Probabilistic inference, inference of probabilistic machines
- [Abe and Warmuth, 1992]
- N. Abe and M. Warmuth.
On the computational complexity of approximating distributions by probabilistic
automata.
Machine Learning, 9:205-260, 1992.
- [Angluin, 1988]
- D. Angluin.
Identifying languages from stochastic examples.
Technical Report YALEU/DCS/RR-614, Yale University, March 1988.
- [Carrasco and Oncina, 1994]
- R. Carrasco and
J. Oncina.
Learning stochastic regular grammars by means of a state merging method.
In Grammatical Inference and Applications, ICGI'94, number 862 in
Lecture Notes in Artificial Intelligence, pages 139-150. Springer Verlag,
1994.
- [Cook and Rozenfeld, 1974]
- C.M. Cook and
A. Rozenfeld.
Some experiments in grammatical inference.
In Computer Oriented Learning Process, pages 157-171, Bonas,
France, 1974. NATO Advanced Study Institute.
- [Dean et al., 1995]
- T. Dean, D. Angluin, k. Basye,
S. Engelson, l. Kaelbling, E. Kokkevis, and O. Maron.
Inferring finite automata with stochastic output functions and an application
to Map learning.
Machine Learning, 18:81-108, 1995.
- [Freund et al., 1993]
- Y. Freund, M. Kearns,
D. Ron, R. Rubinfeld, R. Schapire, and L. Sellie.
Efficient learning of typical automata from random walks.
In 25th ACM Symposium on the Theory of Computing, pages 315-324,
1993.
- [Gaines, 1979]
- F.J. Gaines.
Maryanski's grammatical inferencer.
IEEE Transactions on Computers, 27(1):62-64, 1979.
- [Grünwald, 1994]
- P. Grünwald.
Grammar inference and the minimum description length principle.
NeuroCOLT Technical Report Series NC-TR-94-015, ESPRIT Working Group in Neural
and Computational Learning, 1994.
- [Horning, 1969]
- J.J. Horning.
A Study of Grammatical Inference.
Ph. D. dissertation, Computer Science Department, Stanford University,
Stanford, California, 1969.
- [Kearns et al., 1994]
- M.J. Kearns, Y. Mansour,
D. Ron, R. Rubinfeld, R.E. Schapire, and L. Sellie.
On the learnability of discrete distributions.
In Proc. of the 25th Annual ACM Symposium on Theory of Computing,
pages 273-282, 1994.
- [Maryanski, 1974]
- F.J. Maryanski.
Inference of Probabilistic Grammars.
Ph. D. dissertation, University of Connecticut, 1974.
- [Ron et al., 1995]
- D. Ron, Y. Singer, and
N. Tishby.
On the learnability and usage of acyclic probabilistic automata.
In Computational Learning Theory, COLT'95, pages 31-40, 1995.
- [Stolcke and Omohundro, 1993]
- A. Stolcke and
S.M. Omohundro.
Hidden Markov Model induction by bayesian model merging.
In C.L. Giles, S.J. Hanton, and J.D. Cowan, editors, Advances in Neural
Information Processing Systems. MOrgan Kauffman, 1993.
- [Stolcke and Omohundro, 1994a]
- A. Stolcke and
S. Omohundro.
Inducing probabilistic grammars by bayesian model merging.
In Grammatical Inference and Applications, ICGI'94, number 862 in
Lecture Notes in Artificial Intelligence, pages 106-118. Springer Verlag,
1994.
- [Stolcke and Omohundro, 1994b]
- A. Stolcke and
S.M. Omohundro.
Best-first model merging for Hidden Markov Model induction.
Technical Report TR-94-003, ICSI, January 1994.
- [Stolcke, 1994]
- A. Stolcke.
Bayesian Learning of Probabilistic Language Models.
Ph. D. dissertation, University of California, 1994.
- [Tzeng, 1989a]
- W.-G. Tzeng.
The equivalence and learning of probabilistic automata.
In 30th Annual Symposium on Fundations of Computer Science, pages
268-273, 1989.
- [Tzeng, 1989b]
- W.-G. Tzeng.
A polynomial-time algorithm for the equivalence of probabilistic automata.
SIAM Journal Comput., 21(2):216-227, 1989.
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