Fast probabilistic algorithms

  • Rūsiņš Freivalds
Invited Lectures
Part of the Lecture Notes in Computer Science book series (LNCS, volume 74)


Turing Machine Probabilistic Machine Deterministic Machine Probabilistic Turing Machine Multicounter Machine 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    BARZDIN, J.M., Complexity of symmetry recognition by Turing machines. In: Problemy kibernetiki 15, pp.245–248, Nauka, Moscow, 1965 (Russian).Google Scholar
  2. 2.
    BUKHŠTAB, A.A., Number theory. Učpedgiz, Moscow, 1960 (Russian).Google Scholar
  3. 3.
    FISCHER, P.C., MEYER, A.R. and ROSENBERG A.L., Counter machines and counter languages. Mathematical Systems Theory, 2(1968), No.3, 265–283.CrossRefGoogle Scholar
  4. 4.
    FREIVALDS, R., Fast computations by probabilistic Turing machines. In: Učenye Zapiski Latviiskogo gos. universiteta, 233, pp.201–205, Riga, 1975 (Russian).Google Scholar
  5. 5.
    FREIVALDS, R., Probabilistic machines can use less running time. In: Information Processing 77, (B.Gilchrist, Ed.), pp.839–842, IFIP, North-Holland, 1977.Google Scholar
  6. 6.
    FREIVALDS, R., Probabilistic algorithms in proof-oriented computations. In: Proc. All-Union symposium "Artificial intelligence and automation of research in mathematics", 102–104, Institute of Cybernetics, Kiev, 1978 (Russian).Google Scholar
  7. 7.
    GINSBURG, S., GREIBACH, S.A. and HARRISON, M.A., Stack automata and compiling. Journal of the ACM, 14 (1967), 172–201.CrossRefGoogle Scholar
  8. 8.
    GREIBACH, S.A., Remarks on blind and partially blind one-way multicounter machines. Theoretical Computer Sciencè, 7 (1978), No.3, 311–324.CrossRefGoogle Scholar
  9. 9.
    KNUTH, D.E., The art of computer programming. Vol.2. Addison-Wesley Publishing Co., Reading, Mass., 1969.Google Scholar
  10. 10.
    LIVŠIN, D.I., On a class of stack languages. In: Mathematical linguistics and theory of algorithms, (A.V. Gladkij, Ed.), pp. 113–129, Kalinin State University, Kalinin, 1978 (Russian).Google Scholar
  11. 11.
    LAING, R., Realization and complexity of commutative events. University of Michigan, Technical Report 03105-48-T, 1967.Google Scholar
  12. 12.
    LEEUW, K. de, MOORE E.F., SHANNON, C.E. and SHAPIRO, N., Computability by probabilistic machines. Automata Studies, (C.E.Shannon and J.McCarthy, Eds.), pp.183–212, Princeton University Press, 1956.Google Scholar
  13. 13.
    MINSKY, M., Recursive unsolvability of Post's problem of Tag and other topics in the theory of Turing machines. Annals of Mathematics, 74 (1961), 437–455.Google Scholar
  14. 14.
    PAN, V., Strassen's algorithm is not optimal. Proc. 19th annual symposium on foundations of computer science, pp.166–176, IEEE, 1978.Google Scholar
  15. 15.
    SOLOVAY, R. and STRASSEN, V., A fast Monte-Carlo test for primality. SIAM Journal on Computing, 6 (1977), No.1, 84–85.CrossRefGoogle Scholar
  16. 16.
    STRASSEN, V., Gaussian elimination is not optimal. Numerische Mathematik, 13 (1969), H.4, 354–356.Google Scholar
  17. 17.
    TRAKHTENBROT, B.A., Remarks on the computational complexity by probabilistic machines. In: Teorija algoritmov i matematičeskaja logika, pp.159–176, Comp. Ctr.Acad.Sci.USSR, Moscow, 1974 (Russian).Google Scholar
  18. 18.
    YAO, A.C., A lower bound to palindrome recognition by probabilistic Turing machines. STAN-CS-647, Stanford University, 1977.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1979

Authors and Affiliations

  • Rūsiņš Freivalds
    • 1
  1. 1.Computing CentreLatvian State UniversityRigaUSSR

Personalised recommendations