Learning unions of tree patterns using queries

Theoretical Computer Science

Volumn 185, Issue 1, 1997, Pages 47-62

  Arimura, Hiroki ^a   Ishizaka, Hiroki ^b   Shinohara, Takeshi ^b  

^a KYUSHU UNIVERSITY   (Japan)

^b KYUSHU INSTITUTE OF TECHNOLOGY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; EQUIVALENCE CLASSES; LEARNING ALGORITHMS; LOGIC PROGRAMMING; MEMBERSHIP FUNCTIONS; POLYNOMIALS; QUERY LANGUAGES;

TREE PATTERNS;

LEARNING SYSTEMS;

EID: 0031249272     PISSN: 03043975     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0304-3975(97)00015-7     Document Type: Article

References (20)

1. D. Angluin, Finding patterns common to a set of strings, J. Comput. System Sci. 21 (1980) 46-62.
2. D. Angluin, Queries and concept learning, Machine Learning 2 (1988) 319-342.
3. D. Angluin, M. Frazier, L. Pitt, Learning conjunctions of Horn clauses, Machine Learning 9 (1992) 147-164.
4. S. Arikawa, S. Kuhara, S. Miyano, A. Shinohara, T. Shinohara, A learning algorithm for elementary formal systems and its experiments on identification of transmembrane domains, in: Proc. 25th HICSS (1992) 675-684.
5. H. Arimura, T. Shinohara, S. Otsuki, A polynomial time algorithm for finding finite unions of tree pattern languages, in: Proc. 2nd Nonmonotonic and Inductive Logic, Lecture Notes in Artificial Intelligence, Vol. 659, Springer, Berlin, 1991, 118-131.
6. H. Arimura, T. Shinohara, S. Otsuki, Finding minimal generalizations for unions of pattern languages and its application to inductive inference from positive data, in: Proc. 11th Symp. on Theoretical Aspects of Computer Science, Lecture Notes in Computer Science, Vol. 775, Springer, Berlin, 1994, 649-660.
7. H. Arimura, H. Ishizaka, T. Shinohara, S. Otsuki, A generalization of the least generalization, in: Machine Intelligence, Vol. 13, Oxford Univ. Press, Oxford, 1994, 59-85.
8. W. Cohen, H. Hirsh, Learnability of description logics with equality constraints, Machine Learning 17 (1994) 169-199.
9. M. Frazier, L. Pitt, Classic learning, in: Proc. COLT'94 (1994) 23-34.
10. H. Ishizaka, H. Arimura, T. Shinohara, Finding tree patterns consistent with positive and negative examples using queries, in: Proc. Algorithmic Learning Theory '94, Lecture Notes in Artificial Intelligence, Vol. 872, Springer, Berlin, 1994, 317-332.
11. T. Jiang, A. Salomaa, K. Salomaa, S. Yu, Inclusion is undecidable for pattern languages, in: Proc. 20th ICALP, Lecture Notes in Computer Science, Vol. 700, Springer, Berlin, 1993, 301-312.
12. G. Kuper, K. McAloon, K. Palem, K. Perry, Efficient parallel algorithm for anti-unification and relative complement, in: Proc. 3rd LICS (1988) 111-120.
13. N. Littlestone, Learning quickly when irrelevant attributes abound: a new linear-threshold algorithm, Machine Learning 2 (1988) 285-318.
14. W. Maass, G. Turán, Lower bound methods and separation results for on-line learning models, Machine Learning 9 (1992) 107-145.
15. C.D. Page Jr., A.M. Frisch, Generalization and learnability: a study of constrained atoms, in: S. Muggleton (Ed.), Inductive Logic Programming (1992) 29-61.
16. L. Pitt, L.G. Valiant, Computational limitations on learning from examples, J. ACM 35 (1988) 965-984.
17. L. Pitt, M.K. Warmuth, Prediction preserving reduction, J. Comput. System Sci. 41 (1990) 430-467.
18. G.D. Plotkin, A note on inductive generalization, in: Machine Intelligence, Vol. 5, Edinburgh University Press, Edinburgh, 1970, pp. 153-163.
19. J.C. Reynolds, Transformational systems and the algebraic structure of atomic formulas, in: Machine Intelligence, Vol. 5, Edinburgh University Press, Edinburgh, 1970, pp. 135-152.
20. T. Zeugmann, Lange and Wiehagen's pattern language learning algorithm: an average-case analysis with respect to its total learning time, RIFIS-TR-CS-111, Kyushu University, 1995.