Learning one-variable pattern languages very efficiently on average, in parallel, and by asking queries

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1316, Issue , 1997, Pages 260-276

  Erlebach, Thomas ^a   Rossmanith, Peter ^a   Stadtherr, Hans ^a   Steger, Angelika ^a   Zeugmann, Thomas ^b  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^b KYUSHU UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATION THEORY; COMPUTATIONAL LINGUISTICS; PROBABILITY DISTRIBUTIONS; QUERY LANGUAGES;

CONSTANT FACTORS; EQUAL PROBABILITY; LEARNING TIME; NON-EMPTY STRINGS; PARALLEL VERSION; PATTERN LANGUAGES; POLYNOMIAL NUMBER; TARGET LANGUAGE;

LEARNING SYSTEMS;

EID: 84958039201     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-63577-7_48     Document Type: Conference Paper

References (22)

1. D. Angluin. Finding patterns common to a set of strings. Journal of Computer and System Sciences, 21:46-62, 1980.
2. D. Angluin. Inductive inference of formal languages from positive data. Information and Control, 45:117-135, 1980.
3. D. Angluin. Queries and concept learning. Machine Learning, 2:319-342, 1988.
4. T. Erlebach, P. Rossmanith, H. Stadtherr, A. Steger, and T. Zeugmann. Efficient Learning of One-Variable Pattern Languages from Positive Data. DOI-TR-128, Department of Informatics, Kyushu University, Dee. 12, 1996; http://www.i.kyushuu.ac.jp/,vthomas/treport.html
5. G. Filé. The relation of two patterns with comparable languages. In Proc. 5th Ann. Symp. Theoretical Aspects of Computer Science, LNCS 294, pp. 184-192, Berlin, 1988. Springer-Verlag.
6. S. Fortune and J. Wyllie. Parallelism in random access machines. In Proc. 10th Ann. ACM Syrup. Theory of Computing, pp. 114-118, New York, 1978, ACM Press.
7. E. M. Gold. Language identification in the limit, Inf. Control, 10:447-474, 1967.
8. J. JáJá. An introduction to parallel algorithms. Addison-Wesley, 1992.
9. K. P. Jantke. Polynomial time inference of general pattern languages. In Proc. Symp. Theoretical Aspects of Computer Science, LNCS 166, pp. 314-325, Berlin, 1984. Springer-Verlag.
10. T. Jiang, A. Salomaa, K. Salomaa, and S. Yu. Inclusion is undecidable for pattern languages. In Proc. 20th Int. Colloquium on Automata, Languages and Programming, LNCS 700, pp. 301-312, Berlin, 1993. Springer-Verlag.
11. M. Kearns and L. Pitt. A polynomial-time algorithm for learning k-variable pattern languages from examples. In Proc. 2nd Ann. ACM Workshop on Computational Learning Theory, pp. 57-71, Morgan Kaufmann Publ., San Mateo, 1989.
12. K.-I. Ko and C.-M. Hua. A note on the two-variable pattern-finding problem. J. Comp. Syst. Sci., 34:75-86, 1987.
13. S. Lange and R. Wiehagen. Polynomial-time inference of arbitrary pattern languages. New Generation Computing, 8:361-370, 1991.
14. S. Lange and T. Zeugmann. Set-driven and rearrangement-independent learning of recursive languages. Mathematical Systems Theory, 29:599-634, 1996.
15. D. Osherson, M. Stob and S. Weinstein. Systems that learn: An introduction to learning theory for cognitive and computer scientists. MIT Press, 1986
16. L. Pitt. Inductive inference, DFAs and computational complexity. In Proc. Analogical and Inductive Inference, LNAI 397, pp. 18-44, Berlin, 1989, Springer-Verlag.
17. A. Saloma~. Patterns. EATCS Bulletin 54:46-62, 1994.
18. A. Salomaa. Return to patterns. EATCS Bulletin 55:144-157, 1994.
19. T. Shinotmra and S. Arikawa. Pattern inference. In Algorithmic Learning for Knowledge-Based Systems, LNAI 961, pp. 259-291, Berlin, 1995. Springer-Verlag.
20. K. Wexler and P. Culicover. Formal Principles of Language Acquisition. MIT Press, Cambridge, MA, 1980.
21. T. Zeugmann. Lange and Wiehagen's pattern language learning algorithm: An average-case analysis with respect to its total learning time. Annals of Mathematics and Artificial Intelligence, 1997, to appear.
22. T. Zeugmann and S. Lange. A guided tour across the boundaries of learning recursive languages. In Algorithmic Learning for Knowledge-Based Systems, LNAI 961, pp. 190-258, Berlin, 1995. Springer-Verlag.