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Algebraic Characterizations of Small Classes of Boolean Functions

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STACS 2003 (STACS 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2607))

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Abstract

Programs over semigroups are a well-studied model of computation for boolean functions. It has been used successfully to characterize, in algebraic terms, classes of problems that can, or cannot, be solved within certain resources. The interest of the approach is that the algebraic complexity of the semigroups required to capture a class should be a good indication of its expressive (or computing) power. In this paper we derive algebraic characterizations for some “small” classes of boolean functions, all of which have depth-3 AC0 circuits, namely k-term DNF, k-DNF, k-decision lists, decision trees of bounded rank, and DNF. The interest of such classes, and the reason for this investigation, is that they have been intensely studied in computational learning theory.

Partially supported by the IST Programme of the EU under contract number IST-1999-14186 (ALCOM-FT), by the Spanish Government TIC2001-1577-C03-02 (LOGFAC), by CIRIT 1997SGR-00366, and TIC2000-1970-CE.

Supported by NSERC, FCAR, and the von Humboldt Foundation.

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References

  1. D. Angluin. Learning regular sets from queries and counterexamples. Information and Computation, 75:87–106, 1987.

    Article  MATH  MathSciNet  Google Scholar 

  2. D. Angluin. Queries and concept learning. Machine Learning, 2:319–342, 1988.

    Google Scholar 

  3. D.A. Barrington. Bounded-width polynomial-size branching programs recognize exactly those languages in NC1. Journal of Computer and System Sciences, 38:150–164, 1989.

    Article  MATH  MathSciNet  Google Scholar 

  4. A.L. Blum. Rank-r decision trees are a subclass of r-decision lists. Information Processing Letters, 42:183–185, 1992.

    Article  MATH  MathSciNet  Google Scholar 

  5. M. Beaudry, P. McKenzie, and D. Thérien. The membership problem in aperiodic transformation monoids. Journal of the ACM, 39(3):599–616, 1992.

    Article  MATH  Google Scholar 

  6. A. Blum and S. Rudich. Fast learning of k-term dnf formulas with queries. Journal of Computer and System Sciences, 51:367–373, 1995.

    Article  MathSciNet  Google Scholar 

  7. N.H. Bshouty. Exact learning boolean functions via the monotone theory. Information and Computation, 123:146–153, 1995.

    Article  MATH  MathSciNet  Google Scholar 

  8. D.A. Mix Barrington, H. Straubing, and D. Thérien. Non-uniform automata over groups. Information and Computation, 89:109–132, 1990.

    Article  MATH  MathSciNet  Google Scholar 

  9. D.A. Mix Barrington and D. Thérien. Finite monoids and the fine structure of NC1. Journal of the ACM, 35:941–952, 1988.

    Article  Google Scholar 

  10. J. Castro and J.L. Balcázar. Simple PAC learning of simple decision lists. In Algorithmic Learning Theory, 6th International Workshop, ALT’ 95, Proceedings, volume 997, pages 239–248. Springer, 1995.

    Google Scholar 

  11. A. Ehrenfeucht and D. Haussler. Learning decision trees from random examples. Information and Computation, 82:231–246, 1989.

    Article  MATH  MathSciNet  Google Scholar 

  12. S. Eilenberg. Automata, Languages, and Machines, volume B. Academic Press, 1976.

    Google Scholar 

  13. T. Elomaa. The biases of decision tree pruning strategies. In Advances in Intelligent Data Analysis: Proc. 3rd Intl. Symp., pages 63–74, 1999.

    Google Scholar 

  14. R. Gavaldà, D. Thérien, and P. Tesson. Learning expressions and programs over monoids. In Technical Report R01-38, Department LSI, UPC, pages-, 2001.

    Google Scholar 

  15. J.C. Jackson. An efficient membership-query algorithm for learning dnf. Journal of Computer and System Sciences, 53:414–440, 1997.

    Article  Google Scholar 

  16. M.J. Kearns and U.V. Vazirani. An Introduction to Computational Learning Theory. The MIT Press, 1994.

    Google Scholar 

  17. A. Maciel, P. Péladeau, and D. Thérien. Programs over semigroups of dotdepth one. Theoretical Computer Science, 245:135–148, 2000.

    Article  MATH  MathSciNet  Google Scholar 

  18. Ronald L. Rivest. Learning decision lists. Machine Learning, 2(3):229–246, 1987.

    Google Scholar 

  19. J.-F. Raymond, P. Tesson, and D. Thérien. An algebraic approach to communication complexity. In Proc. ICALP’98, Springer-Verlag LNCS, volume 1443, pages 29–40, 1998.

    Google Scholar 

  20. M.P. Schützenberger. Sur le produit de concaténation non ambigu. Semigroup Forum, 13:47–75, 1976.

    Google Scholar 

  21. H.U. Simon. Learning decision lists and trees with equivalence queries. In Proceedings of the 2nd European Conference on Computational Learning Theory (EuroCOLT’95), pages 322–336, 1995.

    Google Scholar 

  22. M. Szegedy. Functions with bounded symmetric communication complexity, programs over commutative monoids, and acc. Journal of Computer and System Sciences, 47:405–423, 1993.

    Article  MATH  MathSciNet  Google Scholar 

  23. D. Thérien. Programs over aperiodic monoids. Theoretical Computer Science, 64(3):271–280, 29 1989.

    Article  MATH  MathSciNet  Google Scholar 

  24. D. Thérien and P. Tesson. Diamonds are forever: the DA variety. In submitted, 2001.

    Google Scholar 

  25. L.G. Valiant. A theory of the learnable. Communications of the ACM, 27:1134–1142, 1984.

    Article  MATH  Google Scholar 

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Gavaldà, R., Thérien, D. (2003). Algebraic Characterizations of Small Classes of Boolean Functions. In: Alt, H., Habib, M. (eds) STACS 2003. STACS 2003. Lecture Notes in Computer Science, vol 2607. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36494-3_30

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  • DOI: https://doi.org/10.1007/3-540-36494-3_30

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  • Print ISBN: 978-3-540-00623-7

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