Learning rational stochastic tree languages

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

Volumn 4754 LNAI, Issue , 2007, Pages 242-256

  Denis, François ^a   Habrard, Amaury ^a  

^a AIX MARSEILLE UNIVERSITY   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; FORMAL LANGUAGES; PARAMETER ESTIMATION; PROBABILITY DISTRIBUTIONS; STOCHASTIC MODELS; TREES (MATHEMATICS);

MULTIPLICITY TREE AUTOMATON; RATIONAL STOCHASTIC; STOCHASTIC TREE LANGUAGES;

LEARNING SYSTEMS;

EID: 38149007130     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-75225-7_21     Document Type: Conference Paper

References (16)

1. Carrasco, R., Oncina, J., Calera-Rubio, J.: Stochastic inference of regular tree languages. Machine Learning 44(1/2), 185-197 (2001)
2. Rico-Juan, J., Calera, J., Carrasco, R.: Probabilistic k-testable tree-languages. In: Oliveira, A.L. (ed.) ICGI 2000. LNCS (LNAI), vol. 1891, pp. 221-228. Springer, Heidelberg (2000)
3. Abe, N., Mamitsuka, H.: Predicting protein secondary structure using stochastic tree grammars. Machine Learning Journal 29(2-3), 275-301 (1997)
4. Denis, F., Esposito, Y.: Rational stochastic languages, Technical report, LIF - Université de Provence (2006), http://hal.ccsd.cnrs.fr/ccsd- 00019728
5. Denis, F., Esposito, Y., Habrard, A.: Learning rational stochastic languages. In: Lugosi, G., Simon, H.U. (eds.) COLT 2006. LNCS (LNAI), vol. 4005, Springer, Heidelberg (2006)
6. Habrard, A., Denis, F., Esposito, Y.: Using pseudo-stochastic rational languages in probabilistic grammatical inference. In: Sakakibara, Y., Kobayashi, S., Sato, K., Nishino, T., Tomita, E. (eds.) ICGI 2006. LNCS (LNAI), vol. 4201, pp. 112-124. Springer, Heidelberg (2006)
7. Berstel, J., Reutenauer, C.: Recognizable formal power series on trees. Theoretical Computer Science 18, 115-148 (1982)
8. Esik, Z., Kuich, W.: Formal tree series. Journal of Automata, Languages and Combinatorics 8(2), 219-285 (2003)
9. Habrard, A., Oncina, J.: Learning multiplicity tree automata. In: Sakakibara, Y., Kobayashi, S., Sato, K., Nishino, T., Tomita, E. (eds.) ICGI 2006. LNCS (LNAI), vol. 4201, Springer, Heidelberg (2006)
10. Drewes, F., Vogler, H.: Learning deterministically recognizable tree serie. Journal of Automata, Languages and Combinatorics (2007)
11. Comon, H., Dauchet, M., Gilleron, R., Jacquemard, F., Lugiez, D., Tison, S., Tommasi, M.: Tree Automata Techniques and Applications (1997), Available from: http://www.grappa.univ-lille3.fr/tata
12. Wetherell, C.S.: Probabilistic languages: A review and some open questions. ACM Comput. Surv. 12(4), 361-379 (1980)
13. Vapnik, V.: Statistical Learning Theory. John Wiley, New York, NY (1998)
14. Lugosi, G.: Pattern classification and learning theory. In: Principles of Nonparametric Learning, Springer, Heidelberg (2002)
15. Hardy, G., Wright, M.: An introduction to the theory of numbers. Oxford University Press, Oxford (1979)
16. Denis, F., Esposito, Y.: Learning classes of probabilistic automata. In: ShaweTaylor, J., Singer, Y. (eds.) COLT 2004. LNCS (LNAI), vol. 3120, pp. 124-139. Springer, Heidelberg (2004)