sources of Randomness," 26th. IEEE Symposium on the Foundations of Computer Science, 1985.Google Scholar
  2. [Rg]
    P. Raghavan, "Probabilistic Construction of Deterministic Algorithms: Approximating Packing Integer Programs," Annual IEEE Symposium on Foundations of Computing 1986.Google Scholar
  3. [SV]
    M. Santha and U.V. Vazirani, "Generating Quasi-random Sequences from Slightly-random Sources," Proc. 25th Ann. Symp. on the Theory of Computing. Oct. 1984, pp. 434–440.Google Scholar
  4. [Va]
    U.V. Vazirani, Towards a Strong Communication Complexity Theory or Generating Quasi-Random Sequences from Two Communicating Slightly-random Sources,” Proc. STOC 1985.Google Scholar
  5. [VV]
    U.V. Vazirani and V.V. Vazirani, "Random Polynomial Time is Equal to Slightly-Random Polynomial Time," Proceedings of FOCS 1985, submitted to JACM.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1986

Authors and Affiliations

  • Umesh V. Vazirani
    • 1
  • Vijay V. Vazirani
    • 2
  1. 1.Harvard UniversityCambridge
  2. 2.AT&T Bell LabsMurray Hill

Personalised recommendations